From 4fac4c3dedfd2a19cb264c7c3692979aed280ace Mon Sep 17 00:00:00 2001 From: Lee Yang Date: Wed, 13 Nov 2024 11:41:40 -0800 Subject: [PATCH 01/22] Add support for platform runtime variants, e.g. photon (#1417) Signed-off-by: Lee Yang --- .../qualx/models/xgboost/combined.cfg | 2 +- .../qualx/models/xgboost/combined.json | 2 +- .../qualx/models/xgboost/combined.metrics | 208 ++++++++--------- .../models/xgboost/databricks-aws_photon.cfg | 1 + .../models/xgboost/databricks-aws_photon.json | 1 + .../xgboost/databricks-aws_photon.metrics | 109 +++++++++ .../qualx/models/xgboost/databricks-azure.cfg | 2 +- .../models/xgboost/databricks-azure.json | 2 +- .../models/xgboost/databricks-azure.metrics | 204 ++++++++--------- .../qualx/models/xgboost/dataproc.cfg | 2 +- .../qualx/models/xgboost/dataproc.json | 2 +- .../qualx/models/xgboost/dataproc.metrics | 214 +++++++++--------- .../resources/qualx/models/xgboost/emr.json | 2 +- .../qualx/models/xgboost/emr.metrics | 118 +++++----- .../resources/qualx/models/xgboost/onprem.cfg | 2 +- .../qualx/models/xgboost/onprem.json | 2 +- .../qualx/models/xgboost/onprem.metrics | 212 ++++++++--------- .../spark_rapids_tools/tools/qualx/model.py | 1 + .../tools/qualx/preprocess.py | 2 + .../tools/qualx/qualx_main.py | 122 ++++++++-- .../spark_rapids_tools/tools/qualx/util.py | 34 ++- 21 files changed, 728 insertions(+), 516 deletions(-) create mode 100644 user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-aws_photon.cfg create mode 100644 user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-aws_photon.json create mode 100644 user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-aws_photon.metrics diff --git a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.cfg b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.cfg index 43077e3b1..a71e4ac88 100644 --- 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InsertIntoHadoopFsRelationCommand,0.0077676065,0.06578073089700996,0.2479396088001299,0.0,0.0,0.0,0.0,1.0 -27,sr_totalBytesReadRatio,0.007221504,0.8361453565586155,1.3662214671113486,0.0,0.004273335926715613,0.240080503081491,1.2728366902983292,16.779651636748564 -28,executorRunTime_mean,0.0071591875,2366.6584062954435,9501.329853803001,6.0,318.93636363636364,800.1361473833383,1949.925602451221,228020.38461538462 -29,sw_bytesWrittenRatio,0.006407322,0.7806374593931262,1.2972364256017963,0.0,0.004150472420326595,0.22463455514071917,1.1903429883320307,16.779651636748564 -30,sr_localBlocksFetched_sum,0.005959179,49214.2634551495,225628.62132859995,0.0,129.0,1192.0,14217.0,3860026.0 -31,shuffle_write_bw,0.0053309235,152382.46464272073,286432.34421850665,0.0,1869.6975619919024,59718.23640727125,188672.94593715094,4415434.0 -32,maxMem,0.0051829726,17870057652.91329,11170076067.719357,455501414.0,10119177830.0,10119177830.0,25581060096.0,43359456460.0 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a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure.cfg +++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure.cfg @@ -1 +1 @@ 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\ No newline at end of file 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\ No newline at end of file diff --git a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure.json b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure.json index b569c8da7..1e16cab6c 100644 --- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure.json +++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure.json @@ -1 +1 @@ -{"learner":{"attributes":{},"feature_names":["numTasks_sum","duration_sum","duration_max","duration_min","duration_mean","input_recordsRead_sum","output_recordsWritten_sum","peakExecutionMemory_max","resultSerializationTime_sum","resultSize_max","sr_localBlocksFetched_sum","sr_remoteBlocksFetched_sum","sw_recordsWritten_sum","sqlOp_ColumnarToRow","sqlOp_Exchange","sqlOp_Execute InsertIntoHadoopFsRelationCommand","sqlOp_Scan parquet 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\ No newline at end of file diff --git a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure.metrics b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure.metrics index 27abdd04d..d5168e636 100644 --- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure.metrics +++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure.metrics @@ -1,109 +1,109 @@ ,feature,shap_value,mean,std,min,25%,50%,75%,max -0,executorCPUTime_mean,0.12423957,3083.661435888062,5116.536518124452,79.01805054151625,529.5195832704212,1391.1708930540242,3098.8835876649596,46123.548214285714 -1,sr_remoteBytesReadRatio,0.114727944,0.821447639429395,1.190295307104319,4.361993847958805e-07,0.004681915012233263,0.2507003788881129,1.3747557349907953,9.945049508262114 -2,sw_recordsWritten_sum,0.08057826,1374410117.7790263,3387308853.036538,200.0,1055515.5,70762368.0,1083955333.0,32214909337.0 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\ No newline at end of file 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a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/onprem.cfg +++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/onprem.cfg @@ -1 +1 @@ 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\ No newline at end of file +{"learner":{"generic_param":{"device":"cpu","fail_on_invalid_gpu_id":"0","n_jobs":"0","nthread":"0","random_state":"0","seed":"0","seed_per_iteration":"0","validate_parameters":"1"},"gradient_booster":{"gbtree_model_param":{"num_parallel_tree":"1","num_trees":"97"},"gbtree_train_param":{"process_type":"default","tree_method":"auto","updater":"grow_quantile_histmaker","updater_seq":"grow_quantile_histmaker"},"name":"gbtree","specified_updater":false,"tree_train_param":{"alpha":"0","cache_opt":"1","colsample_bylevel":"1","colsample_bynode":"1","colsample_bytree":"1","eta":"0.0459315479","gamma":"0.0072274562","grow_policy":"depthwise","interaction_constraints":"","lambda":"1","learning_rate":"0.0459315479","max_bin":"256","max_cat_threshold":"64","max_cat_to_onehot":"4","max_delta_step":"0","max_depth":"6","max_leaves":"0","min_child_weight":"2","min_split_loss":"0.0072274562","monotone_constraints":"()","refresh_leaf":"1","reg_alpha":"0","reg_lambda":"1","sampling_method":"uniform","sketch_ratio":"2","sparse_threshold":"0.20000000000000001","subsample":"0.656415164"},"updater":[{"hist_train_param":{"debug_synchronize":"0","max_cached_hist_node":"65536"},"name":"grow_quantile_histmaker"}]},"learner_model_param":{"base_score":"8.761862E-1","boost_from_average":"1","num_class":"0","num_feature":"108","num_target":"1"},"learner_train_param":{"booster":"gbtree","disable_default_eval_metric":"0","multi_strategy":"one_output_per_tree","objective":"reg:squarederror"},"metrics":[{"name":"mae"},{"name":"mape"}],"objective":{"name":"reg:squarederror","reg_loss_param":{"scale_pos_weight":"1"}}},"version":[2,0,3]} \ No newline at end of file diff --git a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/onprem.json b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/onprem.json index 691af8005..0906f9a53 100644 --- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/onprem.json +++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/onprem.json @@ -1 +1 @@ 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a/user_tools/src/spark_rapids_tools/tools/qualx/preprocess.py b/user_tools/src/spark_rapids_tools/tools/qualx/preprocess.py index 0aadd6974..d203bbc7f 100644 --- a/user_tools/src/spark_rapids_tools/tools/qualx/preprocess.py +++ b/user_tools/src/spark_rapids_tools/tools/qualx/preprocess.py @@ -92,6 +92,7 @@ 'scan_time', 'shuffle_read_bw', 'shuffle_write_bw', + 'sparkRuntime', 'sparkVersion', 'sqlID', 'sqlOp_AQEShuffleRead', @@ -541,6 +542,7 @@ def combine_tables(table_name: str) -> pd.DataFrame: 'sqlID', 'Duration', 'description', + 'sparkRuntime', 'sparkVersion', 'pluginEnabled', 'resourceProfileId', diff --git a/user_tools/src/spark_rapids_tools/tools/qualx/qualx_main.py b/user_tools/src/spark_rapids_tools/tools/qualx/qualx_main.py index bde6da008..d5f4c9177 100644 --- a/user_tools/src/spark_rapids_tools/tools/qualx/qualx_main.py +++ b/user_tools/src/spark_rapids_tools/tools/qualx/qualx_main.py @@ -62,7 +62,7 @@ logger = get_logger(__name__) -def _get_model_path(platform: str, model: Optional[str]) -> Path: +def _get_model_path(platform: str, model: Optional[str], variant: Optional[str] = None) -> Path: if model is not None: # if "model" is provided if CspPath.is_file_path(model, raise_on_error=False): @@ -84,29 +84,65 @@ def _get_model_path(platform: str, model: Optional[str]) -> Path: if not model_path.exists(): raise FileNotFoundError(f'Model JSON file for {model} not found at: {model_path}') else: - # if "model" not provided, try loading pre-trained model by "platform" - model_path = Path(Utils.resource_path(f'qualx/models/xgboost/{platform}.json')) + # if "model" not provided, try loading pre-trained model by "platform" (and "variant") + variant_suffixes = { + 'SPARK': '', + 'SPARK_RAPIDS': '', + 'PHOTON': '_photon' + } + variant_suffix = variant_suffixes.get(variant, '') + model_path = Path(Utils.resource_path(f'qualx/models/xgboost/{platform}{variant_suffix}.json')) if not model_path.exists(): - raise ValueError(f'Platform [{platform}] does not have a pre-trained model, ' - 'please specify --model or choose another platform.') + if not variant_suffix: + raise ValueError( + f'Platform [{platform}] does not have a pre-trained model, ' + 'please specify --model or choose another platform.' + ) + # variant model not found, try base platform model + model_path = Path(Utils.resource_path(f'qualx/models/xgboost/{platform}.json')) + if model_path.exists(): + logger.warning( + 'Platform [%s%s] does not have a pretrained model, using [%s] model', + platform, + variant_suffix, + platform, + ) + else: + raise ValueError( + f'Platform [{platform}{variant_suffix}] does not have a pre-trained model, ' + 'please specify --model or choose another platform.' + ) return model_path def _get_model(platform: str, - model: Optional[str] = None) -> Booster: + model: Optional[str] = None, + variant: Optional[str] = None) -> Booster: """ - Load the XGBoost model from the specified path or use the pre-trained model for the platform. - The "model" has a precedence over the other input options. If it is undefined, this function checks - if it is a valid path or a string literal that represents a model name. - Finally, the platform will be used to define the path of the model file if the model is not defined. - :param platform: name of the platform used to define the path of the pre-trained model. - The platform should match a JSON file in the "resources" directory. - :param model: Either a file or a pre-trained model name. If the input is a string literal that - cannot be a file path, then it is assumed that the file is located under the - resources directory. - :return: xgb.Booster loading the model file. + Load the XGBoost model from a specified path or use the pre-trained model for the platform. + + The "model" argument has a precedence over the other input options. If it is defined, this function checks + if it is a valid path to an XGBoost model or a string literal matching a pre-trained model name. + If "model" is not defined, then the pre-trained model matching "platform" will be used. + + Parameters + ---------- + platform: str + Name of the platform used to define the path of the pre-trained model. + The platform should match a JSON file in the "resources" directory. + model: str + Either a path to a model file or the name of a pre-trained model. + If the input is a string literal that cannot be a file path, then it is assumed that the file + is located under the resources directory. + variant: str + Value of the `sparkRuntime` column from the `application_information.csv` file from the profiler tool. + If set, will be used to load a pre-trained model matching the platform and variant. + + Returns + ------- + xgb.Booster model file. """ - model_path = _get_model_path(platform, model) + model_path = _get_model_path(platform, model, variant) logger.info('Loading model from: %s', model_path) xgb_model = xgb.Booster() xgb_model.load_model(model_path) @@ -550,7 +586,6 @@ def predict( qual_tool_filter: Optional[str] = 'stage') -> pd.DataFrame: """Predict GPU speedup given CPU logs.""" - xgb_model = _get_model(platform, model=model) node_level_supp, qual_tool_output, qual_metrics = _get_qual_data(qual) # create a DataFrame with default predictions for all app IDs. # this will be used for apps without predictions. @@ -581,21 +616,63 @@ def predict( ) if profile_df.empty: raise ValueError('Data preprocessing resulted in an empty dataset. Speedup predictions will default to 1.0.') + # reset appName to original profile_df['appName'] = profile_df['appId'].map(app_id_name_map) + # handle platform variants (for CPU eventlogs) + variants = profile_df.loc[profile_df.runType == 'CPU']['sparkRuntime'].unique().tolist() + if len(variants) > 1: + # platform variants found in dataset + if model and model != platform: + # mixing platform and model args w/ variants is ambiguous + raise ValueError( + f'Platform variants found in data, but model ({model}) does not match platform ({platform}).' + ) + # group input data by model variant + prediction_groups = {} + for variant in variants: + xgb_model = _get_model(platform, None, variant) # variants only supported for pre-trained platform models + variant_profile_df = profile_df.loc[ + (profile_df['sparkRuntime'] == variant) | (profile_df['sparkRuntime'] == 'SPARK_RAPIDS') + ] + prediction_groups[xgb_model] = variant_profile_df + else: + # single platform + xgb_model = _get_model(platform, model) + prediction_groups = { + xgb_model: profile_df + } + filter_str = ( f'with {qual_tool_filter} filtering' if node_level_supp is not None and any(profile_df['fraction_supported'] != 1.0) else 'raw' ) logger.info('Predicting dataset (%s): %s', filter_str, dataset_name) - features, feature_cols, label_col = extract_model_features(profile_df) - per_sql_summary = None + try: + features_list = [] + predictions_list = [] + for xgb_model, prof_df in prediction_groups.items(): + features, feature_cols, label_col = extract_model_features(prof_df) + features_index = features.index + features_list.append(features) + predictions = predict_model(xgb_model, features, feature_cols, label_col) + predictions.index = features_index + predictions_list.append(predictions) + features = pd.concat(features_list) + features.sort_index(inplace=True) + predictions = pd.concat(predictions_list) + predictions.sort_index(inplace=True) + except XGBoostError as e: + # ignore and continue + logger.error(e) + + # write output files per_app_summary = None try: - per_sql_summary = predict_model(xgb_model, features, feature_cols, label_col) + per_sql_summary = predictions # save features, feature importance, and shapley values per dataset name if output_info: @@ -625,9 +702,6 @@ def predict( per_app_summary['appDuration'].sum() / per_app_summary['appDuration_pred'].sum() ) print(f'Dataset estimated speedup: {dataset_speedup:.2f}') - except XGBoostError as e: - # ignore and continue - logger.error(e) except Exception as e: # pylint: disable=broad-except # ignore and continue logger.error(e) diff --git a/user_tools/src/spark_rapids_tools/tools/qualx/util.py b/user_tools/src/spark_rapids_tools/tools/qualx/util.py index c7381a48b..831721ff3 100644 --- a/user_tools/src/spark_rapids_tools/tools/qualx/util.py +++ b/user_tools/src/spark_rapids_tools/tools/qualx/util.py @@ -123,14 +123,30 @@ def get_cache_dir() -> str: def get_dataset_platforms(dataset: str) -> Tuple[List[str], str]: """Return list of platforms and dataset parent directory from a string path. + Note: the '_' character is reserved to delimit variants of a platform, e.g. different execution engines + like Photon or Velox. Example: `databricks-aws_photon`. + + Platform variants may be used when separate qualx models are trained for the base platform and the variant. + The platform variant will be used to identify the qualx model, while the base platform will be used when + invoking the Profiler/Qualification tools. + Parameters ---------- dataset: str Path to datasets directory, datasets/platform directory, or datasets/platform/dataset.json file. + + Returns + ------- + platforms: List[str] + List of platforms associated with the dataset path. + dataset_base: str + Parent directory of datasets directory. """ supported_platforms = [ 'databricks-aws', + 'databricks-aws_photon', 'databricks-azure', + 'databricks-azure_photon', 'dataproc', 'emr', 'onprem' @@ -139,17 +155,23 @@ def get_dataset_platforms(dataset: str) -> Tuple[List[str], str]: splits = Path(dataset).parts basename = splits[-1] if basename.endswith('.json'): - # dataset JSON + # single dataset JSON platforms = [splits[-2]] dataset_base = os.path.join(*splits[:-2]) elif basename in supported_platforms: - # platform directory + # single platform directory platforms = [basename] dataset_base = os.path.join(*splits[:-1]) else: - # datasets directory + # otherwise, assume "datasets" directory platforms = os.listdir(dataset) dataset_base = dataset + + # validate platforms + for platform in platforms: + if platform not in supported_platforms: + raise ValueError(f'Unsupported platform: {platform}') + return platforms, dataset_base @@ -230,6 +252,7 @@ def run_profiler_tool(platform: str, eventlog: str, output_dir: str) -> None: logger.info('Running profiling on: %s', eventlog) logger.info('Saving output to: %s', output_dir) + platform_base = platform.split('_')[0] # remove any platform variants when invoking profiler cmds = [] eventlogs = find_eventlogs(eventlog) for log in eventlogs: @@ -244,7 +267,7 @@ def run_profiler_tool(platform: str, eventlog: str, output_dir: str) -> None: # f'spark_rapids_user_tools {platform} profiling --csv --eventlogs {log} --local_folder {output}' 'java -Xmx64g -cp $SPARK_RAPIDS_TOOLS_JAR:$SPARK_HOME/jars/*:$SPARK_HOME/assembly/target/scala-2.12/jars/* ' 'com.nvidia.spark.rapids.tool.profiling.ProfileMain ' - f'--platform {platform} --csv --output-sql-ids-aligned -o {output} {log}' + f'--platform {platform_base} --csv --output-sql-ids-aligned -o {output} {log}' ) cmds.append(cmd) run_commands(cmds) @@ -255,6 +278,7 @@ def run_qualification_tool(platform: str, eventlog: str, output_dir: str) -> Non logger.info('Running qualification on: %s', eventlog) logger.info('Saving output to: %s', output_dir) + platform_base = platform.split('_')[0] # remove any platform variants when invoking qualification cmds = [] eventlogs = find_eventlogs(eventlog) for log in eventlogs: @@ -268,7 +292,7 @@ def run_qualification_tool(platform: str, eventlog: str, output_dir: str) -> Non # --per-sql --eventlogs {log} --local_folder {output}' 'java -Xmx32g -cp $SPARK_RAPIDS_TOOLS_JAR:$SPARK_HOME/jars/*:$SPARK_HOME/assembly/target/scala-2.12/jars/* ' 'com.nvidia.spark.rapids.tool.qualification.QualificationMain ' - f'--platform {platform} --per-sql -o {output} {log}' + f'--platform {platform_base} --per-sql -o {output} {log}' ) cmds.append(cmd) run_commands(cmds) From acec193eed77f0f3614215af4de30579a15c855e Mon Sep 17 00:00:00 2001 From: Matt Ahrens Date: Wed, 13 Nov 2024 21:27:17 -0600 Subject: [PATCH 02/22] Changing autotuner memory error to warning in comments (#1418) * Changing autotuner memory issue from error to warning in output Signed-off-by: mattahrens * Changing autotuner memory issue from error to warning in output - updating unit tests Signed-off-by: mattahrens * Removing trailing space in comment Signed-off-by: mattahrens --------- Signed-off-by: mattahrens --- .../spark/rapids/tool/profiling/AutoTuner.scala | 13 ++++++------- .../rapids/tool/profiling/AutoTunerSuite.scala | 10 +++++++++- 2 files changed, 15 insertions(+), 8 deletions(-) diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/AutoTuner.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/AutoTuner.scala index 6d1a2c165..ec2d20725 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/AutoTuner.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/AutoTuner.scala @@ -539,12 +539,12 @@ class AutoTuner( // For now just throw so we don't get any tunings and its obvious to user this isn't a good // setup. In the future we may just recommend them to use larger nodes. This would be more // ideal once we hook up actual executor heap from an eventlog vs what user passes in. - throwNotEnoughMemException(minExecHeapMem + minOverhead) + warnNotEnoughMem(minExecHeapMem + minOverhead) (0, 0, 0, false) } else { val leftOverMemUsingMinHeap = containerMem - minExecHeapMem if (leftOverMemUsingMinHeap < 0) { - throwNotEnoughMemException(minExecHeapMem + minOverhead) + warnNotEnoughMem(minExecHeapMem + minOverhead) } // Pinned memory uses any unused space up to 4GB. Spill memory is same size as pinned. val pinnedMem = Math.min(MAX_PINNED_MEMORY_MB, (leftOverMemUsingMinHeap / 2)).toLong @@ -556,13 +556,12 @@ class AutoTuner( } } - private def throwNotEnoughMemException(minSize: Long): Unit = { + private def warnNotEnoughMem(minSize: Long): Unit = { // in the future it would be nice to enhance the error message with a recommendation of size - val msg = "This node/worker configuration is not ideal for using the Spark Rapids " + - "Accelerator because it doesn't have enough memory for the executors. " + + val msg = "This node/worker configuration is not ideal for using the Spark Rapids\n" + + "Accelerator because it doesn't have enough memory for the executors.\n" + s"We recommend using nodes/workers with more memory. Need at least ${minSize}MB memory." - logError(msg) - throw new IllegalArgumentException(msg) + appendComment(msg) } /** diff --git a/core/src/test/scala/com/nvidia/spark/rapids/tool/profiling/AutoTunerSuite.scala b/core/src/test/scala/com/nvidia/spark/rapids/tool/profiling/AutoTunerSuite.scala index cc2f806eb..94baa8fc2 100644 --- a/core/src/test/scala/com/nvidia/spark/rapids/tool/profiling/AutoTunerSuite.scala +++ b/core/src/test/scala/com/nvidia/spark/rapids/tool/profiling/AutoTunerSuite.scala @@ -310,7 +310,15 @@ class AutoTunerSuite extends FunSuite with BeforeAndAfterEach with Logging { val platform = PlatformFactory.createInstance(PlatformNames.DATAPROC, clusterPropsOpt) val autoTuner = AutoTuner.buildAutoTunerFromProps(dataprocWorkerInfo, getGpuAppMockInfoProvider, platform) - assertThrows[IllegalArgumentException](autoTuner.getRecommendedProperties()) + val (properties, comments) = autoTuner.getRecommendedProperties() + val autoTunerOutput = Profiler.getAutoTunerResultsAsString(properties, comments) + // scalastyle:off line.size.limit + val expectedComment = + s"""This node/worker configuration is not ideal for using the Spark Rapids +Accelerator because it doesn't have enough memory for the executors. +We recommend using nodes/workers with more memory. Need at least 7796MB memory.""".stripMargin.replaceAll("\n", "") + // scalastyle:on line.size.limit + assert(autoTunerOutput.replaceAll("\n", "").contains(expectedComment)) } test("Load cluster properties with CPU memory missing") { From 5dd244ab73d036bfe0ba49302d41999da54e3ed5 Mon Sep 17 00:00:00 2001 From: Matt Ahrens Date: Thu, 14 Nov 2024 12:53:38 -0600 Subject: [PATCH 03/22] Adding EMR-specific tunings for shuffle manager and ignoring jar (#1419) * Adding EMR-specific tunings for shuffle manager and ignoring Spark RAPIDS jar Signed-off-by: Matt Ahrens * Fixing trailing comma issue caught by scala style checker Signed-off-by: Matt Ahrens * Moving path recommendations check as bool in platform.scala Signed-off-by: Matt Ahrens --------- Signed-off-by: Matt Ahrens --- .../nvidia/spark/rapids/tool/Platform.scala | 6 ++ .../rapids/tool/profiling/AutoTuner.scala | 12 +++- .../tool/profiling/AutoTunerSuite.scala | 68 ++++++++++++++++++- 3 files changed, 84 insertions(+), 2 deletions(-) diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/Platform.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/Platform.scala index 6bf62a537..5ac20b05e 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/Platform.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/Platform.scala @@ -365,6 +365,11 @@ abstract class Platform(var gpuDevice: Option[GpuDevice], */ def isPlatformCSP: Boolean = false + /** + * Indicate if the platform requires path recommendations + */ + def requirePathRecommendations: Boolean = true + /** * The maximum number of Gpus any instance in this platform supports. */ @@ -641,6 +646,7 @@ class EmrPlatform(gpuDevice: Option[GpuDevice], override val defaultGpuDevice: GpuDevice = A10GGpu override def isPlatformCSP: Boolean = true + override def requirePathRecommendations: Boolean = false override def getRetainedSystemProps: Set[String] = Set("EMR_CLUSTER_ID") diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/AutoTuner.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/AutoTuner.scala index ec2d20725..783726cd9 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/AutoTuner.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/AutoTuner.scala @@ -722,7 +722,9 @@ class AutoTuner( recommendShufflePartitions() recommendKryoSerializerSetting() recommendGCProperty() - recommendClassPathEntries() + if (platform.requirePathRecommendations) { + recommendClassPathEntries() + } recommendSystemProperties() } @@ -756,6 +758,14 @@ class AutoTuner( case ver if ver.contains("11.3") => "330db" case _ => "332db" } + } else if (sparkVersion.contains("amzn")) { + sparkVersion match { + case ver if ver.contains("3.5.1") => "351" + case ver if ver.contains("3.5.0") => "350" + case ver if ver.contains("3.4.1") => "341" + case ver if ver.contains("3.4.0") => "340" + case _ => "332" + } } else { shuffleManagerVersion } diff --git a/core/src/test/scala/com/nvidia/spark/rapids/tool/profiling/AutoTunerSuite.scala b/core/src/test/scala/com/nvidia/spark/rapids/tool/profiling/AutoTunerSuite.scala index 94baa8fc2..d61440195 100644 --- a/core/src/test/scala/com/nvidia/spark/rapids/tool/profiling/AutoTunerSuite.scala +++ b/core/src/test/scala/com/nvidia/spark/rapids/tool/profiling/AutoTunerSuite.scala @@ -32,7 +32,6 @@ import org.yaml.snakeyaml.{DumperOptions, Yaml} import org.apache.spark.internal.Logging import org.apache.spark.sql.rapids.tool.util.WebCrawlerUtil - case class DriverInfoProviderMockTest(unsupportedOps: Seq[DriverLogUnsupportedOperators]) extends BaseDriverLogInfoProvider(None) { override def getUnsupportedOperators: Seq[DriverLogUnsupportedOperators] = unsupportedOps @@ -2559,4 +2558,71 @@ We recommend using nodes/workers with more memory. Need at least 7796MB memory." // scalastyle:on line.size.limit assert(expectedResults == autoTunerOutput) } + + test("Test EMR sets shuffle manager properly and doesn't need Spark RAPIDS jar") { + // mock the properties loaded from eventLog + val logEventsProps: mutable.Map[String, String] = + mutable.LinkedHashMap[String, String]( + "spark.executor.cores" -> "32", + "spark.executor.instances" -> "1", + "spark.executor.memory" -> "80g", + "spark.executor.resource.gpu.amount" -> "1", + "spark.executor.instances" -> "1" + ) + val emrWorkerInfo = buildWorkerInfoAsString(None, Some(32), + Some("212992MiB"), Some(5), Some(4), Some(T4Gpu.getMemory), Some(T4Gpu.toString)) + val infoProvider = getMockInfoProvider(0, Seq(0), Seq(0.0), + logEventsProps, Some("3.4.1-amzn-1")) + val clusterPropsOpt = loadClusterPropertiesFromContent(emrWorkerInfo) + val platform = PlatformFactory.createInstance(PlatformNames.EMR, clusterPropsOpt) + val autoTuner: AutoTuner = AutoTuner.buildAutoTunerFromProps(emrWorkerInfo, infoProvider, + platform) + val (properties, comments) = autoTuner.getRecommendedProperties() + val autoTunerOutput = Profiler.getAutoTunerResultsAsString(properties, comments) + // scalastyle:off line.size.limit + val expectedResults = + s"""| + |Spark Properties: + |--conf spark.executor.instances=20 + |--conf spark.executor.memory=24000m + |--conf spark.executor.memoryOverhead=15564m + |--conf spark.rapids.memory.pinnedPool.size=4096m + |--conf spark.rapids.shuffle.multiThreaded.reader.threads=48 + |--conf spark.rapids.shuffle.multiThreaded.writer.threads=48 + |--conf spark.rapids.sql.batchSizeBytes=2147483647 + |--conf spark.rapids.sql.concurrentGpuTasks=2 + |--conf spark.rapids.sql.format.parquet.multithreaded.combine.waitTime=1000 + |--conf spark.rapids.sql.multiThreadedRead.numThreads=64 + |--conf spark.rapids.sql.reader.multithreaded.combine.sizeBytes=10485760 + |--conf spark.shuffle.manager=com.nvidia.spark.rapids.spark341.RapidsShuffleManager + |--conf spark.sql.adaptive.advisoryPartitionSizeInBytes=128m + |--conf spark.sql.adaptive.coalescePartitions.minPartitionSize=4m + |--conf spark.sql.files.maxPartitionBytes=512m + |--conf spark.sql.shuffle.partitions=200 + |--conf spark.task.resource.gpu.amount=0.03125 + | + |Comments: + |- 'spark.executor.memoryOverhead' was not set. + |- 'spark.rapids.memory.pinnedPool.size' was not set. + |- 'spark.rapids.shuffle.multiThreaded.reader.threads' was not set. + |- 'spark.rapids.shuffle.multiThreaded.writer.threads' was not set. + |- 'spark.rapids.sql.batchSizeBytes' was not set. + |- 'spark.rapids.sql.concurrentGpuTasks' was not set. + |- 'spark.rapids.sql.format.parquet.multithreaded.combine.waitTime' was not set. + |- 'spark.rapids.sql.multiThreadedRead.numThreads' was not set. + |- 'spark.rapids.sql.reader.multithreaded.combine.sizeBytes' was not set. + |- 'spark.shuffle.manager' was not set. + |- 'spark.sql.adaptive.advisoryPartitionSizeInBytes' was not set. + |- 'spark.sql.adaptive.autoBroadcastJoinThreshold' was not set. + |- 'spark.sql.adaptive.coalescePartitions.minPartitionSize' was not set. + |- 'spark.sql.adaptive.enabled' should be enabled for better performance. + |- 'spark.sql.files.maxPartitionBytes' was not set. + |- 'spark.sql.shuffle.partitions' was not set. + |- 'spark.task.resource.gpu.amount' was not set. + |- RAPIDS Accelerator for Apache Spark jar is missing in "spark.plugins". Please refer to https://docs.nvidia.com/spark-rapids/user-guide/latest/getting-started/overview.html + |- ${AutoTuner.classPathComments("rapids.shuffle.jars")} + |""".stripMargin + // scalastyle:on line.size.limit + assert(expectedResults == autoTunerOutput) + } } From 43825d8153b8208d7b6fee607e765bcee8e38cbe Mon Sep 17 00:00:00 2001 From: Partho Sarthi Date: Thu, 14 Nov 2024 11:37:51 -0800 Subject: [PATCH 04/22] Add qualification support for Photon jobs in the Python Tool (#1409) * Add support for different speedup threshold in Photon Signed-off-by: Partho Sarthi * Add speed up strategy per app Signed-off-by: Partho Sarthi * Assign app execution engine and categorize speedup based on engine type Signed-off-by: Partho Sarthi * Add E2E test cases Signed-off-by: Partho Sarthi * Rename App Execution Engine to Execution Engine Signed-off-by: Partho Sarthi * Rename loop variables Signed-off-by: Partho Sarthi * Address review comments and parse spark runtime Signed-off-by: Partho Sarthi * Revert "Add E2E test cases" This reverts commit 8921a853 Signed-off-by: Partho Sarthi * Buffer logging Signed-off-by: Partho Sarthi * Add directory list helper methods in CspFs and Photon comment Signed-off-by: Partho Sarthi * Use create_sub_path() to keep protocol intact Signed-off-by: Partho Sarthi --------- Signed-off-by: Partho Sarthi --- .../rapids/qualification.py | 74 +++++++++++++++++-- .../spark_rapids_pytools/rapids/tool_ctxt.py | 7 +- .../resources/qualification-conf.yaml | 66 ++++++++++++----- .../src/spark_rapids_tools/exceptions.py | 6 +- .../spark_rapids_tools/storagelib/cspfs.py | 34 ++++++++- .../tools/speedup_category.py | 51 ++++++++++--- 6 files changed, 200 insertions(+), 38 deletions(-) diff --git a/user_tools/src/spark_rapids_pytools/rapids/qualification.py b/user_tools/src/spark_rapids_pytools/rapids/qualification.py index 7ceb4d684..921dcc9b5 100644 --- a/user_tools/src/spark_rapids_pytools/rapids/qualification.py +++ b/user_tools/src/spark_rapids_pytools/rapids/qualification.py @@ -30,6 +30,7 @@ from spark_rapids_pytools.common.utilities import Utils, TemplateGenerator from spark_rapids_pytools.rapids.rapids_tool import RapidsJarTool from spark_rapids_tools.enums import QualFilterApp, QualEstimationModel +from spark_rapids_tools.storagelib import CspFs from spark_rapids_tools.tools.additional_heuristics import AdditionalHeuristics from spark_rapids_tools.tools.cluster_config_recommender import ClusterConfigRecommender from spark_rapids_tools.tools.qualx.qualx_main import predict @@ -289,12 +290,12 @@ def __build_global_report_summary(self, total_apps: pd.DataFrame, unsupported_ops_df: pd.DataFrame, output_files_info: JSONPropertiesContainer) -> QualificationSummary: + # TODO: This method does a lot of critical but unrelated work. Refactor this into smaller steps/methods + # to improve readability and maintainability. if all_apps.empty: # No need to run saving estimator or process the data frames. return QualificationSummary(total_apps=total_apps, tools_processed_apps=all_apps) - unsupported_ops_obj = UnsupportedOpsStageDuration(self.ctxt.get_value('local', 'output', - 'unsupportedOperators')) # Generate the statistics report try: stats_report = SparkQualificationStats(ctxt=self.ctxt) @@ -303,37 +304,52 @@ def __build_global_report_summary(self, self.logger.error('Failed to generate the statistics report: %s', e) # Calculate unsupported operators stage duration before grouping + unsupported_ops_obj = UnsupportedOpsStageDuration( + self.ctxt.get_value('local', 'output', 'unsupportedOperators')) all_apps = unsupported_ops_obj.prepare_apps_with_unsupported_stages(all_apps, unsupported_ops_df) apps_pruned_df = self.__remap_columns_and_prune(all_apps) + # Apply additional heuristics to skip apps not suitable for GPU acceleration heuristics_ob = AdditionalHeuristics( props=self.ctxt.get_value('local', 'output', 'additionalHeuristics'), tools_output_dir=self.ctxt.get_rapids_output_folder(), output_file=output_files_info.get_value('intermediateOutput', 'files', 'heuristics', 'path')) apps_pruned_df = heuristics_ob.apply_heuristics(apps_pruned_df) - speedup_category_ob = SpeedupCategory(self.ctxt.get_value('local', 'output', 'speedupCategories')) + # Group the applications and recalculate metrics apps_grouped_df, group_notes = self.__group_apps_by_name(apps_pruned_df) - df_final_result = speedup_category_ob.build_category_column(apps_grouped_df) + + # Assign the runtime type (Spark/Photon etc.) and speedup categories (Small/Medium/Large) to each application. + # Note: Strategy for speedup categorization will be based on the execution engine of the application. + apps_with_runtime_df = self._assign_spark_runtime_to_apps(apps_grouped_df) + speedup_category_confs = self.ctxt.get_value('local', 'output', 'speedupCategories') + speedup_category_ob = SpeedupCategory(speedup_category_confs) + df_final_result = speedup_category_ob.build_category_column(apps_with_runtime_df) + + # Generate the cluster shape report reshaped_notes = self.__generate_cluster_shape_report() report_comments = [group_notes] if group_notes else [] if reshaped_notes: report_comments.append(reshaped_notes) + # Write the final result to the output file csv_out = output_files_info.get_value('summary', 'path') if not df_final_result.empty: self.logger.info('Generating GPU Estimated Speedup: as %s', csv_out) df_final_result.to_csv(csv_out, float_format='%.2f') + # Add columns for cluster configuration recommendations and tuning configurations to the processed_apps. recommender = ClusterConfigRecommender(self.ctxt) df_final_result = recommender.add_cluster_and_tuning_recommendations(df_final_result) - # Merge the total_apps with the processed_apps to get the Event Log df_final_result = pd.merge(df_final_result, total_apps[['Event Log', 'AppID']], left_on='App ID', right_on='AppID') + # Write the app metadata app_metadata_info = output_files_info.get_value('appMetadata') config_recommendations_info = output_files_info.get_value('configRecommendations') self._write_app_metadata(df_final_result, app_metadata_info, config_recommendations_info) + + # Return the summary return QualificationSummary(total_apps=total_apps, tools_processed_apps=df_final_result, comments=report_comments) @@ -595,6 +611,54 @@ def _read_qualification_output_file(self, report_name_key: str, file_format_key: report_file_path = FSUtil.build_path(self.ctxt.get_rapids_output_folder(), report_file_name) return pd.read_csv(report_file_path) + def _read_qualification_metric_file(self, file_name: str) -> Dict[str, pd.DataFrame]: + """ + Helper method to read metric files from the qualification tool's output metric folder. + Returns a dictionary of DataFrames, where each key is an application ID, and each + DataFrame contains the corresponding application's metrics data. + Example: + { + 'appId1': pd.DataFrame(...), + 'appId2': pd.DataFrame(...), + } + :param file_name: Name of the metric file to read from each application's folder + """ + metrics = {} + root_metric_dir = self.ctxt.get_metrics_output_folder() + apps_with_missing_metrics = [] + for metric_dir in CspFs.list_all_dirs(root_metric_dir): + app_id_str = metric_dir.base_name() + report_file_path = metric_dir.create_sub_path(file_name) + try: + metrics[app_id_str] = pd.read_csv(str(report_file_path)) + except Exception: # pylint: disable=broad-except + # Some apps may not have the given metrics file, we should ensure + # that the dictionary contains entries for all apps to avoid KeyErrors + # and maintain consistency in processing. + metrics[app_id_str] = pd.DataFrame() + apps_with_missing_metrics.append(app_id_str) + + # Log apps with missing metrics files + if apps_with_missing_metrics: + self.logger.warning('Unable to read metrics file \'%s\' for apps: %s', file_name, + ', '.join(apps_with_missing_metrics)) + return metrics + + def _assign_spark_runtime_to_apps(self, tools_processed_apps: pd.DataFrame) -> pd.DataFrame: + """ + Assigns the Spark Runtime (Spark/Photon) to each application. This will be used to categorize + applications into speedup categories (Small/Medium/Large). + """ + app_info_dict = self._read_qualification_metric_file('application_information.csv') + # Rename columns from each DataFrame in the app_info_dict and merge them with the tools_processed_apps + merged_dfs = [] + for df in app_info_dict.values(): + merged_dfs.append( + df[['appId', 'sparkRuntime']].rename(columns={'appId': 'App ID', 'sparkRuntime': 'Spark Runtime'}) + ) + spark_runtime_df = pd.concat(merged_dfs, ignore_index=True) + return tools_processed_apps.merge(spark_runtime_df, on='App ID', how='left') + @dataclass class QualificationAsLocal(Qualification): diff --git a/user_tools/src/spark_rapids_pytools/rapids/tool_ctxt.py b/user_tools/src/spark_rapids_pytools/rapids/tool_ctxt.py index e0756784b..7e850dcfa 100644 --- a/user_tools/src/spark_rapids_pytools/rapids/tool_ctxt.py +++ b/user_tools/src/spark_rapids_pytools/rapids/tool_ctxt.py @@ -25,7 +25,7 @@ from spark_rapids_pytools.common.prop_manager import YAMLPropertiesContainer from spark_rapids_pytools.common.sys_storage import FSUtil from spark_rapids_pytools.common.utilities import ToolLogging, Utils -from spark_rapids_tools import CspEnv +from spark_rapids_tools import CspEnv, CspPath from spark_rapids_tools.utils import Utilities @@ -215,6 +215,11 @@ def get_rapids_output_folder(self) -> str: return root_dir return FSUtil.build_path(root_dir, rapids_subfolder) + def get_metrics_output_folder(self) -> CspPath: + root_dir = CspPath(self.get_rapids_output_folder()) + metrics_subfolder = self.get_value('toolOutput', 'metricsSubFolder') + return root_dir.create_sub_path(metrics_subfolder) + def get_log4j_properties_file(self) -> str: return self.get_value_silent('toolOutput', 'textFormat', 'log4jFileName') diff --git a/user_tools/src/spark_rapids_pytools/resources/qualification-conf.yaml b/user_tools/src/spark_rapids_pytools/resources/qualification-conf.yaml index c6edb6431..8e998011c 100644 --- a/user_tools/src/spark_rapids_pytools/resources/qualification-conf.yaml +++ b/user_tools/src/spark_rapids_pytools/resources/qualification-conf.yaml @@ -1,6 +1,7 @@ toolOutput: completeOutput: true subFolder: rapids_4_spark_qualification_output + metricsSubFolder: raw_metrics textFormat: summaryLog: fileName: rapids_4_spark_qualification_output.log @@ -148,6 +149,7 @@ local: - 'App Name' - 'Event Log' - 'Cluster Info' + - 'Spark Runtime' - 'Estimated GPU Speedup Category' - 'Full Cluster Config Recommendations*' - 'GPU Config Recommendation Breakdown*' @@ -254,27 +256,51 @@ local: speedupColumnName: 'Estimated GPU Speedup' categoryColumnName: 'Estimated GPU Speedup Category' heuristicsColumnName: 'Skip by Heuristics' - categories: - - title: 'Not Applicable' - lowerBound: -1000000.0 - upperBound: 1.3 - - title: 'Small' - lowerBound: 1.3 - upperBound: 2.0 - - title: 'Medium' - lowerBound: 2.0 - upperBound: 3.0 - - title: 'Large' - lowerBound: 3.0 - upperBound: 1000000.0 - eligibilityConditions: - - columnName: 'Estimated GPU Speedup' - lowerBound: 1.3 - upperBound: 1000000.0 - - columnName: 'Unsupported Operators Stage Duration Percent' - lowerBound: 0.0 - upperBound: 25.0 + sparkRuntimeColumnName: 'Spark Runtime' defaultCategory: 'Not Recommended' + strategies: + spark: # Spark specific speedup categories + categories: + - title: 'Not Applicable' + lowerBound: -1000000.0 + upperBound: 1.3 + - title: 'Small' + lowerBound: 1.3 + upperBound: 2.0 + - title: 'Medium' + lowerBound: 2.0 + upperBound: 3.0 + - title: 'Large' + lowerBound: 3.0 + upperBound: 1000000.0 + eligibilityConditions: + - columnName: 'Estimated GPU Speedup' + lowerBound: 1.3 + upperBound: 1000000.0 + - columnName: 'Unsupported Operators Stage Duration Percent' + lowerBound: 0.0 + upperBound: 25.0 + photon: # Photon specific speedup categories + categories: + - title: 'Not Applicable' + lowerBound: -1000000.0 + upperBound: 1.0 # Lower threshold than Spark since Photon is faster and smaller speedups are valuable + - title: 'Small' + lowerBound: 1.0 + upperBound: 2.0 + - title: 'Medium' + lowerBound: 2.0 + upperBound: 3.0 + - title: 'Large' + lowerBound: 3.0 + upperBound: 1000000.0 + eligibilityConditions: + - columnName: 'Estimated GPU Speedup' + lowerBound: 1.0 + upperBound: 1000000.0 + - columnName: 'Unsupported Operators Stage Duration Percent' + lowerBound: 0.0 + upperBound: 25.0 additionalHeuristics: appInfo: fileName: 'application_information.csv' diff --git a/user_tools/src/spark_rapids_tools/exceptions.py b/user_tools/src/spark_rapids_tools/exceptions.py index d9acbb156..69ebd830c 100644 --- a/user_tools/src/spark_rapids_tools/exceptions.py +++ b/user_tools/src/spark_rapids_tools/exceptions.py @@ -1,4 +1,4 @@ -# Copyright (c) 2023, NVIDIA CORPORATION. +# Copyright (c) 2023-2024, NVIDIA CORPORATION. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -54,6 +54,10 @@ class CspPathAttributeError(CspPathException, ValueError): pass +class CspPathTypeMismatchError(CspPathException, ValueError): + pass + + class InvalidPropertiesSchema(CspPathException, ValueError): """ Defines a class to represent errors caused by invalid properties schema diff --git a/user_tools/src/spark_rapids_tools/storagelib/cspfs.py b/user_tools/src/spark_rapids_tools/storagelib/cspfs.py index 6c00bfaf3..3f2956e85 100644 --- a/user_tools/src/spark_rapids_tools/storagelib/cspfs.py +++ b/user_tools/src/spark_rapids_tools/storagelib/cspfs.py @@ -16,14 +16,15 @@ import abc import os -from typing import Generic, Callable, TypeVar, Any, Union +from typing import Generic, Callable, TypeVar, Any, Union, List, Optional from pyarrow import fs as arrow_fs +from pyarrow.fs import FileType from .csppath import CspPathImplementation, CspPath, path_impl_registry from ..exceptions import ( - CspPathNotFoundException + CspPathNotFoundException, CspPathTypeMismatchError ) BoundedCspPath = TypeVar('BoundedCspPath', bound=CspPath) @@ -151,3 +152,32 @@ def copy_resources(cls, src: BoundedCspPath, dest: BoundedCspPath): destination_filesystem=dest.fs_obj.fs, # 64 MB chunk size chunk_size=64 * 1024 * 1024) + + @classmethod + def list_all_files(cls, path: BoundedCspPath) -> List[BoundedCspPath]: + return cls._list_items_by_type(path, FileType.File) + + @classmethod + def list_all_dirs(cls, path: BoundedCspPath) -> List[BoundedCspPath]: + return cls._list_items_by_type(path, FileType.Directory) + + @classmethod + def list_all(cls, path: BoundedCspPath) -> List[BoundedCspPath]: + return cls._list_items_by_type(path, None) + + @staticmethod + def _list_items_by_type(path: BoundedCspPath, item_type: Optional[FileType]) -> List[BoundedCspPath]: + """ + Helper function to list files, directories, or all items in the given path. + """ + if not path.exists(): + raise CspPathNotFoundException(f'Path does not exist: {path}') + if not path.is_dir(): + raise CspPathTypeMismatchError(f'Path is not a directory: {path}') + + dir_info_list = path.fs_obj.get_file_info(arrow_fs.FileSelector(path.no_scheme, recursive=False)) + return [ + path.create_sub_path(dir_info.base_name) + for dir_info in dir_info_list + if item_type is None or dir_info.type == item_type + ] diff --git a/user_tools/src/spark_rapids_tools/tools/speedup_category.py b/user_tools/src/spark_rapids_tools/tools/speedup_category.py index 15d9b8790..4065a28ec 100644 --- a/user_tools/src/spark_rapids_tools/tools/speedup_category.py +++ b/user_tools/src/spark_rapids_tools/tools/speedup_category.py @@ -15,19 +15,44 @@ """Implementation class for Speedup Category logic.""" from dataclasses import dataclass, field -from typing import Optional +from typing import Optional, Dict import pandas as pd +class SpeedupStrategy: + """ + Wrapper class for speedup strategy properties. + """ + _categories: list + _eligibility_conditions: list + + def __init__(self, props: dict): + self._categories = props.get('categories', []) + self._eligibility_conditions = props.get('eligibilityConditions', []) + + def get_categories(self) -> list: + return self._categories + + def get_eligibility_conditions(self) -> list: + return self._eligibility_conditions + + @dataclass class SpeedupCategory: """ Encapsulates the logic to categorize the speedup values based on the range values. """ props: dict = field(default=None, init=True) + speedup_strategies: Dict[str, SpeedupStrategy] = field(default_factory=dict, init=False) + + def __post_init__(self): + strategy_properties = self.props.get('strategies', {}) + # Create a SpeedupStrategy for each runtime type. + for spark_runtime, properties in strategy_properties.items(): # type: str, dict + self.speedup_strategies[spark_runtime] = SpeedupStrategy(properties) - def __build_category_column(self, all_apps: pd.DataFrame) -> pd.DataFrame: + def _build_category_column(self, all_apps: pd.DataFrame) -> pd.DataFrame: """ Build the category column based on the range values of the speedup column. Example: @@ -44,20 +69,24 @@ def __build_category_column(self, all_apps: pd.DataFrame) -> pd.DataFrame: output: row_2 = pd.Series({'speedup': 3.5, 'speedup category': 'Large'}) reason: Speedup Category will be 'Large' because the speedup is within the range (3-100000). """ - categories = self.props.get('categories') category_col_name = self.props.get('categoryColumnName') speedup_col_name = self.props.get('speedupColumnName') + spark_runtime_col_name = self.props.get('sparkRuntimeColumnName') # Calculate the category based on the speedup value - def calculate_category(col_value) -> Optional[str]: + def calculate_category(single_row: pd.Series) -> Optional[str]: + spark_runtime = single_row.get(spark_runtime_col_name).lower() + # Get the speedup strategy and its categories for the given runtime type. + categories = self.speedup_strategies.get(spark_runtime).get_categories() + col_value = single_row.get(speedup_col_name) for category in categories: if category.get('lowerBound') <= col_value < category.get('upperBound'): return category.get('title') return None - all_apps[category_col_name] = all_apps[speedup_col_name].apply(calculate_category) + all_apps[category_col_name] = all_apps.apply(calculate_category, axis=1) return all_apps - def __process_category(self, all_apps: pd.DataFrame) -> pd.DataFrame: + def _process_category(self, all_apps: pd.DataFrame) -> pd.DataFrame: """ Process the speedup category column based on the eligibility criteria. If the row does not match the criteria, the category column will be set to the `Not Recommended` category. @@ -76,9 +105,13 @@ def __process_category(self, all_apps: pd.DataFrame) -> pd.DataFrame: """ category_col_name = self.props.get('categoryColumnName') heuristics_col_name = self.props.get('heuristicsColumnName') + spark_runtime_col_name = self.props.get('sparkRuntimeColumnName') def process_row(single_row: pd.Series) -> str: - for entry in self.props.get('eligibilityConditions'): + spark_runtime = single_row.get(spark_runtime_col_name).lower() + # Get the speedup strategy and its eligibility conditions for the given runtime type. + eligibility_conditions = self.speedup_strategies.get(spark_runtime).get_eligibility_conditions() + for entry in eligibility_conditions: col_value = single_row[entry.get('columnName')] # If the row is marked to be skipped by heuristics or the value is not within the range, # set the category to default category (Not Recommended) @@ -91,6 +124,6 @@ def process_row(single_row: pd.Series) -> str: return all_apps def build_category_column(self, all_apps: pd.DataFrame) -> pd.DataFrame: - apps_with_category = self.__build_category_column(all_apps) - processed_apps = self.__process_category(apps_with_category) + apps_with_category = self._build_category_column(all_apps) + processed_apps = self._process_category(apps_with_category) return processed_apps From 049bccaf812f08dad9b838e83d77ae775922db52 Mon Sep 17 00:00:00 2001 From: spark-rapids automation <70000568+nvauto@users.noreply.github.com> Date: Fri, 15 Nov 2024 02:36:41 +0000 Subject: [PATCH 05/22] Update dev-version by jenkins-spark-rapids-tools-auto-release-94 Signed-off-by: spark-rapids automation <70000568+nvauto@users.noreply.github.com> --- core/pom.xml | 2 +- user_tools/src/spark_rapids_pytools/__init__.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/core/pom.xml b/core/pom.xml index 0ed3bb03e..fd9057ddf 100644 --- a/core/pom.xml +++ b/core/pom.xml @@ -23,7 +23,7 @@ rapids-4-spark-tools_2.12 RAPIDS Accelerator for Apache Spark tools RAPIDS Accelerator for Apache Spark tools - 24.10.1-SNAPSHOT + 24.10.2-SNAPSHOT jar http://github.com/NVIDIA/spark-rapids-tools diff --git a/user_tools/src/spark_rapids_pytools/__init__.py b/user_tools/src/spark_rapids_pytools/__init__.py index 0eb645c56..84452ec1c 100644 --- a/user_tools/src/spark_rapids_pytools/__init__.py +++ b/user_tools/src/spark_rapids_pytools/__init__.py @@ -16,7 +16,7 @@ from spark_rapids_pytools.build import get_version, get_spark_dep_version -VERSION = '24.10.1' +VERSION = '24.10.2' # defines the default runtime build version for the user tools environment SPARK_DEP_VERSION = '350' __version__ = get_version(VERSION) From 16195abf2abffbfb64c61cccd912c762dcb4bfe6 Mon Sep 17 00:00:00 2001 From: Ahmed Hussein <50450311+amahussein@users.noreply.github.com> Date: Fri, 15 Nov 2024 14:07:10 -0600 Subject: [PATCH 06/22] Remove custom-speedup module from user-tools (#1425) Signed-off-by: Ahmed Hussein (amahussein) Contributes to #1221 This PR remove the python scripts that used to generate custom speedup factors. The scripts are dead since the tools migrated to XGBoost estimates. --- user_tools/custom_speedup_factors/README.md | 56 ---- .../custom_speedup_factors/defaultScores.csv | 19 -- .../generate_speedup_factors.py | 225 ---------------- .../custom_speedup_factors/operatorsList.csv | 254 ------------------ .../validate_qualification_estimates.py | 156 ----------- 5 files changed, 710 deletions(-) delete mode 100644 user_tools/custom_speedup_factors/README.md delete mode 100644 user_tools/custom_speedup_factors/defaultScores.csv delete mode 100644 user_tools/custom_speedup_factors/generate_speedup_factors.py delete mode 100644 user_tools/custom_speedup_factors/operatorsList.csv delete mode 100644 user_tools/custom_speedup_factors/validate_qualification_estimates.py diff --git a/user_tools/custom_speedup_factors/README.md b/user_tools/custom_speedup_factors/README.md deleted file mode 100644 index 2bcdc9466..000000000 --- a/user_tools/custom_speedup_factors/README.md +++ /dev/null @@ -1,56 +0,0 @@ -# Custom Speedup Factors for Workload Qualification - -## Purpose - -Speedup factor estimation for the qualification tool is used for determining the estimated runtime for an application on GPU using Spark RAPIDS. The speedup factors generate multipliers at an exec (and potentially expression) level that are used in the qualification tool for GPU estimates. - -## Prerequisites - -1. python >= 3.8 -2. Necessary Python dependencies: `pandas`, `argparse`, `spark-rapids-user-tools` - -## Generating Custom Speedup Factors - -The high-level process to generate speedup factors for an environment is as follows: - -1. Event log generation - 1. Run the NDS benchmark on CPU cluster along with any other representative jobs and save event log(s). Follow steps documented in the [NDS README](https://github.com/NVIDIA/spark-rapids-benchmarks/blob/dev/nds/README.md) for running the Power Run. - 2. Run the NDS benchmark on GPU cluster along with any other representative jobs and save event log(s). Follow steps documented in the [NDS README](https://github.com/NVIDIA/spark-rapids-benchmarks/blob/dev/nds/README.md) for running the Power Run. - 3. Note that the benchmark data size (referred to as scale factor) should match the representative data size for your workloads. If your workloads are 1TB in size, then you should use SF1000. If your workloads are 500GB in size, then you should use SF500. -2. Job profiler analysis - 1. Run the Spark RAPIDS profiling tool against the CPU and GPU event log to get stage-level duration metrics. -``` -spark_rapids_user_tools onprem profiling --csv --eventlogs CPU-3k --local_folder CPU-3k-profile - -spark_rapids_user_tools onprem profiling --csv --eventlogs GPU-3k --local_folder GPU-3k-profile -``` -3. Speedup factor generation - 1. Run the speedup factor generation script, passing the CPU and GPU profiler output along with a CSV output filename. -``` -python generate_speedup_factors.py --cpu CPU-3k-profile/rapids_4_spark_profile --gpu GPU-3k-profile/rapids_4_spark_profile --output newScores.csv -``` - -The script will generate the new scores in the output specified by the `--output` argument. - -## Running Workload Qualification with Custom Speedup Factors - -Now that you have a custom *operatorsScore.csv* file, you can run the Spark RAPIDS qualification tool using it to get estimations applicable for your environment. Here is the command to run with a custom speedup factor file: -``` -spark_rapids_user_tools onprem qualification --speedup-factor-file newScores.csv --eventlogs -``` - -## Validating Custom Speedup Factors - -There is a utility script in the directory to allow for validation of custom speedup factors given CPU and GPU event logs for a corresponding job or set of jobs. By default, the script will generate custom speedup factors, run the qualification tool with the generated custom speed up factors, and then generate validation metrics for the estimations against the actuals. - -Example execution of the script: -``` -python validate_qualification_estimates.py --cpu_log CPU-nds-eventlog --gpu_log GPU-nds-eventlog --output test-speedup -``` - -The script also allows you to pass in a custom speedup factor file if you have previously generated them. Example: -``` -python validate_qualification_estimates.py --cpu_log CPU-nds-eventlog --gpu_log GPU-nds-eventlog --output test-speedup --speedups test-scores.csv -``` - -Other options include passing in the CPU and/or GPU profiler output if that has already been done via the `cpu_profile` and `gpu_profile` arguments. Additionally, you can pass in a custom tools jar via `--jar` if that is needed. diff --git a/user_tools/custom_speedup_factors/defaultScores.csv b/user_tools/custom_speedup_factors/defaultScores.csv deleted file mode 100644 index c57bc5aa9..000000000 --- a/user_tools/custom_speedup_factors/defaultScores.csv +++ /dev/null @@ -1,19 +0,0 @@ -CPUOperator,Score -AggregateInPandasExec,1.2 -ArrowEvalPythonExec,1.2 -FlatMapGroupsInPandasExec,1.2 -FlatMapCoGroupsInPandasExec,1.2 -MapInPandasExec,1.2 -WindowInPandasExec,1.2 -KMeans-pyspark,8.86 -KMeans-scala,1 -PCA-pyspark,2.24 -PCA-scala,2.69 -LinearRegression-pyspark,2 -LinearRegression-scala,1 -RandomForestClassifier-pyspark,6.31 -RandomForestClassifier-scala,1 -RandomForestRegressor-pyspark,3.66 -RandomForestRegressor-scala,1 -XGBoost-pyspark,1 -XGBoost-scala,3.31 diff --git a/user_tools/custom_speedup_factors/generate_speedup_factors.py b/user_tools/custom_speedup_factors/generate_speedup_factors.py deleted file mode 100644 index 7d09f142c..000000000 --- a/user_tools/custom_speedup_factors/generate_speedup_factors.py +++ /dev/null @@ -1,225 +0,0 @@ -#!/usr/bin/env python3 -# Copyright (c) 2023-2024, NVIDIA CORPORATION. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -"""Spark RAPIDS speedup factor generation script""" - -import argparse -import os - -import pandas as pd - - -def list_directories(root_name): - for root, dirs, files in os.walk(root_name): - return dirs - return [] - - -parser = argparse.ArgumentParser(description="Speedup Factor Analysis") -parser.add_argument("--cpu", type=str, help="Directory of CPU profiler logs", required=True) -parser.add_argument("--gpu", type=str, help="Directory of GPU profiler logs", required=True) -parser.add_argument("--output", type=str, help="Filename for custom speedup factors", required=True) -parser.add_argument("--verbose", action="store_true", help="flag to generate full verbose output for logging raw node results") -parser.add_argument("--chdir", action="store_true", help="flag to change to work dir that's the script located") -args = parser.parse_args() - -cpu_dir = args.cpu -gpu_dir = args.gpu -output = args.output -verbose = args.verbose - -cpu_stage_log = {} -gpu_stage_log = {} -cpu_duration = 0.0 -gpu_duration = 0.0 - -min_speedup = 1.0 - -if args.chdir: - # Change to work dir that's the script located - os.chdir(os.path.dirname(__file__)) - -# CPU log parsing -for app in list_directories(cpu_dir): - - # - figure out query from application_info.csv - app_info = pd.read_csv(cpu_dir + "/" + app + "/application_information.csv") - app_name = app_info.loc[0]["appName"] - cpu_duration = cpu_duration + app_info.loc[0]["duration"] - cpu_stage_log[app_name] = {} - - # - load wholestagecodegen_mapping.csv into a dictionary for lookups (CPU only) - mapping_info = pd.read_csv(cpu_dir + "/" + app + "/wholestagecodegen_mapping.csv") - mapping_info = mapping_info.groupby(['SQL Node'])['Child Node'].apply(','.join).reset_index() - - # - process sql_plan_metrics_for_application.csv - # - load in "duration" (CPU) - # - replace WholeStageCodegen (CPU only) with list of operators from mapping lookup file - # - mapping_info.parent = sql_times.nodeName - cpu_sql_info = pd.read_csv(cpu_dir + "/" + app + "/sql_plan_metrics_for_application.csv") - cpu_sql_times = cpu_sql_info[cpu_sql_info["name"] == "duration"] - cpu_sql_combined = cpu_sql_times.set_index('nodeName').join(mapping_info.set_index('SQL Node'), how='left') - - # - parse WholeStageCodegen durations with child node mapping - cpu_sql_times_df = cpu_sql_combined[['Child Node', 'total']] - - for index, row in cpu_sql_times_df.iterrows(): - operators = str(row['Child Node']).split(',') - duration = row['total']/len(operators)/1000.0 - for operator in operators: - if operator in cpu_stage_log[app_name]: - cpu_stage_log[app_name][operator] = cpu_stage_log[app_name][operator] + duration - else: - cpu_stage_log[app_name][operator] = duration - - # - parse top-level execs from sql_to_stage_information.csv - cpu_stage_info = pd.read_csv(cpu_dir + "/" + app + "/sql_to_stage_information.csv") - cpu_stage_times = cpu_stage_info[['Stage Duration', 'SQL Nodes(IDs)']] - cpu_stage_times_df = cpu_stage_times.dropna() - - for index, row in cpu_stage_times_df.iterrows(): - node_list = str(row['SQL Nodes(IDs)']) - operators = node_list.split(',') - duration = row['Stage Duration']/(len(operators)-node_list.count("WholeStageCodegen")) - - for operator in operators: - if "WholeStageCodegen" in operator: - continue - - op_key = operator.split('(')[0] - if op_key in cpu_stage_log[app_name]: - cpu_stage_log[app_name][op_key] = cpu_stage_log[app_name][op_key] + duration - else: - cpu_stage_log[app_name][op_key] = duration - -# GPU log parsing -for app in list_directories(gpu_dir): - - # - figure out query from application_info.csv - app_info = pd.read_csv(gpu_dir + "/" + app + "/application_information.csv") - app_name = app_info.loc[0]["appName"] - gpu_duration = gpu_duration + app_info.loc[0]["duration"] - gpu_stage_log[app_name] = {} - - # - process sql_to_stage_information.csv to get stage durations - # - split up duration by operators listed in each stage - gpu_stage_info = pd.read_csv(gpu_dir + "/" + app + "/sql_to_stage_information.csv") - gpu_stage_times = gpu_stage_info[['Stage Duration', 'SQL Nodes(IDs)']] - - for index, row in gpu_stage_times.iterrows(): - operators = str(row['SQL Nodes(IDs)']).split(',') - duration = row['Stage Duration']/len(operators) - for operator in operators: - op_key = operator.split('(')[0] - if op_key in gpu_stage_log[app_name]: - gpu_stage_log[app_name][op_key] = gpu_stage_log[app_name][op_key] + duration - else: - gpu_stage_log[app_name][op_key] = duration - -cpu_stage_totals = {} -gpu_stage_totals = {} -cpu_stage_total = 0.0 -gpu_stage_total = 0.0 - -# Sum up SQL operators for each operator found in CPU and GPU -for app_key in cpu_stage_log: - for op_key in cpu_stage_log[app_key]: - if op_key not in cpu_stage_totals: - cpu_stage_totals[op_key] = cpu_stage_log[app_key][op_key] - else: - cpu_stage_totals[op_key] = cpu_stage_totals[op_key] + cpu_stage_log[app_key][op_key] - cpu_stage_total = cpu_stage_total + cpu_stage_log[app_key][op_key] - -for app_key in gpu_stage_log: - for op_key in gpu_stage_log[app_key]: - if op_key not in gpu_stage_totals: - gpu_stage_totals[op_key] = gpu_stage_log[app_key][op_key] - else: - gpu_stage_totals[op_key] = gpu_stage_totals[op_key] + gpu_stage_log[app_key][op_key] - gpu_stage_total = gpu_stage_total + gpu_stage_log[app_key][op_key] - -# Create dictionary of execs where speedup factors can be calculated -scores_dict = {} - -# Scan operators -if 'Scan parquet ' in cpu_stage_totals and 'GpuScan parquet ' in gpu_stage_totals: - scores_dict["BatchScanExec"] = str(round(cpu_stage_totals['Scan parquet '] / gpu_stage_totals['GpuScan parquet '], 2)) - scores_dict["FileSourceScanExec"] = str(round(cpu_stage_totals['Scan parquet '] / gpu_stage_totals['GpuScan parquet '], 2)) -if 'Scan orc ' in cpu_stage_totals and 'GpuScan orc ' in gpu_stage_totals: - scores_dict["BatchScanExec"] = str(round(cpu_stage_totals['Scan orc '] / gpu_stage_totals['GpuScan orc '], 2)) - scores_dict["FileSourceScanExec"] = str(round(cpu_stage_totals['Scan orc '] / gpu_stage_totals['GpuScan orc '], 2)) - -# Other operators -if 'Expand' in cpu_stage_totals and 'GpuExpand' in gpu_stage_totals: - scores_dict["ExpandExec"] = str(round(cpu_stage_totals['Expand'] / gpu_stage_totals['GpuExpand'], 2)) -if 'CartesianProduct' in cpu_stage_totals and 'GpuCartesianProduct' in gpu_stage_totals: - scores_dict["CartesianProductExec"] = str(round(cpu_stage_totals['CartesianProduct'] / gpu_stage_totals['GpuCartesianProduct'], 2)) -if 'Filter' in cpu_stage_totals and 'GpuFilter' in gpu_stage_totals: - scores_dict["FilterExec"] = str(round(cpu_stage_totals['Filter'] / gpu_stage_totals['GpuFilter'], 2)) -if 'SortMergeJoin' in cpu_stage_totals and 'GpuShuffledHashJoin' in gpu_stage_totals: - scores_dict["SortMergeJoinExec"] = str(round(cpu_stage_totals['SortMergeJoin'] / gpu_stage_totals['GpuShuffledHashJoin'], 2)) -if 'BroadcastHashJoin' in cpu_stage_totals and 'GpuBroadcastHashJoin' in gpu_stage_totals: - scores_dict["BroadcastHashJoinExec"] = str(round(cpu_stage_totals['BroadcastHashJoin'] / gpu_stage_totals['GpuBroadcastHashJoin'], 2)) -if 'Exchange' in cpu_stage_totals and 'GpuColumnarExchange' in gpu_stage_totals: - scores_dict["ShuffleExchangeExec"] = str(round(cpu_stage_totals['Exchange'] / gpu_stage_totals['GpuColumnarExchange'], 2)) -if 'HashAggregate' in cpu_stage_totals and 'GpuHashAggregate' in gpu_stage_totals: - scores_dict["HashAggregateExec"] = str(round(cpu_stage_totals['HashAggregate'] / gpu_stage_totals['GpuHashAggregate'], 2)) - scores_dict["ObjectHashAggregateExec"] = str(round(cpu_stage_totals['HashAggregate'] / gpu_stage_totals['GpuHashAggregate'], 2)) - scores_dict["SortAggregateExec"] = str(round(cpu_stage_totals['HashAggregate'] / gpu_stage_totals['GpuHashAggregate'], 2)) -if 'TakeOrderedAndProject' in cpu_stage_totals and 'GpuTopN' in gpu_stage_totals: - scores_dict["TakeOrderedAndProjectExec"] = str(round(cpu_stage_totals['TakeOrderedAndProject'] / gpu_stage_totals['GpuTopN'], 2)) -if 'BroadcastNestedLoopJoin' in cpu_stage_totals and 'GpuBroadcastNestedLoopJoin' in gpu_stage_totals: - scores_dict["BroadcastNestedLoopJoinExec"] = str(round(cpu_stage_totals['BroadcastNestedLoopJoin'] / gpu_stage_totals['GpuBroadcastNestedLoopJoin'], 2)) - -# Set minimum to 1.0 for speedup factors -for key in scores_dict: - if float(scores_dict[key]) < min_speedup: - scores_dict[key] = f"{min_speedup}" - -# Set overall speedup for default value for execs not in logs -overall_speedup = str(max(min_speedup, round(cpu_duration/gpu_duration, 2))) - -# Print out node metrics (if verbose) -if verbose: - print("# CPU Operator Metrics") - for key in cpu_stage_totals: - print(key + " = " + str(cpu_stage_totals[key])) - print("# GPU Operator Metrics") - for key in gpu_stage_totals: - print(key + " = " + str(gpu_stage_totals[key])) - print("# Summary Metrics") - print("CPU Total = " + str(cpu_stage_total)) - print("GPU Total = " + str(gpu_stage_total)) - print("Overall speedup = " + overall_speedup) - - # Print out individual exec speedup factors - print("# Speedup Factors ") - for key in scores_dict: - print(f"{key} = {scores_dict[key]}") - -# Load in list of operators and set initial values to default speedup -scores_df = pd.read_csv("operatorsList.csv") -scores_df["Score"] = overall_speedup - -# Update operators that are found in benchmark -for key in scores_dict: - scores_df.loc[scores_df['CPUOperator'] == key, 'Score'] = scores_dict[key] - -# Add in hard-coded defaults -defaults_df = pd.read_csv("defaultScores.csv") - -# Generate output CSV file -final_df = pd.concat([scores_df, defaults_df]) -final_df.to_csv(output, index=False) diff --git a/user_tools/custom_speedup_factors/operatorsList.csv b/user_tools/custom_speedup_factors/operatorsList.csv deleted file mode 100644 index 986b88ed7..000000000 --- a/user_tools/custom_speedup_factors/operatorsList.csv +++ /dev/null @@ -1,254 +0,0 @@ -CPUOperator -CoalesceExec -CollectLimitExec -ExpandExec -FileSourceScanExec -FilterExec -GenerateExec -GlobalLimitExec -LocalLimitExec -ProjectExec -RangeExec -SampleExec -SortExec -TakeOrderedAndProjectExec -HashAggregateExec -ObjectHashAggregateExec -SortAggregateExec -DataWritingCommandExec -ExecutedCommandExec -BatchScanExec -ShuffleExchangeExec -BroadcastHashJoinExec -BroadcastNestedLoopJoinExec -CartesianProductExec -ShuffledHashJoinExec -SortMergeJoinExec -WindowExec -Abs -Acos -Acosh -Add -AggregateExpression -Alias -And -ApproximatePercentile -ArrayContains -ArrayExcept -ArrayExists -ArrayIntersect -ArrayMax -ArrayMin -ArrayRemove -ArrayRepeat -ArrayTransform -ArrayUnion -ArraysOverlap -ArraysZip -Asin -Asinh -AtLeastNNonNulls -Atan -Atanh -AttributeReference -Average -BRound -BitLength -BitwiseAnd -BitwiseNot -BitwiseOr -BitwiseXor -CaseWhen -Cbrt -Ceil -CheckOverflow -Coalesce -CollectList -CollectSet -Concat -ConcatWs -Contains -Conv -Cos -Cosh -Cot -Count -CreateArray -CreateMap -CreateNamedStruct -CurrentRow$ -DateAdd -DateAddInterval -DateDiff -DateFormatClass -DateSub -DayOfMonth -DayOfWeek -DayOfYear -DenseRank -Divide -DynamicPruningExpression -ElementAt -EndsWith -EqualNullSafe -EqualTo -Exp -Explode -Expm1 -First -Flatten -Floor -FormatNumber -FromUTCTimestamp -FromUnixTime -GetArrayItem -GetArrayStructFields -GetJsonObject -GetMapValue -GetStructField -GetTimestamp -GreaterThan -GreaterThanOrEqual -Greatest -HiveGenericUDF -HiveSimpleUDF -Hour -Hypot -If -In -InSet -InitCap -InputFileBlockLength -InputFileBlockStart -InputFileName -IntegralDivide -IsNaN -IsNotNull -IsNull -JsonToStructs -JsonTuple -KnownFloatingPointNormalized -KnownNotNull -Lag -LambdaFunction -Last -LastDay -Lead -Least -Length -LessThan -LessThanOrEqual -Like -Literal -Log -Log10 -Log1p -Log2 -Logarithm -Lower -MakeDecimal -MapConcat -MapEntries -MapFilter -MapKeys -MapValues -Max -Md5 -MicrosToTimestamp -MillisToTimestamp -Min -Minute -MonotonicallyIncreasingID -Month -Multiply -Murmur3Hash -NaNvl -NamedLambdaVariable -NormalizeNaNAndZero -Not -NthValue -OctetLength -Or -Percentile -PercentRank -PivotFirst -Pmod -PosExplode -Pow -PreciseTimestampConversion -PromotePrecision -PythonUDF -Quarter -RLike -RaiseError -Rand -Rank -RegExpExtract -RegExpExtractAll -RegExpReplace -Remainder -ReplicateRows -Reverse -Rint -Round -RowNumber -ScalaUDF -ScalarSubquery -Second -SecondsToTimestamp -Sequence -ShiftLeft -ShiftRight -ShiftRightUnsigned -Signum -Sin -Sinh -Size -SortArray -SortOrder -SparkPartitionID -SpecifiedWindowFrame -Sqrt -Stack -StartsWith -StddevPop -StddevSamp -StringInstr -StringLPad -StringLocate -StringRPad -StringRepeat -StringReplace -StringSplit -StringToMap -StringTranslate -StringTrim -StringTrimLeft -StringTrimRight -StructsToJson -Substring -SubstringIndex -Subtract -Sum -Tan -Tanh -TimeAdd -ToDegrees -ToRadians -ToUnixTimestamp -TransformKeys -TransformValues -UnaryMinus -UnaryPositive -UnboundedFollowing$ -UnboundedPreceding$ -UnixTimestamp -UnscaledValue -Upper -VariancePop -VarianceSamp -WeekDay -WindowExpression -WindowSpecDefinition -XxHash64 -Year diff --git a/user_tools/custom_speedup_factors/validate_qualification_estimates.py b/user_tools/custom_speedup_factors/validate_qualification_estimates.py deleted file mode 100644 index 26e6b8ae2..000000000 --- a/user_tools/custom_speedup_factors/validate_qualification_estimates.py +++ /dev/null @@ -1,156 +0,0 @@ -#!/usr/bin/env python3 -# Copyright (c) 2023, NVIDIA CORPORATION. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -"""Spark RAPIDS speedup factor validation script""" - -import argparse -import os -import glob -import subprocess - -import pandas as pd -from tabulate import tabulate - -parser = argparse.ArgumentParser(description="Speedup Factor Validation") -parser.add_argument("--cpu_log", type=str, help="Directory of CPU event log(s)", required=True) -parser.add_argument("--gpu_log", type=str, help="Directory of GPU event log(s)", required=True) -parser.add_argument("--output", type=str, help="Output folder for storing logs", required=True) -parser.add_argument("--speedups", type=str, help="Custom speedup factor file") -parser.add_argument("--cpu_profile", type=str, help="Directory of CPU profiler log(s)") -parser.add_argument("--gpu_profile", type=str, help="Directory of GPU profiler log(s)") -parser.add_argument("--jar", type=str, help="Custom tools jar") -parser.add_argument("--verbose", action="store_true", help="flag to generate full verbose output for logging raw node results") -args = parser.parse_args() - -cpu_log = args.cpu_log -gpu_log = args.gpu_log -cpu_profile = args.cpu_profile -gpu_profile = args.gpu_profile -output = args.output -speedups = args.speedups -jar = args.jar -verbose = args.verbose - -print(f"Output folder = {output}") -print(f"CPU event log = {cpu_log}") -print(f"GPU event log = {gpu_log}") - -subprocess.run(f"rm -rf {output}", shell=True) - -speedups_arg = "" -if speedups is not None: - speedups_arg = f"--speedup-factor-file {speedups}" -else: - speedups_arg = f"--speedup-factor-file {output}/generatedScores.csv" - -jar_arg = "" -if jar is not None: - jar_arg = f"--tools_jar {jar}" - -# Generate speedup factors - -### run GPU profiler if needed -gpu_profile_dir = "" -if gpu_profile is not None: - gpu_profile_dir = gpu_profile -else: - gpu_profile_dir = f"{output}/gpu_profile" - subprocess.run(f"spark_rapids_user_tools onprem profiling --csv {jar_arg} --local_folder {gpu_profile_dir} --eventlogs {gpu_log}", shell=True) - -if speedups is None: - ### run CPU profiler if needed - cpu_profile_dir = "" - if cpu_profile is not None: - cpu_profile_dir = cpu_profile - else: - cpu_profile_dir = f"{output}/cpu_profile" - subprocess.run(f"spark_rapids_user_tools onprem profiling --csv {jar_arg} --local_folder {cpu_profile_dir} --eventlogs {cpu_log}", shell=True) - - ### run speedup factor generation - subprocess.run(f"python generate_speedup_factors.py --cpu {cpu_profile_dir}/*/rapids_4_spark_profile --gpu {gpu_profile_dir}/*/rapids_4_spark_profile --output {output}/generatedScores.csv", shell=True) - -# Run qualification - -### set speedup factors to input or generated -speedups_arg = "" -if speedups is not None: - speedups_arg = f"--speedup-factor-file {speedups}" -else: - speedups_arg = f"--speedup-factor-file {output}/generatedScores.csv" - -### run CPU qualification -cpu_tmp_dir = f"{output}/cpu" -subprocess.run(f"spark_rapids_user_tools onprem qualification {speedups_arg} {jar_arg} --local_folder {cpu_tmp_dir} --eventlogs {cpu_log}", shell=True) - -# Parse and validate results - -### CPU log parsing -cpu_app_info = pd.read_csv(glob.glob(f"{cpu_tmp_dir}/*/rapids_4_spark_qualification_output/rapids_4_spark_qualification_output.csv")[0]) -cpu_query_info = cpu_app_info[["App Name", "App Duration", "Estimated GPU Duration", "Estimated GPU Speedup"]] - -### GPU log parsing -gpu_query_info = pd.DataFrame(columns = ['App Name', 'GPU Duration']) -counter = 0 - -for app in glob.glob(f"{gpu_profile_dir}/*/rapids_4_spark_profile/*/application_information.csv"): - app_info = pd.read_csv(app) - new_row = pd.DataFrame({'App Name': app_info.loc[0]["appName"], 'GPU Duration': app_info.loc[0]["duration"]}, index=[counter]) - gpu_query_info = pd.concat([gpu_query_info, new_row]) - counter = counter+1 - -merged_info = cpu_query_info.merge(gpu_query_info, left_on='App Name', right_on='App Name') -merged_info["Duration Error (sec)"] = (merged_info["Estimated GPU Duration"] - merged_info["GPU Duration"])/1000.0 -merged_info["Duration Error (pct)"] = (100.0*(merged_info["Estimated GPU Duration"] - merged_info["GPU Duration"])/merged_info["Estimated GPU Duration"]).apply(lambda x: round(x,2)) -merged_info["GPU Speedup"] = (merged_info["App Duration"]/merged_info["GPU Duration"]).apply(lambda x: round(x,2)) -merged_info["Speedup Error (abs)"] = merged_info["Estimated GPU Speedup"] - merged_info["GPU Speedup"] -merged_info["Speedup Error (pct)"] = (100.0*(merged_info["Estimated GPU Speedup"] - merged_info["GPU Speedup"])/merged_info["Estimated GPU Speedup"]).apply(lambda x: round(x,2)) - -print("==================================================") -print(" Application Details") -print("==================================================") -print(tabulate(merged_info, headers='keys', tablefmt='psql')) - -print("==================================================") -print(" Duration Error Metrics ") -print("==================================================") -print("Average duration error (seconds) = " + str(round(merged_info["Duration Error (sec)"].mean(),2))) -print("Median duration error (seconds) = " + str(round(merged_info["Duration Error (sec)"].median(),2))) -print("Min duration error (seconds) = " + str(round(merged_info["Duration Error (sec)"].min(),2))) -print("Max duration error (seconds) = " + str(round(merged_info["Duration Error (sec)"].max(),2))) -print("Average duration error (diff pct) = " + str(round(merged_info["Duration Error (pct)"].mean(),2))) -print("Median duration error (diff pct) = " + str(round(merged_info["Duration Error (pct)"].median(),2))) -print("Max duration error (diff pct) = " + str(round(merged_info["Duration Error (pct)"].max(),2))) -print("Average duration error (diff sec) = " + str(round(merged_info["Duration Error (sec)"].abs().mean(),2))) -print("Median duration error (diff sec) = " + str(round(merged_info["Duration Error (sec)"].abs().median(),2))) -print("Max duration error (diff sec) = " + str(round(merged_info["Duration Error (sec)"].abs().max(),2))) -print("Average duration error (abs pct) = " + str(round(merged_info["Duration Error (pct)"].abs().mean(),2))) -print("Median duration error (abs pct) = " + str(round(merged_info["Duration Error (pct)"].abs().median(),2))) -print("Max duration error (abs pct) = " + str(round(merged_info["Duration Error (pct)"].abs().max(),2))) -print("==================================================") -print(" Speedup Error Metrics ") -print("==================================================") -print("Average speedup error (diff) = " + str(round(merged_info["Speedup Error (abs)"].mean(),2))) -print("Median speedup error (diff) = " + str(round(merged_info["Speedup Error (abs)"].median(),2))) -print("Min speedup error (diff) = " + str(round(merged_info["Speedup Error (abs)"].min(),2))) -print("Max speedup error (diff) = " + str(round(merged_info["Speedup Error (abs)"].max(),2))) -print("Average speedup error (diff pct) = " + str(round(merged_info["Speedup Error (pct)"].mean(),2))) -print("Median speedup error (diff pct = " + str(round(merged_info["Speedup Error (pct)"].median(),2))) -print("Max speedup error (diff pct) = " + str(round(merged_info["Speedup Error (pct)"].max(),2))) -print("Average speedup error (abs diff) = " + str(round(merged_info["Speedup Error (abs)"].abs().mean(),2))) -print("Median speedup error (abs diff) = " + str(round(merged_info["Speedup Error (abs)"].abs().median(),2))) -print("Max speedup error (abs diff) = " + str(round(merged_info["Speedup Error (abs)"].abs().max(),2))) -print("Average speedup error (abs pct) = " + str(round(merged_info["Speedup Error (pct)"].abs().mean(),2))) -print("Median speedup error (abs pct) = " + str(round(merged_info["Speedup Error (pct)"].abs().median(),2))) -print("Max speedup error (abs pct) = " + str(round(merged_info["Speedup Error (pct)"].abs().max(),2))) From 197d7ebadd054f38e3bdc0f6a939eacc0bb4dbe8 Mon Sep 17 00:00:00 2001 From: Ahmed Hussein <50450311+amahussein@users.noreply.github.com> Date: Fri, 15 Nov 2024 15:31:01 -0600 Subject: [PATCH 07/22] Trigger GC at the beginning of each benchmark iteration (#1424) Signed-off-by: Ahmed Hussein (amahussein) Contributes to #1423 Trigger a GC at the beginning of each benchmark iteration --- .../org/apache/spark/rapids/tool/benchmarks/Benchmark.scala | 1 + 1 file changed, 1 insertion(+) diff --git a/core/src/main/scala/org/apache/spark/rapids/tool/benchmarks/Benchmark.scala b/core/src/main/scala/org/apache/spark/rapids/tool/benchmarks/Benchmark.scala index a09f121ad..45ad3bdd4 100644 --- a/core/src/main/scala/org/apache/spark/rapids/tool/benchmarks/Benchmark.scala +++ b/core/src/main/scala/org/apache/spark/rapids/tool/benchmarks/Benchmark.scala @@ -104,6 +104,7 @@ class Benchmark( val gcTimes = ArrayBuffer[Long]() //For tracking maximum GC over iterations for (i <- 0 until minIters) { + System.gc() // ensures GC for a consistent state across different iterations val timer = new ToolsTimer(i) val memoryTracker = new MemoryMetricsTracker f(timer) From 6af4bdbea950eddf1da857137598b31e092f31c9 Mon Sep 17 00:00:00 2001 From: Lee Yang Date: Fri, 15 Nov 2024 13:51:05 -0800 Subject: [PATCH 08/22] Add qualx model for databricks-azure_photon and update combined model (#1427) Signed-off-by: Lee Yang --- .../qualx/models/xgboost/combined.cfg | 2 +- .../qualx/models/xgboost/combined.json | 2 +- .../qualx/models/xgboost/combined.metrics | 206 +++++++++--------- .../xgboost/databricks-azure_photon.cfg | 1 + .../xgboost/databricks-azure_photon.json | 1 + .../xgboost/databricks-azure_photon.metrics | 109 +++++++++ 6 files changed, 216 insertions(+), 105 deletions(-) create mode 100644 user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure_photon.cfg create mode 100644 user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure_photon.json create mode 100644 user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure_photon.metrics diff --git a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.cfg b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.cfg index a71e4ac88..9e52614e1 100644 --- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.cfg +++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.cfg @@ -1 +1 @@ -{"learner":{"generic_param":{"device":"cpu","fail_on_invalid_gpu_id":"0","n_jobs":"0","nthread":"0","random_state":"0","seed":"0","seed_per_iteration":"0","validate_parameters":"1"},"gradient_booster":{"gbtree_model_param":{"num_parallel_tree":"1","num_trees":"95"},"gbtree_train_param":{"process_type":"default","tree_method":"auto","updater":"grow_quantile_histmaker","updater_seq":"grow_quantile_histmaker"},"name":"gbtree","specified_updater":false,"tree_train_param":{"alpha":"0","cache_opt":"1","colsample_bylevel":"1","colsample_bynode":"1","colsample_bytree":"1","eta":"0.0461824611","gamma":"0.00909571908","grow_policy":"depthwise","interaction_constraints":"","lambda":"1","learning_rate":"0.0461824611","max_bin":"256","max_cat_threshold":"64","max_cat_to_onehot":"4","max_delta_step":"0","max_depth":"7","max_leaves":"0","min_child_weight":"5","min_split_loss":"0.00909571908","monotone_constraints":"()","refresh_leaf":"1","reg_alpha":"0","reg_lambda":"1","sampling_method":"uniform","sketch_ratio":"2","sparse_threshold":"0.20000000000000001","subsample":"0.678620815"},"updater":[{"hist_train_param":{"debug_synchronize":"0","max_cached_hist_node":"65536"},"name":"grow_quantile_histmaker"}]},"learner_model_param":{"base_score":"6.0162324E-1","boost_from_average":"1","num_class":"0","num_feature":"108","num_target":"1"},"learner_train_param":{"booster":"gbtree","disable_default_eval_metric":"0","multi_strategy":"one_output_per_tree","objective":"reg:squarederror"},"metrics":[{"name":"mae"},{"name":"mape"}],"objective":{"name":"reg:squarederror","reg_loss_param":{"scale_pos_weight":"1"}}},"version":[2,0,3]} \ No newline at end of file +{"learner":{"generic_param":{"device":"cpu","fail_on_invalid_gpu_id":"0","n_jobs":"0","nthread":"0","random_state":"0","seed":"0","seed_per_iteration":"0","validate_parameters":"1"},"gradient_booster":{"gbtree_model_param":{"num_parallel_tree":"1","num_trees":"93"},"gbtree_train_param":{"process_type":"default","tree_method":"auto","updater":"grow_quantile_histmaker","updater_seq":"grow_quantile_histmaker"},"name":"gbtree","specified_updater":false,"tree_train_param":{"alpha":"0","cache_opt":"1","colsample_bylevel":"1","colsample_bynode":"1","colsample_bytree":"1","eta":"0.0499666668","gamma":"0.00690161297","grow_policy":"depthwise","interaction_constraints":"","lambda":"1","learning_rate":"0.0499666668","max_bin":"256","max_cat_threshold":"64","max_cat_to_onehot":"4","max_delta_step":"0","max_depth":"9","max_leaves":"0","min_child_weight":"4","min_split_loss":"0.00690161297","monotone_constraints":"()","refresh_leaf":"1","reg_alpha":"0","reg_lambda":"1","sampling_method":"uniform","sketch_ratio":"2","sparse_threshold":"0.20000000000000001","subsample":"0.768415093"},"updater":[{"hist_train_param":{"debug_synchronize":"0","max_cached_hist_node":"65536"},"name":"grow_quantile_histmaker"}]},"learner_model_param":{"base_score":"5.681664E-1","boost_from_average":"1","num_class":"0","num_feature":"108","num_target":"1"},"learner_train_param":{"booster":"gbtree","disable_default_eval_metric":"0","multi_strategy":"one_output_per_tree","objective":"reg:squarederror"},"metrics":[{"name":"mae"},{"name":"mape"}],"objective":{"name":"reg:squarederror","reg_loss_param":{"scale_pos_weight":"1"}}},"version":[2,0,3]} 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\ No newline at end of file diff --git a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.metrics b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.metrics index 48d813802..0c51ba152 100644 --- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.metrics +++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.metrics @@ -1,109 +1,109 @@ ,feature,shap_value,mean,std,min,25%,50%,75%,max -0,maxOnHeapMem,0.20945993,13322869089.941265,7488668175.285684,455501414.0,8974132838.0,10119177830.0,25581060096.0,26104509235.0 -1,executorCPUTime_mean,0.13217798,1634.153783487937,8748.589803157292,3.875,197.9729381443299,436.94290529695024,1135.2854603729604,227947.84615384616 -2,duration_max,0.1219628,20541.67078313253,137003.95576951889,15.0,968.25,2579.0,6378.75,3183955.0 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-10,sw_bytesWrittenRatio,0.028922884,0.7604902070964409,1.3003267564355534,0.0,0.004150472420326595,0.21370576377241818,1.157900579000657,18.780553045389944 -11,numExecutors,0.024495639,5.8987951807228916,3.213034389977632,1.0,1.0,8.0,8.0,14.0 -12,executorDeserializeCPUTime_mean,0.024004536,8.030784826809064,16.658939715849467,0.01225114854517611,1.4864407335921035,2.419585568383332,7.029241677804745,245.76923076923077 -13,resultSize_max,0.020455461,4190136.878012048,11408161.99505687,1785.0,15419.5,88018.0,2055176.25,263794922.0 -14,maxMem,0.018641975,20250091878.876205,12966667752.433016,455501414.0,10119177830.0,10119177830.0,26104509235.0,43359456460.0 -15,executorDeserializeTime_mean,0.01747867,19.705015574648073,45.748027926559544,0.04395604395604396,2.5203326403326405,4.653391453668846,10.778132235981074,475.6 -16,duration_min,0.016311068,56.37590361445783,119.50961727307138,0.0,11.0,17.0,40.0,1779.0 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+100,sqlOp_Project,0.0,1.0,0.0,1.0,1.0,1.0,1.0,1.0 +101,output_bytesWritten_mean,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +102,memoryBytesSpilled_mean,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +103,diskBytesSpilled_mean,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +104,sqlOp_HashAggregate,0.0,0.990909090909091,0.09512832433347063,0.0,1.0,1.0,1.0,1.0 +105,sqlOp_ObjectHashAggregate,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +106,sr_remoteBytesReadToDiskRatio,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +107,sqlOp_WindowSort,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 From 9cba9270544a1b330a713107c9cddd0072e01b8f Mon Sep 17 00:00:00 2001 From: Ahmed Hussein <50450311+amahussein@users.noreply.github.com> Date: Tue, 19 Nov 2024 16:34:26 -0600 Subject: [PATCH 09/22] Reduce the log noise caused by core report summary (#1426) Signed-off-by: Ahmed Hussein (amahussein) Contributes to #1416 This change set the log level of ToolTextFileWriter to debug and summarize the logging into a single message to show the final directory --- .../com/nvidia/spark/rapids/tool/ToolTextFileWriter.scala | 2 +- .../com/nvidia/spark/rapids/tool/profiling/Profiler.scala | 1 + .../spark/rapids/tool/qualification/Qualification.scala | 8 +------- .../spark/sql/rapids/tool/util/RuntimeReporter.scala | 3 +++ 4 files changed, 6 insertions(+), 8 deletions(-) diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/ToolTextFileWriter.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/ToolTextFileWriter.scala index 87701419a..a05f7c74a 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/ToolTextFileWriter.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/ToolTextFileWriter.scala @@ -70,7 +70,7 @@ class ToolTextFileWriter( // No need to close the outputStream. // Java should handle nested streams automatically. utf8Writer.foreach { writer => - logInfo(s"$finalLocationText output location: $textOutputLoc") + logDebug(s"$finalLocationText output location: $textOutputLoc") writer.flush() writer.close() } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/Profiler.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/Profiler.scala index bad5524e3..a69701c64 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/Profiler.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/Profiler.scala @@ -119,6 +119,7 @@ class Profiler(hadoopConf: Configuration, appArgs: ProfileArgs, enablePB: Boolea progressBar.foreach(_.finishAll()) // Write status reports for all event logs to a CSV file + logOutputPath() val reportResults = generateStatusResults(appStatusReporter.asScala.values.toSeq) ProfileOutputWriter.writeCSVTable("Profiling Status", reportResults, outputDir) } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/Qualification.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/Qualification.scala index 23d0defe7..c50464233 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/Qualification.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/Qualification.scala @@ -237,13 +237,6 @@ class Qualification(outputPath: String, numRows: Int, hadoopConf: Configuration, } } - /** - * The outputPath of the current instance of the provider - */ - def getReportOutputPath: String = { - s"$outputDir/rapids_4_spark_qualification_output" - } - /** * Generates a qualification report based on the provided summary information. */ @@ -263,6 +256,7 @@ class Qualification(outputPath: String, numRows: Int, hadoopConf: Configuration, qWriter.writeStageReport(allAppsSum, order) qWriter.writeUnsupportedOpsSummaryCSVReport(allAppsSum) val appStatusResult = generateStatusResults(appStatusReporter.asScala.values.toSeq) + logOutputPath() qWriter.writeStatusReport(appStatusResult, order) if (mlOpsEnabled) { if (allAppsSum.exists(x => x.mlFunctions.nonEmpty)) { diff --git a/core/src/main/scala/org/apache/spark/sql/rapids/tool/util/RuntimeReporter.scala b/core/src/main/scala/org/apache/spark/sql/rapids/tool/util/RuntimeReporter.scala index 57a8ad074..0ae7bfa6b 100644 --- a/core/src/main/scala/org/apache/spark/sql/rapids/tool/util/RuntimeReporter.scala +++ b/core/src/main/scala/org/apache/spark/sql/rapids/tool/util/RuntimeReporter.scala @@ -27,6 +27,9 @@ trait RuntimeReporter extends Logging { def generateRuntimeReport(hadoopConf: Option[Configuration] = None): Unit = { RuntimeUtil.generateReport(outputDir, hadoopConf) } + def logOutputPath(): Unit = { + logInfo(s"Tools output directory: $outputDir") + } /** * Updates the status of "SUCCESS" applications to "SKIPPED" if newer attempts with From de40e8d2bbe5eac932efd78d76b763512e0a90c0 Mon Sep 17 00:00:00 2001 From: Cindy Jiang <47068112+cindyyuanjiang@users.noreply.github.com> Date: Fri, 22 Nov 2024 11:55:02 -0800 Subject: [PATCH 10/22] [FEA] Add stage/task level diagnostic output for GPU slowness in Profiler tool (#1375) * initial implementation Signed-off-by: cindyyuanjiang * updated output schema based on offline discussion Signed-off-by: cindyyuanjiang * address feedback to merge two tables together Signed-off-by: cindyyuanjiang * update order of columns Signed-off-by: cindyyuanjiang * get gpu semaphore time Signed-off-by: cindyyuanjiang * add benchmark Signed-off-by: cindyyuanjiang * clean up code Signed-off-by: cindyyuanjiang * add unit test Signed-off-by: cindyyuanjiang * new expectation file Signed-off-by: cindyyuanjiang * address review feedback Signed-off-by: cindyyuanjiang * address review feedback Signed-off-by: cindyyuanjiang * add new file Signed-off-by: cindyyuanjiang * remove unnecessary comment Signed-off-by: cindyyuanjiang * address review feedback Signed-off-by: cindyyuanjiang * refactored for memory optimization Signed-off-by: cindyyuanjiang * addressed review feedback Signed-off-by: cindyyuanjiang * refactor stageDiagnosticResults Signed-off-by: cindyyuanjiang * change num attemps to tasks Signed-off-by: cindyyuanjiang * remove diagnostic from applicationsummaryinfo Signed-off-by: cindyyuanjiang * remove unused import Signed-off-by: cindyyuanjiang * new file Signed-off-by: cindyyuanjiang * add diagnostic view in qual tool output Signed-off-by: cindyyuanjiang * remove diagnostic vire from qual tool profile.log file Signed-off-by: cindyyuanjiang * address review feedback Signed-off-by: cindyyuanjiang * add profile benchmark class Signed-off-by: cindyyuanjiang * fix profiler benchmark Signed-off-by: cindyyuanjiang --------- Signed-off-by: cindyyuanjiang --- .../tool/analysis/AggRawMetricsResult.scala | 6 +- .../rapids/tool/analysis/AnalysisUtils.scala | 36 ++++ .../tool/analysis/AppSQLPlanAnalyzer.scala | 28 ++- .../analysis/AppSparkMetricsAggTrait.scala | 12 +- .../analysis/AppSparkMetricsAnalyzer.scala | 91 +++++++- .../profiling/DiagnosticSummaryInfo.scala | 25 +++ .../profiling/ProfileClassWarehouse.scala | 204 ++++++++++++++---- .../tool/profiling/ProfileOutputWriter.scala | 6 + .../rapids/tool/profiling/Profiler.scala | 51 +++-- .../rapids/tool/tuning/TunerContext.scala | 6 +- .../tool/views/AggMetricsResultSorter.scala | 15 +- .../tool/views/QualRawReportGenerator.scala | 18 +- .../rapids/tool/views/RawMetricProfView.scala | 8 +- .../spark/rapids/tool/views/package.scala | 1 + .../SingleThreadedProfileToolBenchmark.scala | 36 ++++ .../sql/rapids/tool/store/AccumNameRef.scala | 4 + ..._stagediagnosticmetricsagg_expectation.csv | 5 + .../rapids/tool/profiling/AnalysisSuite.scala | 87 ++++++++ .../tool/profiling/ApplicationInfoSuite.scala | 8 +- 19 files changed, 560 insertions(+), 87 deletions(-) create mode 100644 core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AnalysisUtils.scala create mode 100644 core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/DiagnosticSummaryInfo.scala create mode 100644 core/src/main/scala/org/apache/spark/rapids/tool/benchmarks/SingleThreadedProfileToolBenchmark.scala create mode 100644 core/src/test/resources/ProfilingExpectations/rapids_join_eventlog_stagediagnosticmetricsagg_expectation.csv diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AggRawMetricsResult.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AggRawMetricsResult.scala index b21e36054..2584d702f 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AggRawMetricsResult.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AggRawMetricsResult.scala @@ -16,7 +16,7 @@ package com.nvidia.spark.rapids.tool.analysis -import com.nvidia.spark.rapids.tool.profiling.{IOAnalysisProfileResult, JobAggTaskMetricsProfileResult, ShuffleSkewProfileResult, SQLDurationExecutorTimeProfileResult, SQLMaxTaskInputSizes, SQLTaskAggMetricsProfileResult, StageAggTaskMetricsProfileResult} +import com.nvidia.spark.rapids.tool.profiling.{IOAnalysisProfileResult, JobAggTaskMetricsProfileResult, ShuffleSkewProfileResult, SQLDurationExecutorTimeProfileResult, SQLMaxTaskInputSizes, SQLTaskAggMetricsProfileResult, StageAggTaskMetricsProfileResult, StageDiagnosticResult} /** * The result of the aggregation of the raw metrics. It contains the aggregated metrics for an @@ -32,6 +32,7 @@ import com.nvidia.spark.rapids.tool.profiling.{IOAnalysisProfileResult, JobAggTa * @param ioAggs lists the SQLs along their IO metrics * @param sqlDurAggs the aggregated duration and CPU time for SQLs * @param maxTaskInputSizes a sequence of SQLMaxTaskInputSizes that contains the maximum input size + * @param stageDiagnostics the stage level Spark metrics for diagnostic purposes */ case class AggRawMetricsResult( jobAggs: Seq[JobAggTaskMetricsProfileResult], @@ -40,4 +41,5 @@ case class AggRawMetricsResult( sqlAggs: Seq[SQLTaskAggMetricsProfileResult], ioAggs: Seq[IOAnalysisProfileResult], sqlDurAggs: Seq[SQLDurationExecutorTimeProfileResult], - maxTaskInputSizes: Seq[SQLMaxTaskInputSizes]) + maxTaskInputSizes: Seq[SQLMaxTaskInputSizes], + stageDiagnostics: Seq[StageDiagnosticResult]) diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AnalysisUtils.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AnalysisUtils.scala new file mode 100644 index 000000000..01f6989c7 --- /dev/null +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AnalysisUtils.scala @@ -0,0 +1,36 @@ +/* + * Copyright (c) 2024, NVIDIA CORPORATION. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package com.nvidia.spark.rapids.tool.analysis + +object StageAccumDiagnosticMetrics { + val MEMORY_SPILLED_METRIC = "internal.metrics.memoryBytesSpilled" + val DISK_SPILLED_METRIC = "internal.metrics.diskBytesSpilled" + val INPUT_BYTES_READ_METRIC = "internal.metrics.input.bytesRead" + val OUTPUT_BYTES_WRITTEN_METRIC = "internal.metrics.output.bytesWritten" + val SW_TOTAL_BYTES_METRIC = "internal.metrics.shuffle.write.bytesWritten" + val SR_FETCH_WAIT_TIME_METRIC = "internal.metrics.shuffle.read.fetchWaitTime" + val SW_WRITE_TIME_METRIC = "internal.metrics.shuffle.write.writeTime" + val GPU_SEMAPHORE_WAIT_METRIC = "gpuSemaphoreWait" + + /** + * Get all diagnostic metrics + */ + def getAllDiagnosticMetrics: Set[String] = Set(MEMORY_SPILLED_METRIC, + DISK_SPILLED_METRIC, INPUT_BYTES_READ_METRIC, OUTPUT_BYTES_WRITTEN_METRIC, + SW_TOTAL_BYTES_METRIC, SR_FETCH_WAIT_TIME_METRIC, SW_WRITE_TIME_METRIC, + GPU_SEMAPHORE_WAIT_METRIC) +} diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AppSQLPlanAnalyzer.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AppSQLPlanAnalyzer.scala index e32061726..7e17767b9 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AppSQLPlanAnalyzer.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AppSQLPlanAnalyzer.scala @@ -56,6 +56,24 @@ class AppSQLPlanAnalyzer(app: AppBase, appIndex: Int) extends AppAnalysisBase(ap // SQLPlanParser. var unsupportedSQLPlan: ArrayBuffer[UnsupportedSQLPlan] = ArrayBuffer[UnsupportedSQLPlan]() var allSQLMetrics: ArrayBuffer[SQLMetricInfoCase] = ArrayBuffer[SQLMetricInfoCase]() + // A map between stage ID and a set of node names + val stageToNodeNames: HashMap[Long, Seq[String]] = HashMap.empty[Long, Seq[String]] + // A map between stage ID and diagnostic metrics results (stored as a map between metric name + // and AccumProfileResults) + val stageToDiagnosticMetrics: HashMap[Long, HashMap[String, AccumProfileResults]] = + HashMap.empty[Long, HashMap[String, AccumProfileResults]] + + /** + * Given an input diagnostic metric result, update stageToDiagnosticMetrics mapping + * @param accum AccumProfileResults to be analyzed + */ + private def updateStageDiagnosticMetrics(accum: AccumProfileResults): Unit = { + val stageId = accum.stageId + if (!stageToDiagnosticMetrics.contains(stageId)) { + stageToDiagnosticMetrics(stageId) = HashMap.empty[String, AccumProfileResults] + } + stageToDiagnosticMetrics(stageId)(accum.accMetaRef.getName()) = accum + } /** * Connects Operators to Stages using AccumulatorIDs. @@ -261,6 +279,7 @@ class AppSQLPlanAnalyzer(app: AppBase, appIndex: Int) extends AppAnalysisBase(ap } validNodes.map(n => s"${n.name}(${n.id.toString})") }.getOrElse(Seq.empty) + stageToNodeNames(sModel.stageInfo.stageId) = nodeNames SQLStageInfoProfileResult(appIndex, j.sqlID.get, jobId, sModel.stageInfo.stageId, sModel.stageInfo.attemptNumber(), sModel.duration, nodeNames) } @@ -339,14 +358,19 @@ class AppSQLPlanAnalyzer(app: AppBase, appIndex: Int) extends AppAnalysisBase(ap } else { taskUpatesSubset(taskUpatesSubset.size / 2) } - Some(AccumProfileResults( + // reuse AccumProfileResults to avoid generating extra memory from allocating new objects + val accumProfileResults = AccumProfileResults( appIndex, stageId, accumInfo.infoRef, min = min, median = median, max = max, - total = sum)) + total = sum) + if (accumInfo.infoRef.name.isDiagnosticMetrics()) { + updateStageDiagnosticMetrics(accumProfileResults) + } + Some(accumProfileResults) } }) } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AppSparkMetricsAggTrait.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AppSparkMetricsAggTrait.scala index e219ee46b..0f43ae8b2 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AppSparkMetricsAggTrait.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AppSparkMetricsAggTrait.scala @@ -26,10 +26,14 @@ trait AppSparkMetricsAggTrait extends AppIndexMapperTrait { * object to aggregate the Raw metrics and returns the result * @param app the AppBase to be analyzed * @param index the application index + * @param sqlAnalyzer optional AppSQLPlanAnalyzer used to aggregate diagnostic metrics, + * this is already present in ApplicationInfo for Profiler, but for + * Qualification this argument needs to be provided. * @return a single record of AggRawMetricsResult containing all the raw aggregated Spark * metrics */ - def getAggRawMetrics(app: AppBase, index: Int): AggRawMetricsResult = { + def getAggRawMetrics(app: AppBase, index: Int, sqlAnalyzer: Option[AppSQLPlanAnalyzer] = None): + AggRawMetricsResult = { val analysisObj = new AppSparkMetricsAnalyzer(app) AggRawMetricsResult( analysisObj.aggregateSparkMetricsByJob(index), @@ -38,7 +42,8 @@ trait AppSparkMetricsAggTrait extends AppIndexMapperTrait { analysisObj.aggregateSparkMetricsBySql(index), analysisObj.aggregateIOMetricsBySql(analysisObj.aggregateSparkMetricsBySql(index)), analysisObj.aggregateDurationAndCPUTimeBySql(index), - Seq(analysisObj.maxTaskInputSizeBytesPerSQL(index))) + Seq(analysisObj.maxTaskInputSizeBytesPerSQL(index)), + analysisObj.aggregateDiagnosticMetricsByStage(index, sqlAnalyzer)) } /** @@ -59,7 +64,8 @@ trait AppSparkMetricsAggTrait extends AppIndexMapperTrait { agg1.sqlAggs ++ agg2.sqlAggs, agg1.ioAggs ++ agg2.ioAggs, agg1.sqlDurAggs ++ agg2.sqlDurAggs, - agg1.maxTaskInputSizes ++ agg2.maxTaskInputSizes) + agg1.maxTaskInputSizes ++ agg2.maxTaskInputSizes, + agg1.stageDiagnostics ++ agg2.stageDiagnostics) } } } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AppSparkMetricsAnalyzer.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AppSparkMetricsAnalyzer.scala index 48723739a..69dcbb787 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AppSparkMetricsAnalyzer.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AppSparkMetricsAnalyzer.scala @@ -18,13 +18,15 @@ package com.nvidia.spark.rapids.tool.analysis import java.util.concurrent.TimeUnit -import scala.collection.mutable +import scala.collection.mutable.{ArrayBuffer, HashMap, LinkedHashMap} +import com.nvidia.spark.rapids.tool.analysis.StageAccumDiagnosticMetrics._ import com.nvidia.spark.rapids.tool.planparser.DatabricksParseHelper -import com.nvidia.spark.rapids.tool.profiling.{IOAnalysisProfileResult, JobAggTaskMetricsProfileResult, ShuffleSkewProfileResult, SQLDurationExecutorTimeProfileResult, SQLMaxTaskInputSizes, SQLTaskAggMetricsProfileResult, StageAggTaskMetricsProfileResult} +import com.nvidia.spark.rapids.tool.profiling.{AccumProfileResults, IOAnalysisProfileResult, JobAggTaskMetricsProfileResult, ShuffleSkewProfileResult, SQLDurationExecutorTimeProfileResult, SQLMaxTaskInputSizes, SQLTaskAggMetricsProfileResult, StageAggTaskMetricsProfileResult, StageDiagnosticResult} import org.apache.spark.sql.rapids.tool.{AppBase, ToolUtils} -import org.apache.spark.sql.rapids.tool.store.{AccumInfo, TaskModel} +import org.apache.spark.sql.rapids.tool.profiling.ApplicationInfo +import org.apache.spark.sql.rapids.tool.store.{AccumInfo, AccumMetaRef, AccumNameRef, TaskModel} /** * Does analysis on the DataFrames from object of AppBase. @@ -50,14 +52,14 @@ class AppSparkMetricsAnalyzer(app: AppBase) extends AppAnalysisBase(app) { // Hashmap to cache the stage level metrics. It is initialized to None just in case the caller // does not call methods in order starting with stage level metrics. private var stageLevelCache: - Option[mutable.LinkedHashMap[Int, StageAggTaskMetricsProfileResult]] = None + Option[LinkedHashMap[Int, StageAggTaskMetricsProfileResult]] = None // Getter method used to protect the cache from out-of-order calls. // If the stage-level metrics are not generated yet, generates and add them to the cache private def stageLevelSparkMetrics( - index: Int): mutable.LinkedHashMap[Int, StageAggTaskMetricsProfileResult] = { + index: Int): LinkedHashMap[Int, StageAggTaskMetricsProfileResult] = { if (stageLevelCache.isEmpty) { - stageLevelCache = Some(mutable.LinkedHashMap[Int, StageAggTaskMetricsProfileResult]()) + stageLevelCache = Some(LinkedHashMap[Int, StageAggTaskMetricsProfileResult]()) aggregateSparkMetricsByStageInternal(index) } stageLevelCache.get @@ -320,6 +322,62 @@ class AppSparkMetricsAnalyzer(app: AppBase) extends AppAnalysisBase(app) { sqlRows.toSeq } + /** + * Aggregates the diagnostic SparkMetrics by stage. + * @param index the App-index (used by the profiler tool) + * @param analyzer optional AppSQLPlanAnalyzer which is used to pull stage level + * information like node names and diagnostic metrics results, only + * Qualification needs to provide this argument. + * @return sequence of StageDiagnosticAggTaskMetricsProfileResult + */ + def aggregateDiagnosticMetricsByStage(index: Int, analyzer: Option[AppSQLPlanAnalyzer] = None): + Seq[StageDiagnosticResult] = { + val sqlAnalyzer = analyzer match { + case Some(res) => res + case None => + // for Profiler this is present in ApplicationInfo + app.asInstanceOf[ApplicationInfo].planMetricProcessor + } + val zeroAccumProfileResults = + AccumProfileResults(0, 0, AccumMetaRef(0L, AccumNameRef("")), 0L, 0L, 0L, 0L) + + // TODO: this has stage attempts. we should handle different attempts + app.stageManager.getAllStages.map { sm => + // TODO: Should we only consider successful tasks? + val tasksInStage = app.taskManager.getTasks(sm.stageInfo.stageId, + sm.stageInfo.attemptNumber()) + // count duplicate task attempts + val numTasks = tasksInStage.size + val nodeNames = sqlAnalyzer.stageToNodeNames. + getOrElse(sm.stageInfo.stageId, Seq.empty[String]) + val diagnosticMetricsMap = sqlAnalyzer.stageToDiagnosticMetrics. + getOrElse(sm.stageInfo.stageId, HashMap.empty[String, AccumProfileResults]). + withDefaultValue(zeroAccumProfileResults) + val srTotalBytesMetrics = + AppSparkMetricsAnalyzer.getStatistics(tasksInStage.map(_.sr_totalBytesRead)) + + StageDiagnosticResult(index, + app.getAppName, + app.appId, + sm.stageInfo.stageId, + sm.duration, + numTasks, + srTotalBytesMetrics.min, + srTotalBytesMetrics.med, + srTotalBytesMetrics.max, + srTotalBytesMetrics.total, + diagnosticMetricsMap(MEMORY_SPILLED_METRIC), + diagnosticMetricsMap(DISK_SPILLED_METRIC), + diagnosticMetricsMap(INPUT_BYTES_READ_METRIC), + diagnosticMetricsMap(OUTPUT_BYTES_WRITTEN_METRIC), + diagnosticMetricsMap(SW_TOTAL_BYTES_METRIC), + diagnosticMetricsMap(SR_FETCH_WAIT_TIME_METRIC), + diagnosticMetricsMap(SW_WRITE_TIME_METRIC), + diagnosticMetricsMap(GPU_SEMAPHORE_WAIT_METRIC), + nodeNames) + }.toSeq + } + /** * Aggregates the SparkMetrics by stage. This is an internal method to populate the cached metrics * to be used by other aggregators. @@ -336,8 +394,8 @@ class AppSparkMetricsAnalyzer(app: AppBase) extends AppAnalysisBase(app) { // Note: // - A HashMap could be used instead of separate mutable.ArrayBuffer for each metric type, // but avoiding it for readability. - val photonPeakMemoryAccumInfos = mutable.ArrayBuffer[AccumInfo]() - val photonShuffleWriteTimeAccumInfos = mutable.ArrayBuffer[AccumInfo]() + val photonPeakMemoryAccumInfos = ArrayBuffer[AccumInfo]() + val photonShuffleWriteTimeAccumInfos = ArrayBuffer[AccumInfo]() if (app.isPhoton) { app.accumManager.applyToAccumInfoMap { accumInfo => @@ -434,6 +492,23 @@ object AppSparkMetricsAnalyzer { } } + /** + * Given an input iterable, returns its min, median, max and sum. + */ + def getStatistics(arr: Iterable[Long]): StatisticsMetrics = { + if (arr.isEmpty) { + StatisticsMetrics(0L, 0L, 0L, 0L) + } + val sortedArr = arr.toSeq.sorted + val len = sortedArr.size + val med = if (len % 2 == 0) { + (sortedArr(len / 2) + sortedArr(len / 2 - 1)) / 2 + } else { + sortedArr(len / 2) + } + StatisticsMetrics(sortedArr.head, med, sortedArr(len - 1), sortedArr.sum) + } + def maxWithEmptyHandling(arr: Iterable[Long]): Long = { if (arr.isEmpty) { 0L diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/DiagnosticSummaryInfo.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/DiagnosticSummaryInfo.scala new file mode 100644 index 000000000..6ba34f7f5 --- /dev/null +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/DiagnosticSummaryInfo.scala @@ -0,0 +1,25 @@ +/* + * Copyright (c) 2024, NVIDIA CORPORATION. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package com.nvidia.spark.rapids.tool.profiling + +/** + * Stores Profiler diagnostic info. + * TODO: We plan to add two more fields/views in upcoming PRs. + */ +case class DiagnosticSummaryInfo( + stageDiagnostics: Seq[StageDiagnosticResult] +) diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/ProfileClassWarehouse.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/ProfileClassWarehouse.scala index 24b6cbd73..ab5abdd2b 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/ProfileClassWarehouse.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/ProfileClassWarehouse.scala @@ -96,9 +96,7 @@ case class SQLCleanAndAlignIdsProfileResult( override def convertToSeq: Seq[String] = { Seq(appIndex.toString, sqlID.toString) } - override def convertToCSVSeq: Seq[String] = { - Seq(appIndex.toString, sqlID.toString) - } + override def convertToCSVSeq: Seq[String] = convertToSeq } case class SQLStageInfoProfileResult( @@ -185,9 +183,7 @@ case class AppStatusResult( Seq(path, status, appId, message) } - override def convertToCSVSeq: Seq[String] = { - Seq(path, status, appId, message) - } + override def convertToCSVSeq: Seq[String] = convertToSeq } // note that some things might not be set until after sqlMetricsAggregation called @@ -501,40 +497,8 @@ trait BaseJobStageAggTaskMetricsProfileResult extends ProfileResult { swRecordsWrittenSum.toString, swWriteTimeSum.toString) } - override def convertToCSVSeq: Seq[String] = { - Seq(appIndex.toString, - id.toString, - numTasks.toString, - durStr, - diskBytesSpilledSum.toString, - durationSum.toString, - durationMax.toString, - durationMin.toString, - durationAvg.toString, - executorCPUTimeSum.toString, - executorDeserializeCpuTimeSum.toString, - executorDeserializeTimeSum.toString, - executorRunTimeSum.toString, - inputBytesReadSum.toString, - inputRecordsReadSum.toString, - jvmGCTimeSum.toString, - memoryBytesSpilledSum.toString, - outputBytesWrittenSum.toString, - outputRecordsWrittenSum.toString, - peakExecutionMemoryMax.toString, - resultSerializationTimeSum.toString, - resultSizeMax.toString, - srFetchWaitTimeSum.toString, - srLocalBlocksFetchedSum.toString, - srcLocalBytesReadSum.toString, - srRemoteBlocksFetchSum.toString, - srRemoteBytesReadSum.toString, - srRemoteBytesReadToDiskSum.toString, - srTotalBytesReadSum.toString, - swBytesWrittenSum.toString, - swRecordsWrittenSum.toString, - swWriteTimeSum.toString) - } + + override def convertToCSVSeq: Seq[String] = convertToSeq } case class JobAggTaskMetricsProfileResult( @@ -609,6 +573,166 @@ case class StageAggTaskMetricsProfileResult( override def idHeader = "stageId" } +case class StageDiagnosticResult( + appIndex: Int, + appName: String, + appId: String, + stageId: Long, + duration: Option[Long], + numTasks: Int, + srTotalBytesReadMin: Long, + srTotalBytesReadMed: Long, + srTotalBytesReadMax: Long, + srTotalBytesReadSum: Long, + memoryBytesSpilled: AccumProfileResults, + diskBytesSpilled: AccumProfileResults, + inputBytesRead: AccumProfileResults, + outputBytesWritten: AccumProfileResults, + swBytesWritten: AccumProfileResults, + srFetchWaitTime: AccumProfileResults, + swWriteTime: AccumProfileResults, + gpuSemaphoreWait: AccumProfileResults, + nodeNames: Seq[String]) extends ProfileResult { + + def bytesToMB(numBytes: Long): Long = numBytes / (1024 * 1024) + + def nanoToMilliSec(numNano: Long): Long = numNano / 1000000 + + val durStr = duration match { + case Some(dur) => dur.toString + case None => "null" + } + + override val outputHeaders = { + Seq("appIndex", + "appName", + "appId", + "stageId", + "stageDurationMs", + "numTasks", + "memoryBytesSpilledMBMin", + "memoryBytesSpilledMBMedian", + "memoryBytesSpilledMBMax", + "memoryBytesSpilledMBTotal", + "diskBytesSpilledMBMin", + "diskBytesSpilledMBMedian", + "diskBytesSpilledMBMax", + "diskBytesSpilledMBTotal", + "inputBytesReadMin", + "inputBytesReadMedian", + "inputBytesReadMax", + "inputBytesReadTotal", + "outputBytesWrittenMin", + "outputBytesWrittenMedian", + "outputBytesWrittenMax", + "outputBytesWrittenTotal", + "shuffleReadBytesMin", + "shuffleReadBytesMedian", + "shuffleReadBytesMax", + "shuffleReadBytesTotal", + "shuffleWriteBytesMin", + "shuffleWriteBytesMedian", + "shuffleWriteBytesMax", + "shuffleWriteBytesTotal", + "shuffleReadFetchWaitTimeMin", + "shuffleReadFetchWaitTimeMedian", + "shuffleReadFetchWaitTimeMax", + "shuffleReadFetchWaitTimeTotal", + "shuffleWriteWriteTimeMin", + "shuffleWriteWriteTimeMedian", + "shuffleWriteWriteTimeMax", + "shuffleWriteWriteTimeTotal", + "gpuSemaphoreWaitTimeTotal", + "SQL Nodes(IDs)") + } + + override def convertToSeq: Seq[String] = { + Seq(appIndex.toString, + appName, + appId, + stageId.toString, + durStr, + numTasks.toString, + bytesToMB(memoryBytesSpilled.min).toString, + bytesToMB(memoryBytesSpilled.median).toString, + bytesToMB(memoryBytesSpilled.max).toString, + bytesToMB(memoryBytesSpilled.total).toString, + bytesToMB(diskBytesSpilled.min).toString, + bytesToMB(diskBytesSpilled.median).toString, + bytesToMB(diskBytesSpilled.max).toString, + bytesToMB(diskBytesSpilled.total).toString, + inputBytesRead.min.toString, + inputBytesRead.median.toString, + inputBytesRead.max.toString, + inputBytesRead.total.toString, + outputBytesWritten.min.toString, + outputBytesWritten.median.toString, + outputBytesWritten.max.toString, + outputBytesWritten.total.toString, + srTotalBytesReadMin.toString, + srTotalBytesReadMed.toString, + srTotalBytesReadMax.toString, + srTotalBytesReadSum.toString, + swBytesWritten.min.toString, + swBytesWritten.median.toString, + swBytesWritten.max.toString, + swBytesWritten.total.toString, + nanoToMilliSec(srFetchWaitTime.min).toString, + nanoToMilliSec(srFetchWaitTime.median).toString, + nanoToMilliSec(srFetchWaitTime.max).toString, + nanoToMilliSec(srFetchWaitTime.total).toString, + nanoToMilliSec(swWriteTime.min).toString, + nanoToMilliSec(swWriteTime.median).toString, + nanoToMilliSec(swWriteTime.max).toString, + nanoToMilliSec(swWriteTime.total).toString, + gpuSemaphoreWait.total.toString, + nodeNames.mkString(",")) + } + + override def convertToCSVSeq: Seq[String] = { + Seq(appIndex.toString, + appName, + appId, + stageId.toString, + durStr, + numTasks.toString, + bytesToMB(memoryBytesSpilled.min).toString, + bytesToMB(memoryBytesSpilled.median).toString, + bytesToMB(memoryBytesSpilled.max).toString, + bytesToMB(memoryBytesSpilled.total).toString, + bytesToMB(diskBytesSpilled.min).toString, + bytesToMB(diskBytesSpilled.median).toString, + bytesToMB(diskBytesSpilled.max).toString, + bytesToMB(diskBytesSpilled.total).toString, + inputBytesRead.min.toString, + inputBytesRead.median.toString, + inputBytesRead.max.toString, + inputBytesRead.total.toString, + outputBytesWritten.min.toString, + outputBytesWritten.median.toString, + outputBytesWritten.max.toString, + outputBytesWritten.total.toString, + srTotalBytesReadMin.toString, + srTotalBytesReadMed.toString, + srTotalBytesReadMax.toString, + srTotalBytesReadSum.toString, + swBytesWritten.min.toString, + swBytesWritten.median.toString, + swBytesWritten.max.toString, + swBytesWritten.total.toString, + nanoToMilliSec(srFetchWaitTime.min).toString, + nanoToMilliSec(srFetchWaitTime.median).toString, + nanoToMilliSec(srFetchWaitTime.max).toString, + nanoToMilliSec(srFetchWaitTime.total).toString, + nanoToMilliSec(swWriteTime.min).toString, + nanoToMilliSec(swWriteTime.median).toString, + nanoToMilliSec(swWriteTime.max).toString, + nanoToMilliSec(swWriteTime.total).toString, + gpuSemaphoreWait.total.toString, + StringUtils.reformatCSVString(nodeNames.mkString(","))) + } +} + case class SQLMaxTaskInputSizes( appIndex: Int, appId: String, diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/ProfileOutputWriter.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/ProfileOutputWriter.scala index e42ec24fa..3c87919ee 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/ProfileOutputWriter.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/ProfileOutputWriter.scala @@ -74,6 +74,12 @@ class ProfileOutputWriter(outputDir: String, filePrefix: String, numOutputRows: } } + def writeCSVTable(headerText: String, outRows: Seq[ProfileResult]): Unit = { + if (outputCSV) { + ProfileOutputWriter.writeCSVTable(headerText, outRows, outputDir) + } + } + def close(): Unit = { textFileWriter.close() } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/Profiler.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/Profiler.scala index a69701c64..75b4c4590 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/Profiler.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/Profiler.scala @@ -76,9 +76,11 @@ class Profiler(hadoopConf: Configuration, appArgs: ProfileArgs, enablePB: Boolea Profiler.COMPARE_LOG_FILE_NAME_PREFIX, numOutputRows, outputCSV = outputCSV) try { // we need the info for all of the apps to be able to compare so this happens serially - val (sums, comparedRes) = processApps(apps, printPlans = false, profileOutputWriter) + val (sums, comparedRes, diagnostics) = + processApps(apps, printPlans = false, profileOutputWriter) progressBar.foreach(_.reportSuccessfulProcesses(apps.size)) - writeSafelyToOutput(profileOutputWriter, Seq(sums), false, comparedRes) + writeSafelyToOutput(profileOutputWriter, Seq(sums), false, comparedRes, + Seq(diagnostics)) } catch { case _: Exception => progressBar.foreach(_.reportFailedProcesses(apps.size)) @@ -97,8 +99,8 @@ class Profiler(hadoopConf: Configuration, appArgs: ProfileArgs, enablePB: Boolea // combine them into single tables in the output. val profileOutputWriter = new ProfileOutputWriter(s"$outputDir/combined", Profiler.COMBINED_LOG_FILE_NAME_PREFIX, numOutputRows, outputCSV = outputCSV) - val sums = createAppsAndSummarize(eventLogInfos, profileOutputWriter) - writeSafelyToOutput(profileOutputWriter, sums, outputCombined) + val (sums, diagnostics) = createAppsAndSummarize(eventLogInfos, profileOutputWriter) + writeSafelyToOutput(profileOutputWriter, sums, outputCombined, diagnosticSum = diagnostics) profileOutputWriter.close() } } else { @@ -227,14 +229,18 @@ class Profiler(hadoopConf: Configuration, appArgs: ProfileArgs, enablePB: Boolea allApps.asScala.toSeq } - private def createAppsAndSummarize(allPaths: Seq[EventLogInfo], - profileOutputWriter: ProfileOutputWriter): Seq[ApplicationSummaryInfo] = { + private def createAppsAndSummarize( + allPaths: Seq[EventLogInfo], + profileOutputWriter: ProfileOutputWriter) + : (Seq[ApplicationSummaryInfo], Seq[DiagnosticSummaryInfo]) = { val allApps = new ConcurrentLinkedQueue[ApplicationSummaryInfo]() + val allDiagnostics = new ConcurrentLinkedQueue[DiagnosticSummaryInfo]() class ProfileThread(path: EventLogInfo, index: Int) extends Runnable { def run: Unit = profileApp(path, index, { app => - val (s, _) = processApps(Seq(app), false, profileOutputWriter) + val (s, _, d) = processApps(Seq(app), false, profileOutputWriter) allApps.add(s) + allDiagnostics.add(d) }) } @@ -255,7 +261,7 @@ class Profiler(hadoopConf: Configuration, appArgs: ProfileArgs, enablePB: Boolea " stopping processing any more event logs") threadPool.shutdownNow() } - allApps.asScala.toSeq + (allApps.asScala.toSeq, allDiagnostics.asScala.toSeq) } private def createAppAndProcess( @@ -266,8 +272,10 @@ class Profiler(hadoopConf: Configuration, appArgs: ProfileArgs, enablePB: Boolea val profileOutputWriter = new ProfileOutputWriter(s"$outputDir/${app.appId}", Profiler.PROFILE_LOG_NAME, numOutputRows, outputCSV = outputCSV) try { - val (sum, _) = processApps(Seq(app), appArgs.printPlans(), profileOutputWriter) - writeSafelyToOutput(profileOutputWriter, Seq(sum), false) + val (sum, _, diagnostics) = + processApps(Seq(app), appArgs.printPlans(), profileOutputWriter) + writeSafelyToOutput(profileOutputWriter, Seq(sum), false, + diagnosticSum = Seq(diagnostics)) } finally { profileOutputWriter.close() } @@ -312,7 +320,7 @@ class Profiler(hadoopConf: Configuration, appArgs: ProfileArgs, enablePB: Boolea apps: Seq[ApplicationInfo], printPlans: Boolean, profileOutputWriter: ProfileOutputWriter) - : (ApplicationSummaryInfo, Option[CompareSummaryInfo]) = { + : (ApplicationSummaryInfo, Option[CompareSummaryInfo], DiagnosticSummaryInfo) = { val startTime = System.currentTimeMillis() val collect = new CollectInformation(apps) @@ -327,6 +335,7 @@ class Profiler(hadoopConf: Configuration, appArgs: ProfileArgs, enablePB: Boolea val stageMetrics = collect.getStageLevelMetrics val wholeStage = collect.getWholeStageCodeGenMapping val sparkRapidsBuildInfo = collect.getSparkRapidsInfo + // for compare mode we just add in extra tables for matching across applications // the rest of the tables simply list all applications specified val compareRes = if (appArgs.compare()) { @@ -393,7 +402,8 @@ class Profiler(hadoopConf: Configuration, appArgs: ProfileArgs, enablePB: Boolea analysis.sqlAggs, analysis.sqlDurAggs, analysis.taskShuffleSkew, failedTasks, failedStages, failedJobs, removedBMs, removedExecutors, unsupportedOps, sparkProps, collect.getSQLToStage, wholeStage, maxTaskInputInfo, - appLogPath, analysis.ioAggs, systemProps, sqlIdAlign, sparkRapidsBuildInfo), compareRes) + appLogPath, analysis.ioAggs, systemProps, sqlIdAlign, sparkRapidsBuildInfo), + compareRes, DiagnosticSummaryInfo(analysis.stageDiagnostics)) } /** @@ -427,7 +437,8 @@ class Profiler(hadoopConf: Configuration, appArgs: ProfileArgs, enablePB: Boolea def writeOutput(profileOutputWriter: ProfileOutputWriter, appsSum: Seq[ApplicationSummaryInfo], outputCombined: Boolean, - comparedRes: Option[CompareSummaryInfo] = None): Unit = { + comparedRes: Option[CompareSummaryInfo] = None, + diagnosticSum: Seq[DiagnosticSummaryInfo]): Unit = { val sums = if (outputCombined) { // the properties table here has the column names as the app indexes so we have to @@ -557,6 +568,15 @@ class Profiler(hadoopConf: Configuration, appArgs: ProfileArgs, enablePB: Boolea profileOutputWriter.writeSparkRapidsBuildInfo("Spark Rapids Build Info", app.sparkRapidsBuildInfo) } + // Write diagnostic related results to CSV files + val diagnostics = if (outputCombined) { + Seq(DiagnosticSummaryInfo(diagnosticSum.flatMap(_.stageDiagnostics))) + } else { + diagnosticSum + } + diagnostics.foreach { diagnostoic => + profileOutputWriter.writeCSVTable(STAGE_DIAGNOSTICS_LABEL, diagnostoic.stageDiagnostics) + } } /** @@ -566,9 +586,10 @@ class Profiler(hadoopConf: Configuration, appArgs: ProfileArgs, enablePB: Boolea */ private def writeSafelyToOutput(profileOutputWriter: ProfileOutputWriter, appsSum: Seq[ApplicationSummaryInfo], outputCombined: Boolean, - comparedRes: Option[CompareSummaryInfo] = None): Unit = { + comparedRes: Option[CompareSummaryInfo] = None, + diagnosticSum: Seq[DiagnosticSummaryInfo]): Unit = { try { - writeOutput(profileOutputWriter, appsSum, outputCombined, comparedRes) + writeOutput(profileOutputWriter, appsSum, outputCombined, comparedRes, diagnosticSum) } catch { case e: Exception => logError("Exception thrown while writing", e) diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/tuning/TunerContext.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/tuning/TunerContext.scala index c795d0434..b9b23ec07 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/tuning/TunerContext.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/tuning/TunerContext.scala @@ -19,7 +19,7 @@ package com.nvidia.spark.rapids.tool.tuning import scala.util.{Failure, Success, Try} import com.nvidia.spark.rapids.tool.Platform -import com.nvidia.spark.rapids.tool.analysis.QualSparkMetricsAnalyzer +import com.nvidia.spark.rapids.tool.analysis.{AppSQLPlanAnalyzer, QualSparkMetricsAnalyzer} import com.nvidia.spark.rapids.tool.profiling.{DataSourceProfileResult, RecommendedCommentResult, RecommendedPropertyResult} import org.apache.hadoop.conf.Configuration @@ -53,7 +53,9 @@ case class TunerContext ( appIndex: Int = 1, dsInfo: Seq[DataSourceProfileResult], platform: Platform): Option[TuningResult] = { - val rawAggMetrics = QualSparkMetricsAnalyzer.getAggRawMetrics(appInfo, appIndex) + val sqlAnalyzer = AppSQLPlanAnalyzer(appInfo, appIndex) + val rawAggMetrics = + QualSparkMetricsAnalyzer.getAggRawMetrics(appInfo, appIndex, Some(sqlAnalyzer)) QualificationAutoTuner(appInfo, appAggStats, this, rawAggMetrics, dsInfo).collect { case qualTuner => Try { diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/views/AggMetricsResultSorter.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/views/AggMetricsResultSorter.scala index b6cbff4b0..440a4ac64 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/views/AggMetricsResultSorter.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/views/AggMetricsResultSorter.scala @@ -16,7 +16,7 @@ package com.nvidia.spark.rapids.tool.views -import com.nvidia.spark.rapids.tool.profiling.{BaseJobStageAggTaskMetricsProfileResult, IOAnalysisProfileResult, ShuffleSkewProfileResult, SQLDurationExecutorTimeProfileResult, SQLTaskAggMetricsProfileResult} +import com.nvidia.spark.rapids.tool.profiling.{BaseJobStageAggTaskMetricsProfileResult, IOAnalysisProfileResult, ShuffleSkewProfileResult, SQLDurationExecutorTimeProfileResult, SQLTaskAggMetricsProfileResult, StageDiagnosticResult} /** * Contains the sort logic for the aggregated Spark RawMetrics. @@ -91,4 +91,17 @@ object AggMetricsResultSorter { } } } + + def sortStageDiagnostics( + rows: Seq[StageDiagnosticResult]): + Seq[StageDiagnosticResult] = { + if (rows.isEmpty) { + Seq.empty + } else { + rows.sortBy { cols => + val sortDur = cols.duration.getOrElse(0L) + (cols.appIndex, -sortDur, -cols.memoryBytesSpilled.total) + } + } + } } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/views/QualRawReportGenerator.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/views/QualRawReportGenerator.scala index d1252d4ec..3a2cb8b48 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/views/QualRawReportGenerator.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/views/QualRawReportGenerator.scala @@ -36,14 +36,16 @@ object QualRawReportGenerator { AggMetricsResultSorter.sortSqlAgg(aggRawResult.sqlAggs), AggMetricsResultSorter.sortIO(aggRawResult.ioAggs), AggMetricsResultSorter.sortSqlDurationAgg(aggRawResult.sqlDurAggs), - aggRawResult.maxTaskInputSizes) + aggRawResult.maxTaskInputSizes, + AggMetricsResultSorter.sortStageDiagnostics(aggRawResult.stageDiagnostics)) Map( STAGE_AGG_LABEL -> sortedRes.stageAggs, JOB_AGG_LABEL -> sortedRes.jobAggs, TASK_SHUFFLE_SKEW -> sortedRes.taskShuffleSkew, SQL_AGG_LABEL -> sortedRes.sqlAggs, IO_LABEL -> sortedRes.ioAggs, - SQL_DUR_LABEL -> sortedRes.sqlDurAggs) + SQL_DUR_LABEL -> sortedRes.sqlDurAggs, + STAGE_DIAGNOSTICS_LABEL -> sortedRes.stageDiagnostics) } private def generateSQLProcessingView( @@ -92,11 +94,13 @@ object QualRawReportGenerator { SystemQualPropertiesView.getRawView(Seq(app)), Some(SystemQualPropertiesView.getDescription)) pWriter.writeText("\n### B. Analysis ###\n") - constructLabelsMaps( - QualSparkMetricsAnalyzer.getAggRawMetrics(app, appIndex)).foreach { case (label, metrics) => - pWriter.write(label, - metrics, - AGG_DESCRIPTION.get(label)) + constructLabelsMaps(QualSparkMetricsAnalyzer. + getAggRawMetrics(app, appIndex, Some(sqlPlanAnalyzer))).foreach { case (label, metrics) => + if (label == STAGE_DIAGNOSTICS_LABEL) { + pWriter.writeCSVTable(label, metrics) + } else { + pWriter.write(label, metrics, AGG_DESCRIPTION.get(label)) + } } pWriter.writeText("\n### C. Health Check###\n") pWriter.write(QualFailedTaskView.getLabel, QualFailedTaskView.getRawView(Seq(app))) diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/views/RawMetricProfView.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/views/RawMetricProfView.scala index 5caf7436b..3936d0222 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/views/RawMetricProfView.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/views/RawMetricProfView.scala @@ -17,7 +17,7 @@ package com.nvidia.spark.rapids.tool.views import com.nvidia.spark.rapids.tool.analysis.ProfSparkMetricsAnalyzer -import com.nvidia.spark.rapids.tool.profiling.{IOAnalysisProfileResult, JobAggTaskMetricsProfileResult, ShuffleSkewProfileResult, SQLDurationExecutorTimeProfileResult, SQLMaxTaskInputSizes, SQLTaskAggMetricsProfileResult, StageAggTaskMetricsProfileResult} +import com.nvidia.spark.rapids.tool.profiling.{IOAnalysisProfileResult, JobAggTaskMetricsProfileResult, ShuffleSkewProfileResult, SQLDurationExecutorTimeProfileResult, SQLMaxTaskInputSizes, SQLTaskAggMetricsProfileResult, StageAggTaskMetricsProfileResult, StageDiagnosticResult} import org.apache.spark.sql.rapids.tool.profiling.ApplicationInfo @@ -30,7 +30,8 @@ case class ProfilerAggregatedView( sqlAggs: Seq[SQLTaskAggMetricsProfileResult], ioAggs: Seq[IOAnalysisProfileResult], sqlDurAggs: Seq[SQLDurationExecutorTimeProfileResult], - maxTaskInputSizes: Seq[SQLMaxTaskInputSizes]) + maxTaskInputSizes: Seq[SQLMaxTaskInputSizes], + stageDiagnostics: Seq[StageDiagnosticResult]) object RawMetricProfilerView { def getAggMetrics(apps: Seq[ApplicationInfo]): ProfilerAggregatedView = { @@ -42,6 +43,7 @@ object RawMetricProfilerView { AggMetricsResultSorter.sortSqlAgg(aggMetricsResults.sqlAggs), AggMetricsResultSorter.sortIO(aggMetricsResults.ioAggs), AggMetricsResultSorter.sortSqlDurationAgg(aggMetricsResults.sqlDurAggs), - aggMetricsResults.maxTaskInputSizes) + aggMetricsResults.maxTaskInputSizes, + AggMetricsResultSorter.sortStageDiagnostics(aggMetricsResults.stageDiagnostics)) } } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/views/package.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/views/package.scala index c588aad8d..a509ae3f7 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/views/package.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/views/package.scala @@ -28,6 +28,7 @@ package object views { val IO_LABEL = "IO Metrics" val SQL_DUR_LABEL = "SQL Duration and Executor CPU Time Percent" val SQL_MAX_INPUT_SIZE = "SQL Max Task Input Size" + val STAGE_DIAGNOSTICS_LABEL = "Stage Level Diagnostic Metrics" val AGG_DESCRIPTION = Map( STAGE_AGG_LABEL -> "Stage metrics", diff --git a/core/src/main/scala/org/apache/spark/rapids/tool/benchmarks/SingleThreadedProfileToolBenchmark.scala b/core/src/main/scala/org/apache/spark/rapids/tool/benchmarks/SingleThreadedProfileToolBenchmark.scala new file mode 100644 index 000000000..575329277 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/rapids/tool/benchmarks/SingleThreadedProfileToolBenchmark.scala @@ -0,0 +1,36 @@ +/* + * Copyright (c) 2024, NVIDIA CORPORATION. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rapids.tool.benchmarks + +import com.nvidia.spark.rapids.tool.profiling.{ProfileArgs, ProfileMain} + +object ProfToolBenchmark extends BenchmarkBase { + override def runBenchmarkSuite(inputArgs: Array[String]): Unit = { + // Currently the input arguments are assumed to be common across cases + // This will be improved in a follow up PR to enable passing as a config + // file with argument support for different cases + runBenchmark("Benchmark_Profiling_CSV") { + val (prefix, suffix) = inputArgs.splitAt(inputArgs.length - 1) + addCase("Profiling_CSV") { _ => + ProfileMain.mainInternal(new ProfileArgs(prefix :+ "--num-threads" + :+ "1" :+ "--csv" :+ suffix.head), + enablePB = true) + } + run() + } + } +} diff --git a/core/src/main/scala/org/apache/spark/sql/rapids/tool/store/AccumNameRef.scala b/core/src/main/scala/org/apache/spark/sql/rapids/tool/store/AccumNameRef.scala index e7349d064..0172f5229 100644 --- a/core/src/main/scala/org/apache/spark/sql/rapids/tool/store/AccumNameRef.scala +++ b/core/src/main/scala/org/apache/spark/sql/rapids/tool/store/AccumNameRef.scala @@ -18,6 +18,8 @@ package org.apache.spark.sql.rapids.tool.store import java.util.concurrent.ConcurrentHashMap +import com.nvidia.spark.rapids.tool.analysis.StageAccumDiagnosticMetrics.getAllDiagnosticMetrics + import org.apache.spark.sql.rapids.tool.util.EventUtils.normalizeMetricName import org.apache.spark.sql.rapids.tool.util.StringUtils @@ -33,6 +35,8 @@ case class AccumNameRef(value: String) { // We opt to use this optimization because while writing the CSV files, each row is going to // create a new CSV string even though they represent the same AccumulatorName. val csvValue: String = StringUtils.reformatCSVString(value) + + def isDiagnosticMetrics(): Boolean = getAllDiagnosticMetrics.contains(value) } object AccumNameRef { diff --git a/core/src/test/resources/ProfilingExpectations/rapids_join_eventlog_stagediagnosticmetricsagg_expectation.csv b/core/src/test/resources/ProfilingExpectations/rapids_join_eventlog_stagediagnosticmetricsagg_expectation.csv new file mode 100644 index 000000000..e847d1b06 --- /dev/null +++ b/core/src/test/resources/ProfilingExpectations/rapids_join_eventlog_stagediagnosticmetricsagg_expectation.csv @@ -0,0 +1,5 @@ +appIndex,appName,appId,stageId,stageDurationMs,numTasks,memoryBytesSpilledMBMin,memoryBytesSpilledMBMedian,memoryBytesSpilledMBMax,memoryBytesSpilledMBTotal,diskBytesSpilledMBMin,diskBytesSpilledMBMedian,diskBytesSpilledMBMax,diskBytesSpilledMBTotal,inputBytesReadMin,inputBytesReadMedian,inputBytesReadMax,inputBytesReadTotal,outputBytesWrittenMin,outputBytesWrittenMedian,outputBytesWrittenMax,outputBytesWrittenTotal,shuffleReadBytesMin,shuffleReadBytesMedian,shuffleReadBytesMax,shuffleReadBytesTotal,shuffleWriteBytesMin,shuffleWriteBytesMedian,shuffleWriteBytesMax,shuffleWriteBytesTotal,shuffleReadFetchWaitTimeMin,shuffleReadFetchWaitTimeMedian,shuffleReadFetchWaitTimeMax,shuffleReadFetchWaitTimeTotal,shuffleWriteWriteTimeMin,shuffleWriteWriteTimeMedian,shuffleWriteWriteTimeMax,shuffleWriteWriteTimeTotal,gpuSemaphoreWaitTimeTotal,SQL Nodes(IDs) +1,Spark shell,local-1622814619968,0,1743,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6688608,6688702,6688825,40132250,0,0,0,0,41,60,100,400,0,"GpuColumnarExchange(16),GpuProject(17),GpuRowToColumnar(18),WholeStageCodegen (2)(19),Scan(21)" +1,Spark shell,local-1622814619968,1,1631,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6688602,6688708,6688833,40132258,0,0,0,0,37,92,108,508,0,"GpuColumnarExchange(8),GpuProject(9),GpuRowToColumnar(10),WholeStageCodegen (1)(11),Scan(13)" +1,Spark shell,local-1622814619968,2,688,200,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,397220,401479,405854,80264508,77,77,77,15400,0,0,0,0,0,0,9,93,0,"GpuColumnarExchange(3),GpuHashAggregate(4),GpuProject(5),GpuShuffledHashJoin(6),GpuShuffleCoalesce(7),GpuColumnarExchange(8),GpuCoalesceBatches(14),GpuShuffleCoalesce(15),GpuColumnarExchange(16)" +1,Spark shell,local-1622814619968,3,83,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,15400,15400,15400,15400,0,0,0,0,0,0,0,0,0,0,0,0,0,"GpuColumnarToRow(0),GpuHashAggregate(1),GpuShuffleCoalesce(2),GpuColumnarExchange(3)" diff --git a/core/src/test/scala/com/nvidia/spark/rapids/tool/profiling/AnalysisSuite.scala b/core/src/test/scala/com/nvidia/spark/rapids/tool/profiling/AnalysisSuite.scala index b247433a4..2b8c3bf12 100644 --- a/core/src/test/scala/com/nvidia/spark/rapids/tool/profiling/AnalysisSuite.scala +++ b/core/src/test/scala/com/nvidia/spark/rapids/tool/profiling/AnalysisSuite.scala @@ -25,8 +25,75 @@ import org.scalatest.FunSuite import org.apache.spark.sql.{DataFrame, SparkSession} import org.apache.spark.sql.types._ +case class TestStageDiagnosticResult( + appIndex: Int, + appName: String, + appId: String, + stageId: Long, + duration: Option[Long], + numTasks: Int, + memoryBytesSpilledMBMin: Long, + memoryBytesSpilledMBMed: Long, + memoryBytesSpilledMBMax: Long, + memoryBytesSpilledMBSum: Long, + diskBytesSpilledMBMin: Long, + diskBytesSpilledMBMed: Long, + diskBytesSpilledMBMax: Long, + diskBytesSpilledMBSum: Long, + inputBytesReadMin: Long, + inputBytesReadMed: Long, + inputBytesReadMax: Long, + inputBytesReadSum: Long, + outputBytesWrittenMin: Long, + outputBytesWrittenMed: Long, + outputBytesWrittenMax: Long, + outputBytesWrittenSum: Long, + srTotalBytesReadMin: Long, + srTotalBytesReadMed: Long, + srTotalBytesReadMax: Long, + srTotalBytesReadSum: Long, + swBytesWrittenMin: Long, + swBytesWrittenMed: Long, + swBytesWrittenMax: Long, + swBytesWrittenSum: Long, + srFetchWaitTimeMin: Long, + srFetchWaitTimeMed: Long, + srFetchWaitTimeMax: Long, + srFetchWaitTimeSum: Long, + swWriteTimeMin: Long, + swWriteTimeMed: Long, + swWriteTimeMax: Long, + swWriteTimeSum: Long, + gpuSemaphoreWaitSum: Long, + nodeNames: Seq[String]) + class AnalysisSuite extends FunSuite { + private def createTestStageDiagnosticResult(diagnosticsResults: Seq[StageDiagnosticResult]): + Seq[TestStageDiagnosticResult] = { + def bytesToMB(numBytes: Long): Long = numBytes / (1024 * 1024) + def nanoToMilliSec(numNano: Long): Long = numNano / 1000000 + diagnosticsResults.map {result => + TestStageDiagnosticResult(result.appIndex, result.appName, result.appId, result.stageId, + result.duration, result.numTasks, bytesToMB(result.memoryBytesSpilled.min), + bytesToMB(result.memoryBytesSpilled.median), bytesToMB(result.memoryBytesSpilled.max), + bytesToMB(result.memoryBytesSpilled.total), bytesToMB(result.diskBytesSpilled.min), + bytesToMB(result.diskBytesSpilled.median), bytesToMB(result.diskBytesSpilled.max), + bytesToMB(result.diskBytesSpilled.total), result.inputBytesRead.min, + result.inputBytesRead.median, result.inputBytesRead.max, result.inputBytesRead.total, + result.outputBytesWritten.min, result.outputBytesWritten.median, + result.outputBytesWritten.max, result.outputBytesWritten.total, + result.srTotalBytesReadMin, result.srTotalBytesReadMed, result.srTotalBytesReadMax, + result.srTotalBytesReadSum, result.swBytesWritten.min, result.swBytesWritten.median, + result.swBytesWritten.max, result.swBytesWritten.total, + nanoToMilliSec(result.srFetchWaitTime.min), nanoToMilliSec(result.srFetchWaitTime.median), + nanoToMilliSec(result.srFetchWaitTime.max), nanoToMilliSec(result.srFetchWaitTime.total), + nanoToMilliSec(result.swWriteTime.min), nanoToMilliSec(result.swWriteTime.median), + nanoToMilliSec(result.swWriteTime.max), nanoToMilliSec(result.swWriteTime.total), + result.gpuSemaphoreWait.total, result.nodeNames) + } + } + lazy val sparkSession = { SparkSession .builder() @@ -75,6 +142,26 @@ class AnalysisSuite extends FunSuite { expectFile("sql"), expectFile("job"), expectFile("stage")) } + test("test stage-level diagnostic aggregation simple") { + val expectFile = "rapids_join_eventlog_stagediagnosticmetricsagg_expectation.csv" + val logs = Array(s"$logDir/rapids_join_eventlog.zstd") + val apps = ToolTestUtils.processProfileApps(logs, sparkSession) + assert(apps.size == logs.size) + + // This step is to compute stage to node names and diagnostic metrics mappings, + // which is used in collecting diagnostic metrics. + val collect = new CollectInformation(apps) + collect.getSQLToStage + collect.getStageLevelMetrics + + val aggResults = RawMetricProfilerView.getAggMetrics(apps) + import org.apache.spark.sql.functions._ + import sparkSession.implicits._ + val actualDf = createTestStageDiagnosticResult(aggResults.stageDiagnostics).toDF. + withColumn("nodeNames", concat_ws(",", col("nodeNames"))) + compareMetrics(actualDf, expectFile) + } + private def testSqlMetricsAggregation(logs: Array[String], expectFileSQL: String, expectFileJob: String, expectFileStage: String): Unit = { val apps = ToolTestUtils.processProfileApps(logs, sparkSession) diff --git a/core/src/test/scala/com/nvidia/spark/rapids/tool/profiling/ApplicationInfoSuite.scala b/core/src/test/scala/com/nvidia/spark/rapids/tool/profiling/ApplicationInfoSuite.scala index de9921cec..7ff03a943 100644 --- a/core/src/test/scala/com/nvidia/spark/rapids/tool/profiling/ApplicationInfoSuite.scala +++ b/core/src/test/scala/com/nvidia/spark/rapids/tool/profiling/ApplicationInfoSuite.scala @@ -841,7 +841,7 @@ class ApplicationInfoSuite extends FunSuite with Logging { f.endsWith(".csv") }) // compare the number of files generated - assert(dotDirs.length === 20) + assert(dotDirs.length === 21) for (file <- dotDirs) { assert(file.getAbsolutePath.endsWith(".csv")) // just load each one to make sure formatted properly @@ -875,7 +875,7 @@ class ApplicationInfoSuite extends FunSuite with Logging { f.endsWith(".csv") }) // compare the number of files generated - assert(dotDirs.length === 16) + assert(dotDirs.length === 17) for (file <- dotDirs) { assert(file.getAbsolutePath.endsWith(".csv")) // just load each one to make sure formatted properly @@ -912,7 +912,7 @@ class ApplicationInfoSuite extends FunSuite with Logging { f.endsWith(".csv") }) // compare the number of files generated - assert(dotDirs.length === 20) + assert(dotDirs.length === 21) for (file <- dotDirs) { assert(file.getAbsolutePath.endsWith(".csv")) // just load each one to make sure formatted properly @@ -949,7 +949,7 @@ class ApplicationInfoSuite extends FunSuite with Logging { f.endsWith(".csv") }) // compare the number of files generated - assert(dotDirs.length === 18) + assert(dotDirs.length === 19) for (file <- dotDirs) { assert(file.getAbsolutePath.endsWith(".csv")) // just load each one to make sure formatted properly From 3cd1fe72ac16825d7438890cb167bbca4ada590b Mon Sep 17 00:00:00 2001 From: Niranjan Artal <50492963+nartal1@users.noreply.github.com> Date: Mon, 25 Nov 2024 08:59:52 -0800 Subject: [PATCH 11/22] Include expression parsers for HashAggregate and ObjectHashAggregate (#1432) * Include expression parsers for HashAggregate and ObjectHashAggregate Signed-off-by: Niranjan Artal * address review comments --------- Signed-off-by: Niranjan Artal --- .../spark/rapids/tool/planparser/GenericExecParser.scala | 3 ++- .../rapids/tool/planparser/HashAggregateExecParser.scala | 4 +++- .../tool/planparser/ObjectHashAggregateExecParser.scala | 4 +++- .../nvidia/spark/rapids/tool/planparser/SQLPlanParser.scala | 6 ++++-- 4 files changed, 12 insertions(+), 5 deletions(-) diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/GenericExecParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/GenericExecParser.scala index cd67502c5..62ffb5eaa 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/GenericExecParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/GenericExecParser.scala @@ -35,6 +35,7 @@ class GenericExecParser( override def parse: ExecInfo = { val duration = computeDuration val expressions = parseExpressions() + val notSupportedExprs = getNotSupportedExprs(expressions) val isExecSupported = checker.isExecSupported(fullExecName) && notSupportedExprs.isEmpty @@ -59,7 +60,7 @@ class GenericExecParser( } protected def getExprString: String = { - node.desc.replaceFirst(s"${node.name} ", "") + node.desc.replaceFirst(s"^${node.name}\\s*", "") } protected def getNotSupportedExprs(expressions: Array[String]): Seq[UnsupportedExpr] = { diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/HashAggregateExecParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/HashAggregateExecParser.scala index 9dc5e0d1c..99e051caf 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/HashAggregateExecParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/HashAggregateExecParser.scala @@ -26,8 +26,10 @@ case class HashAggregateExecParser( override val node: SparkPlanGraphNode, override val checker: PluginTypeChecker, override val sqlID: Long, + override val expressionFunction: Option[String => Array[String]], appBase: AppBase) extends - GenericExecParser(node, checker, sqlID, app = Some(appBase)) with Logging { + GenericExecParser(node, checker, sqlID, + expressionFunction = expressionFunction, app = Some(appBase)) with Logging { override def getDurationMetricIds: Seq[Long] = { node.metrics.find(_.name == "time in aggregation build").map(_.accumulatorId).toSeq diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ObjectHashAggregateExecParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ObjectHashAggregateExecParser.scala index c66b60f2f..717b22d3a 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ObjectHashAggregateExecParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ObjectHashAggregateExecParser.scala @@ -26,8 +26,10 @@ case class ObjectHashAggregateExecParser( override val node: SparkPlanGraphNode, override val checker: PluginTypeChecker, override val sqlID: Long, + override val expressionFunction: Option[String => Array[String]], appBase: AppBase) extends - GenericExecParser(node, checker, sqlID, app = Some(appBase)) with Logging { + GenericExecParser(node, checker, sqlID, + expressionFunction = expressionFunction, app = Some(appBase)) with Logging { override def getDurationMetricIds: Seq[Long] = { node.metrics.find(_.name == "time in aggregation build").map(_.accumulatorId).toSeq diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SQLPlanParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SQLPlanParser.scala index c4b31f78d..1b8d63a5f 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SQLPlanParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SQLPlanParser.scala @@ -491,11 +491,13 @@ object SQLPlanParser extends Logging { GenericExecParser( node, checker, sqlID, expressionFunction = Some(parseGenerateExpressions)).parse case "HashAggregate" => - HashAggregateExecParser(node, checker, sqlID, app).parse + HashAggregateExecParser( + node, checker, sqlID, Some(parseAggregateExpressions), app).parse case i if DataWritingCommandExecParser.isWritingCmdExec(i) => DataWritingCommandExecParser.parseNode(node, checker, sqlID) case "ObjectHashAggregate" => - ObjectHashAggregateExecParser(node, checker, sqlID, app).parse + ObjectHashAggregateExecParser( + node, checker, sqlID, Some(parseAggregateExpressions), app).parse case "Project" => GenericExecParser( node, checker, sqlID, expressionFunction = Some(parseProjectExpressions)).parse From 5f10bbd1f9a31660b44f33088d7b05d096b88205 Mon Sep 17 00:00:00 2001 From: Ahmed Hussein <50450311+amahussein@users.noreply.github.com> Date: Wed, 27 Nov 2024 09:08:43 -0600 Subject: [PATCH 12/22] Sort Qual execs report by sqlId and nodeId (#1436) * Sort Qual execs report by sqlId and nodeId Signed-off-by: Ahmed Hussein (amahussein) * handling children execs smarter way Signed-off-by: Ahmed Hussein (amahussein) --------- Signed-off-by: Ahmed Hussein (amahussein) --- .../tool/qualification/QualOutputWriter.scala | 80 +++++++++---------- .../tool/qualification/Qualification.scala | 2 +- 2 files changed, 38 insertions(+), 44 deletions(-) diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/QualOutputWriter.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/QualOutputWriter.scala index d0193ca8e..ed101d820 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/QualOutputWriter.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/QualOutputWriter.scala @@ -255,17 +255,50 @@ class QualOutputWriter(outputDir: String, reportReadSchema: Boolean, } } - def writeExecReport(sums: Seq[QualificationSummaryInfo], order: String) : Unit = { + def writeExecReport(sums: Seq[QualificationSummaryInfo]) : Unit = { val csvFileWriter = new ToolTextFileWriter(outputDir, s"${QualOutputWriter.LOGFILE_NAME}_execs.csv", "Plan Exec Info", hadoopConf) try { - val headersAndSizes = QualOutputWriter.getDetailedExecsHeaderStrings csvFileWriter.write(QualOutputWriter.constructDetailedHeader( QualOutputWriter.getDetailedExecsHeaderStrings, ",", false)) + val delimiter = "," + val booleanTrue = "true" + val booleanFalse = "false" + val zeroDurationStr = "0" sums.foreach { sumInfo => - val appRows = QualOutputWriter.constructExecsInfo(sumInfo, headersAndSizes, ",", false) - appRows.foreach(csvFileWriter.write(_)) + val appIDCSVStr = StringUtils.reformatCSVString(sumInfo.appId) + sumInfo.planInfo.foreach { pInfo => + val execInfos = pInfo.execInfo.flatMap { eInfo => + eInfo.children.getOrElse(Seq.empty) :+ eInfo + }.sortBy(eInfo => eInfo.nodeId) + val sqlIDStr = pInfo.sqlID.toString + val rows = execInfos.map { info => + val (childrenExecsStr, nodeIdsStr) = if (info.children.isDefined) { + (StringUtils.reformatCSVString( + info.children.get.map(_.exec).mkString(":")), + StringUtils.reformatCSVString( + info.children.get.map(_.nodeId).mkString(":"))) + } else { + ("", "") + } + Seq(appIDCSVStr, sqlIDStr, StringUtils.reformatCSVString(info.exec), + StringUtils.reformatCSVString(info.expr), + if (info.duration.isDefined) info.duration.get.toString else zeroDurationStr, + info.nodeId.toString, + if (info.isSupported) booleanTrue else booleanFalse, + StringUtils.reformatCSVString(info.stages.mkString(":")), + childrenExecsStr, + nodeIdsStr, + if (info.shouldRemove) booleanTrue else booleanFalse, + if (info.shouldIgnore) booleanTrue else booleanFalse, + StringUtils.reformatCSVString(info.getOpAction.toString) + ).mkString(delimiter) + } + if (rows.nonEmpty) { + csvFileWriter.write(s"${rows.mkString("\n")}\n") + } + } } } finally { csvFileWriter.close() @@ -941,33 +974,6 @@ object QualOutputWriter { detailedHeadersAndFields } - private def constructExecInfoBuffer( - info: ExecInfo, - appId: String, - delimiter: String, - prettyPrint: Boolean, - headersAndSizes: LinkedHashMap[String, Int], - reformatCSV: Boolean = true): String = { - val reformatCSVFunc = getReformatCSVFunc(reformatCSV) - val data = ListBuffer[(String, Int)]( - reformatCSVFunc(appId) -> headersAndSizes(APP_ID_STR), - info.sqlID.toString -> headersAndSizes(SQL_ID_STR), - reformatCSVFunc(info.exec) -> headersAndSizes(EXEC_STR), - reformatCSVFunc(info.expr) -> headersAndSizes(EXEC_STR), - info.duration.getOrElse(0).toString -> headersAndSizes(EXEC_DURATION), - info.nodeId.toString -> headersAndSizes(EXEC_NODEID), - info.isSupported.toString -> headersAndSizes(EXEC_IS_SUPPORTED), - reformatCSVFunc(info.stages.mkString(":")) -> headersAndSizes(EXEC_STAGES), - reformatCSVFunc(info.children.getOrElse(Seq.empty).map(_.exec).mkString(":")) -> - headersAndSizes(EXEC_CHILDREN), - reformatCSVFunc(info.children.getOrElse(Seq.empty).map(_.nodeId).mkString(":")) -> - headersAndSizes(EXEC_CHILDREN_NODE_IDS), - info.shouldRemove.toString -> headersAndSizes(EXEC_SHOULD_REMOVE), - info.shouldIgnore.toString -> headersAndSizes(EXEC_SHOULD_IGNORE), - reformatCSVFunc(info.getOpAction.toString) -> headersAndSizes(EXEC_ACTION) - ) - constructOutputRow(data, delimiter, prettyPrint) - } private def getDetailedStagesHeaderStrings: LinkedHashMap[String, Int] = { val detailedHeadersAndFields = LinkedHashMap[String, Int]( @@ -1077,18 +1083,6 @@ object QualOutputWriter { }.toSet } - private def constructExecsInfo( - sumInfo: QualificationSummaryInfo, - headersAndSizes: LinkedHashMap[String, Int], - delimiter: String, - prettyPrint: Boolean): Set[String] = { - // No need to visit the execInfo children because the result returned from - // "getAllExecsFromPlan" is already flattened - getAllExecsFromPlan(sumInfo.planInfo).collect { case info => - constructExecInfoBuffer(info, sumInfo.appId, delimiter, prettyPrint, headersAndSizes) - } - } - def createFormattedQualSummaryInfo( appInfo: QualificationSummaryInfo, delimiter: String = TEXT_DELIMITER) : FormattedQualificationSummaryInfo = { diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/Qualification.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/Qualification.scala index c50464233..49d70b80e 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/Qualification.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/Qualification.scala @@ -252,7 +252,7 @@ class Qualification(outputPath: String, numRows: Int, hadoopConf: Configuration, qWriter.writePerSqlTextReport(allAppsSum, numRows, maxSQLDescLength) qWriter.writePerSqlCSVReport(allAppsSum, maxSQLDescLength) } - qWriter.writeExecReport(allAppsSum, order) + qWriter.writeExecReport(allAppsSum) qWriter.writeStageReport(allAppsSum, order) qWriter.writeUnsupportedOpsSummaryCSVReport(allAppsSum) val appStatusResult = generateStatusResults(appStatusReporter.asScala.values.toSeq) From 9f519d2329333b6242f58ca3882f10af52bff77b Mon Sep 17 00:00:00 2001 From: Cindy Jiang <47068112+cindyyuanjiang@users.noreply.github.com> Date: Wed, 27 Nov 2024 11:25:38 -0800 Subject: [PATCH 13/22] fix index out of bound bug (#1439) Signed-off-by: cindyyuanjiang --- .../tool/analysis/AppSparkMetricsAnalyzer.scala | 15 ++++++++------- 1 file changed, 8 insertions(+), 7 deletions(-) diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AppSparkMetricsAnalyzer.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AppSparkMetricsAnalyzer.scala index 69dcbb787..33194644e 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AppSparkMetricsAnalyzer.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AppSparkMetricsAnalyzer.scala @@ -498,15 +498,16 @@ object AppSparkMetricsAnalyzer { def getStatistics(arr: Iterable[Long]): StatisticsMetrics = { if (arr.isEmpty) { StatisticsMetrics(0L, 0L, 0L, 0L) - } - val sortedArr = arr.toSeq.sorted - val len = sortedArr.size - val med = if (len % 2 == 0) { - (sortedArr(len / 2) + sortedArr(len / 2 - 1)) / 2 } else { - sortedArr(len / 2) + val sortedArr = arr.toSeq.sorted + val len = sortedArr.size + val med = if (len % 2 == 0) { + (sortedArr(len / 2) + sortedArr(len / 2 - 1)) / 2 + } else { + sortedArr(len / 2) + } + StatisticsMetrics(sortedArr.head, med, sortedArr(len - 1), sortedArr.sum) } - StatisticsMetrics(sortedArr.head, med, sortedArr(len - 1), sortedArr.sum) } def maxWithEmptyHandling(arr: Iterable[Long]): Long = { From fc49eb6af1f864095fa9c585ec9ccc6ec384c16f Mon Sep 17 00:00:00 2001 From: Lee Yang Date: Wed, 27 Nov 2024 14:58:51 -0800 Subject: [PATCH 14/22] update models for latest code and dataset JSON (#1442) Signed-off-by: Lee Yang --- .../qualx/models/xgboost/combined.cfg | 2 +- .../qualx/models/xgboost/combined.json | 2 +- .../qualx/models/xgboost/combined.metrics | 176 +++++++------- .../qualx/models/xgboost/databricks-aws.json | 2 +- .../qualx/models/xgboost/databricks-azure.cfg | 2 +- .../models/xgboost/databricks-azure.json | 2 +- .../models/xgboost/databricks-azure.metrics | 204 ++++++++--------- .../xgboost/databricks-azure_photon.cfg | 2 +- .../xgboost/databricks-azure_photon.json | 2 +- .../xgboost/databricks-azure_photon.metrics | 212 ++++++++--------- .../qualx/models/xgboost/dataproc.cfg | 2 +- .../qualx/models/xgboost/dataproc.json | 2 +- .../qualx/models/xgboost/dataproc.metrics | 214 +++++++++--------- .../resources/qualx/models/xgboost/emr.json | 2 +- .../qualx/models/xgboost/emr.metrics | 118 +++++----- .../resources/qualx/models/xgboost/onprem.cfg | 2 +- .../qualx/models/xgboost/onprem.json | 2 +- .../qualx/models/xgboost/onprem.metrics | 212 ++++++++--------- 18 files changed, 580 insertions(+), 580 deletions(-) diff --git a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.cfg b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.cfg index 9e52614e1..f84abdfcb 100644 --- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.cfg +++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.cfg @@ -1 +1 @@ -{"learner":{"generic_param":{"device":"cpu","fail_on_invalid_gpu_id":"0","n_jobs":"0","nthread":"0","random_state":"0","seed":"0","seed_per_iteration":"0","validate_parameters":"1"},"gradient_booster":{"gbtree_model_param":{"num_parallel_tree":"1","num_trees":"93"},"gbtree_train_param":{"process_type":"default","tree_method":"auto","updater":"grow_quantile_histmaker","updater_seq":"grow_quantile_histmaker"},"name":"gbtree","specified_updater":false,"tree_train_param":{"alpha":"0","cache_opt":"1","colsample_bylevel":"1","colsample_bynode":"1","colsample_bytree":"1","eta":"0.0499666668","gamma":"0.00690161297","grow_policy":"depthwise","interaction_constraints":"","lambda":"1","learning_rate":"0.0499666668","max_bin":"256","max_cat_threshold":"64","max_cat_to_onehot":"4","max_delta_step":"0","max_depth":"9","max_leaves":"0","min_child_weight":"4","min_split_loss":"0.00690161297","monotone_constraints":"()","refresh_leaf":"1","reg_alpha":"0","reg_lambda":"1","sampling_method":"uniform","sketch_ratio":"2","sparse_threshold":"0.20000000000000001","subsample":"0.768415093"},"updater":[{"hist_train_param":{"debug_synchronize":"0","max_cached_hist_node":"65536"},"name":"grow_quantile_histmaker"}]},"learner_model_param":{"base_score":"5.681664E-1","boost_from_average":"1","num_class":"0","num_feature":"108","num_target":"1"},"learner_train_param":{"booster":"gbtree","disable_default_eval_metric":"0","multi_strategy":"one_output_per_tree","objective":"reg:squarederror"},"metrics":[{"name":"mae"},{"name":"mape"}],"objective":{"name":"reg:squarederror","reg_loss_param":{"scale_pos_weight":"1"}}},"version":[2,0,3]} \ No newline at end of file +{"learner":{"generic_param":{"device":"cpu","fail_on_invalid_gpu_id":"0","n_jobs":"0","nthread":"0","random_state":"0","seed":"0","seed_per_iteration":"0","validate_parameters":"1"},"gradient_booster":{"gbtree_model_param":{"num_parallel_tree":"1","num_trees":"97"},"gbtree_train_param":{"process_type":"default","tree_method":"auto","updater":"grow_quantile_histmaker","updater_seq":"grow_quantile_histmaker"},"name":"gbtree","specified_updater":false,"tree_train_param":{"alpha":"0","cache_opt":"1","colsample_bylevel":"1","colsample_bynode":"1","colsample_bytree":"1","eta":"0.0478905365","gamma":"0.100665279","grow_policy":"depthwise","interaction_constraints":"","lambda":"1","learning_rate":"0.0478905365","max_bin":"256","max_cat_threshold":"64","max_cat_to_onehot":"4","max_delta_step":"0","max_depth":"7","max_leaves":"0","min_child_weight":"2","min_split_loss":"0.100665279","monotone_constraints":"()","refresh_leaf":"1","reg_alpha":"0","reg_lambda":"1","sampling_method":"uniform","sketch_ratio":"2","sparse_threshold":"0.20000000000000001","subsample":"0.799700022"},"updater":[{"hist_train_param":{"debug_synchronize":"0","max_cached_hist_node":"65536"},"name":"grow_quantile_histmaker"}]},"learner_model_param":{"base_score":"5.681664E-1","boost_from_average":"1","num_class":"0","num_feature":"108","num_target":"1"},"learner_train_param":{"booster":"gbtree","disable_default_eval_metric":"0","multi_strategy":"one_output_per_tree","objective":"reg:squarederror"},"metrics":[{"name":"mae"},{"name":"mape"}],"objective":{"name":"reg:squarederror","reg_loss_param":{"scale_pos_weight":"1"}}},"version":[2,0,3]} \ No newline at end of file diff --git a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.json b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.json index 630bdbde5..d08771d24 100644 --- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.json +++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.json @@ -1 +1 @@ -{"learner":{"attributes":{},"feature_names":["numTasks_sum","duration_sum","duration_max","duration_min","duration_mean","input_recordsRead_sum","output_recordsWritten_sum","peakExecutionMemory_max","resultSerializationTime_sum","resultSize_max","sr_localBlocksFetched_sum","sr_remoteBlocksFetched_sum","sw_recordsWritten_sum","sqlOp_Exchange","sqlOp_Execute InsertIntoHadoopFsRelationCommand","sqlOp_Scan parquet 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\ No newline at end of file diff --git a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.metrics b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.metrics index 0c51ba152..4895b8807 100644 --- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.metrics +++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.metrics @@ -1,89 +1,89 @@ ,feature,shap_value,mean,std,min,25%,50%,75%,max -0,maxOnHeapMem,0.28238225,12891675333.097458,7443156274.854311,455501414.0,8974132838.0,10119177830.0,10119177830.0,26104509235.0 -1,duration_max,0.12174313,19727.637005649718,132756.56647030968,15.0,1000.75,2626.5,6606.5,3183955.0 -2,executorCPUTime_mean,0.10378177,1600.0121232217436,8490.83160303521,3.875,196.08367473240125,438.1275815373426,1135.2854603729604,227947.84615384616 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-107,sqlOp_WindowSort,0.0,0.000847457627118644,0.029102898519035535,0.0,0.0,0.0,0.0,1.0 +107,sqlOp_WindowSort,0.0,0.000847457627118644,0.02910289851903554,0.0,0.0,0.0,0.0,1.0 diff --git a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-aws.json b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-aws.json index 0b1f885b3..bfe96460c 100644 --- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-aws.json +++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-aws.json @@ -1 +1 @@ -{"learner":{"attributes":{},"feature_names":["numTasks_sum","duration_sum","duration_max","duration_min","duration_mean","input_recordsRead_sum","output_recordsWritten_sum","peakExecutionMemory_max","resultSerializationTime_sum","resultSize_max","sr_localBlocksFetched_sum","sr_remoteBlocksFetched_sum","sw_recordsWritten_sum","sqlOp_ColumnarToRow","sqlOp_Exchange","sqlOp_Execute 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\ No newline at end of file diff --git a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure.metrics b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure.metrics index d5168e636..27abdd04d 100644 --- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure.metrics +++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure.metrics @@ -1,109 +1,109 @@ ,feature,shap_value,mean,std,min,25%,50%,75%,max -0,executorCPUTime_mean,0.12785757,3083.661435888062,5116.536518124452,79.01805054151625,529.5195832704212,1391.1708930540242,3098.8835876649596,46123.548214285714 -1,sr_remoteBytesReadRatio,0.092217326,0.821447639429395,1.190295307104319,4.361993847958805e-07,0.004681915012233263,0.2507003788881129,1.3747557349907953,9.945049508262114 -2,sw_recordsWritten_sum,0.08674005,1374410117.7790263,3387308853.036538,200.0,1055515.5,70762368.0,1083955333.0,32214909337.0 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a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure_photon.cfg b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure_photon.cfg index ea2374289..24c179963 100644 --- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure_photon.cfg +++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure_photon.cfg @@ -1 +1 @@ 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\ No newline at end of file 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\ No newline at end of file diff --git a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure_photon.json b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure_photon.json index ff33444cb..1aa1b696d 100644 --- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure_photon.json +++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure_photon.json @@ -1 +1 @@ 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\ No newline at end of file diff --git a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure_photon.metrics b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure_photon.metrics index 81bf8eac2..02fd5b915 100644 --- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure_photon.metrics +++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure_photon.metrics @@ -1,109 +1,109 @@ ,feature,shap_value,mean,std,min,25%,50%,75%,max -0,sw_bytesWrittenRatio,0.0832446,0.5919399675594721,1.476025676540793,3.811915686539279e-07,0.004988403730711104,0.15715677052090143,0.6968701139378873,19.10476372587304 -1,input_bytesRead_mean,0.06974004,48660306.00109597,49428056.486782335,466150.2392857143,9457240.909980843,31206626.71954965,76555115.52221651,240185411.32144082 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b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/dataproc.cfg index 3aa9ab781..4eaa3245f 100644 --- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/dataproc.cfg +++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/dataproc.cfg @@ -1 +1 @@ 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\ No newline at end of file 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\ No newline at end of file diff --git a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/dataproc.metrics b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/dataproc.metrics index d443a3fa7..5f5bdac0d 100644 --- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/dataproc.metrics +++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/dataproc.metrics @@ -1,109 +1,109 @@ ,feature,shap_value,mean,std,min,25%,50%,75%,max -0,duration_max,0.24739769,82414.25463743677,311681.84687962633,1504.0,4702.0,7190.0,20850.0,3183955.0 -1,duration_sum,0.07175633,16930121.96627319,45073353.38047576,3197.0,1082442.0,2678990.0,10368109.0,515693115.0 -2,executorCPUTime_mean,0.06844651,2722.177687148267,7012.88983905512,23.339985149433822,585.2242380261248,1063.8777813608513,2163.7598204264873,68323.01515151515 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b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/onprem.cfg @@ -1 +1 @@ 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\ No newline at end of file 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JDBCRelation,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -78,sqlOp_Execute InsertIntoHadoopFsRelationCommand,0.0,0.13009198423127463,0.3365151758705616,0.0,0.0,0.0,0.0,1.0 -79,maxOffHeapMem,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +0,duration_max,0.3195818,6139.4632063074905,32138.962204191022,15.0,560.0,1136.5,3113.0,515161.0 +1,scan_bw,0.17451431,1593713.4898735192,2294166.855457363,0.0,174981.0170488308,655006.879324951,2101650.4235552456,17385294.707427993 +2,executorCPUTime_mean,0.06829664,1343.4213374053284,11697.68424064774,3.875,163.23010869565218,315.8137480798771,686.9930131090191,227947.84615384616 +3,scan_time,0.026964596,46345.203022339025,243193.36454642916,0.0,473.5,2177.5,10481.0,3127801.0 +4,executorDeserializeTime_mean,0.025398523,6.00370659180027,19.71922884656477,0.04395604395604396,2.2201527924130664,3.6647940074906367,5.147844471947195,475.6 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+98,sr_remoteBytesReadToDiskRatio,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +99,sr_totalBytesReadRatio,0.0,0.7902416781930374,1.431541673913999,0.0,0.004238274599405685,0.17196742660015743,1.1388709718278844,16.779651636748564 +100,sr_remoteBytesRead_mean,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +101,sr_remoteBytesReadToDisk_mean,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +102,sr_totalBytesRead_mean,0.0,3984381.8321779394,8966196.568703005,0.0,9715.138598022106,441049.2350230415,3399921.6142857145,104601898.28278689 +103,platform_onprem,0.0,1.0,0.0,1.0,1.0,1.0,1.0,1.0 +104,platform_databricks-aws,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +105,platform_databricks-azure,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +106,platform_dataproc,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 107,sqlOp_WindowSort,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 From fb725201e1f812d6b29d5400e484aa6b739bf259 Mon Sep 17 00:00:00 2001 From: Lee Yang Date: Tue, 3 Dec 2024 10:21:44 -0800 Subject: [PATCH 15/22] More flexible regexes; fix default split function (#1443) Signed-off-by: Lee Yang --- user_tools/src/spark_rapids_tools/tools/qualx/model.py | 2 +- .../src/spark_rapids_tools/tools/qualx/preprocess.py | 10 +++++++--- user_tools/src/spark_rapids_tools/tools/qualx/util.py | 6 +++--- 3 files changed, 11 insertions(+), 7 deletions(-) diff --git a/user_tools/src/spark_rapids_tools/tools/qualx/model.py b/user_tools/src/spark_rapids_tools/tools/qualx/model.py index 9f9470a1f..4491545f2 100644 --- a/user_tools/src/spark_rapids_tools/tools/qualx/model.py +++ b/user_tools/src/spark_rapids_tools/tools/qualx/model.py @@ -347,7 +347,7 @@ def extract_model_features( default_df = default_df.loc[~default_df.appName.str.startswith(f'{ds_name}:')] modified_default_df = default_split_fn(default_df) if modified_default_df.index.equals(default_df.index): - cpu_aug_tbl.update(default_df) + cpu_aug_tbl.update(modified_default_df) cpu_aug_tbl.astype(df_schema) else: raise ValueError('Default split_function unexpectedly modified row indices.') diff --git a/user_tools/src/spark_rapids_tools/tools/qualx/preprocess.py b/user_tools/src/spark_rapids_tools/tools/qualx/preprocess.py index d203bbc7f..320615b7c 100644 --- a/user_tools/src/spark_rapids_tools/tools/qualx/preprocess.py +++ b/user_tools/src/spark_rapids_tools/tools/qualx/preprocess.py @@ -30,7 +30,9 @@ get_logger, get_dataset_platforms, load_plugin, - run_profiler_tool, log_fallback, + log_fallback, + run_profiler_tool, + RegexPattern ) PREPROCESSED_FILE = 'preprocessed.parquet' @@ -269,10 +271,12 @@ def infer_app_meta(eventlogs: List[str]) -> Mapping[str, Mapping]: app_meta_inner = {} for e in eventlog_list: parts = Path(e).parts - app_id_inner = parts[-1] + app_id_part = parts[-1] + match = RegexPattern.app_id.search(app_id_part) + app_id = match.group() if match else app_id_part run_type = parts[-2].upper() job_name = parts[-4] - app_meta_inner[app_id_inner] = { + app_meta_inner[app_id] = { 'jobName': job_name, 'runType': run_type, 'scaleFactor': 1, diff --git a/user_tools/src/spark_rapids_tools/tools/qualx/util.py b/user_tools/src/spark_rapids_tools/tools/qualx/util.py index 831721ff3..9bb8ee1a5 100644 --- a/user_tools/src/spark_rapids_tools/tools/qualx/util.py +++ b/user_tools/src/spark_rapids_tools/tools/qualx/util.py @@ -45,9 +45,9 @@ def get_logger(name: str) -> logging.Logger: @dataclass class RegexPattern: - app_id = re.compile(r'^app.*[_-][0-9]+[_-][0-9]+$') - profile = re.compile(r'^prof_[0-9]+_[0-9a-zA-Z]+$') - qual_tool = re.compile(r'^qual_[0-9]+_[0-9a-zA-Z]+$') + app_id = re.compile(r'app.*[_-][0-9]+[_-][0-9]+') + profile = re.compile(r'prof_[0-9]+_[0-9a-zA-Z]+') + qual_tool = re.compile(r'qual_[0-9]+_[0-9a-zA-Z]+') rapids_profile = re.compile(r'rapids_4_spark_profile') rapids_qual = re.compile(r'rapids_4_spark_qualification_output') qual_tool_metrics = re.compile(r'raw_metrics') From 0eb5bf51fe99b6d7de3eeb234b71c97ad335d957 Mon Sep 17 00:00:00 2001 From: Ahmed Hussein <50450311+amahussein@users.noreply.github.com> Date: Tue, 3 Dec 2024 12:53:14 -0600 Subject: [PATCH 16/22] Fix missing exec-to-stageId mapping in Qual tool (#1437) * Fix missing exec-to-stageId mapping in Qual tool Fixes #1156 This adds logic to walk the SparkGraph in order to assign execs to stages. For nodes that have no AccumIDs, the clusterization processes relies on adjacent nodes. --------- Signed-off-by: Ahmed Hussein (amahussein) --- .../tool/analysis/AppSQLPlanAnalyzer.scala | 4 +- .../tool/planparser/SQLPlanParser.scala | 27 +- .../planparser/WholeStageExecParser.scala | 24 +- .../photon/PhotonStageExecParser.scala | 5 +- .../rapids/tool/AccumToStageRetriever.scala | 31 ++ .../spark/sql/rapids/tool/AppBase.scala | 8 +- .../sql/rapids/tool/util/ToolsPlanGraph.scala | 371 +++++++++++++++++- .../complex_dec_expectation.csv | 2 +- .../read_dsv1_expectation.csv | 2 +- .../read_dsv2_expectation.csv | 2 +- .../truncated_1_end_expectation.csv | 2 +- .../tool/planparser/BasePlanParserSuite.scala | 23 ++ .../tool/planparser/SqlPlanParserSuite.scala | 79 +++- 13 files changed, 539 insertions(+), 41 deletions(-) create mode 100644 core/src/main/scala/org/apache/spark/sql/rapids/tool/AccumToStageRetriever.scala diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AppSQLPlanAnalyzer.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AppSQLPlanAnalyzer.scala index 7e17767b9..9580aa470 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AppSQLPlanAnalyzer.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AppSQLPlanAnalyzer.scala @@ -18,7 +18,6 @@ package com.nvidia.spark.rapids.tool.analysis import scala.collection.mutable.{AbstractSet, ArrayBuffer, HashMap, LinkedHashSet} -import com.nvidia.spark.rapids.tool.planparser.SQLPlanParser import com.nvidia.spark.rapids.tool.profiling.{AccumProfileResults, SQLAccumProfileResults, SQLMetricInfoCase, SQLStageInfoProfileResult, UnsupportedSQLPlan, WholeStageCodeGenResults} import com.nvidia.spark.rapids.tool.qualification.QualSQLPlanAnalyzer @@ -88,7 +87,8 @@ class AppSQLPlanAnalyzer(app: AppBase, appIndex: Int) extends AppAnalysisBase(ap // Maps stages to operators by checking for non-zero intersection // between nodeMetrics and stageAccumulateIDs val nodeIdToStage = planGraph.allNodes.map { node => - val mappedStages = SQLPlanParser.getStagesInSQLNode(node, app) + val nodeAccums = node.metrics.map(_.accumulatorId) + val mappedStages = app.getStageIDsFromAccumIds(nodeAccums) ((sqlId, node.id), mappedStages) }.toMap sqlPlanNodeIdToStageIds ++= nodeIdToStage diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SQLPlanParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SQLPlanParser.scala index 1b8d63a5f..ad2634c41 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SQLPlanParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SQLPlanParser.scala @@ -26,7 +26,6 @@ import com.nvidia.spark.rapids.tool.qualification.PluginTypeChecker import org.apache.spark.internal.Logging import org.apache.spark.sql.execution.SparkPlanInfo -//import org.apache.spark.sql.execution.joins.CartesianProductExec import org.apache.spark.sql.execution.ui.{SparkPlanGraph, SparkPlanGraphCluster, SparkPlanGraphNode} import org.apache.spark.sql.rapids.tool.{AppBase, BuildSide, ExecHelper, JoinType, RDDCheckHelper, ToolUtils, UnsupportedExpr} import org.apache.spark.sql.rapids.tool.util.ToolsPlanGraph @@ -433,22 +432,19 @@ object SQLPlanParser extends Logging { sqlDesc: String, checker: PluginTypeChecker, app: AppBase): PlanInfo = { - val planGraph = ToolsPlanGraph(planInfo) + val toolsGraph = ToolsPlanGraph.createGraphWithStageClusters(planInfo, app) + // Find all the node graphs that should be excluded and send it to the parsePlanNode - val excludedNodes = buildSkippedReusedNodesForPlan(planGraph) + val excludedNodes = buildSkippedReusedNodesForPlan(toolsGraph.sparkGraph) // we want the sub-graph nodes to be inside of the wholeStageCodeGen so use nodes // vs allNodes - val execInfos = planGraph.nodes.flatMap { node => - parsePlanNode(node, sqlID, checker, app, reusedNodeIds = excludedNodes) + val execInfos = toolsGraph.nodes.flatMap { node => + parsePlanNode(node, sqlID, checker, app, reusedNodeIds = excludedNodes, + nodeIdToStagesFunc = toolsGraph.getNodeStageClusters) } PlanInfo(appID, sqlID, sqlDesc, execInfos) } - def getStagesInSQLNode(node: SparkPlanGraphNode, app: AppBase): Set[Int] = { - val nodeAccums = node.metrics.map(_.accumulatorId) - nodeAccums.flatMap(app.accumManager.getAccStageIds).toSet - } - // Set containing execs that refers to other expressions. We need this to be a list to allow // appending more execs in teh future as necessary. // Note that Spark graph may create duplicate nodes when any of the following execs exists. @@ -541,7 +537,8 @@ object SQLPlanParser extends Logging { sqlID: Long, checker: PluginTypeChecker, app: AppBase, - reusedNodeIds: Set[Long] + reusedNodeIds: Set[Long], + nodeIdToStagesFunc: Long => Set[Int] ): Seq[ExecInfo] = { // Avoid counting duplicate nodes. We mark them as shouldRemove to neutralize their impact on // speedups. @@ -560,9 +557,11 @@ object SQLPlanParser extends Logging { // For WholeStageCodegen clusters, use PhotonStageExecParser if the cluster is of Photon type. // Else, fall back to WholeStageExecParser to parse the cluster. case photonCluster: PhotonSparkPlanGraphCluster => - PhotonStageExecParser(photonCluster, checker, sqlID, app, reusedNodeIds).parse + PhotonStageExecParser(photonCluster, checker, sqlID, app, reusedNodeIds, + nodeIdToStagesFunc = nodeIdToStagesFunc).parse case cluster: SparkPlanGraphCluster => - WholeStageExecParser(cluster, checker, sqlID, app, reusedNodeIds).parse + WholeStageExecParser(cluster, checker, sqlID, app, reusedNodeIds, + nodeIdToStagesFunc = nodeIdToStagesFunc).parse case _ => // For individual nodes, use PhotonPlanParser if the node is of Photon type. // Else, fall back to the Spark node parsing logic to parse the node. @@ -587,7 +586,7 @@ object SQLPlanParser extends Logging { ExecInfo(node, sqlID, normalizedNodeName, expr = "", 1, duration = None, node.id, isSupported = false, None) } - val stagesInNode = getStagesInSQLNode(node, app) + val stagesInNode = nodeIdToStagesFunc(node.id) execInfo.setStages(stagesInNode) // shouldRemove is set to true if the exec is a member of "execsToBeRemoved" or if the node // is a duplicate diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/WholeStageExecParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/WholeStageExecParser.scala index 19eb46a52..cdef3b225 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/WholeStageExecParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/WholeStageExecParser.scala @@ -27,7 +27,8 @@ abstract class WholeStageExecParserBase( checker: PluginTypeChecker, sqlID: Long, app: AppBase, - reusedNodeIds: Set[Long]) extends Logging { + reusedNodeIds: Set[Long], + nodeIdToStagesFunc: Long => Set[Int]) extends Logging { val fullExecName = "WholeStageCodegenExec" @@ -38,16 +39,15 @@ abstract class WholeStageExecParserBase( // Perhaps take the max of those in Stage? val accumId = node.metrics.find(_.name == "duration").map(_.accumulatorId) val maxDuration = SQLPlanParser.getTotalDuration(accumId, app) - val stagesInNode = SQLPlanParser.getStagesInSQLNode(node, app) + val stagesInNode = nodeIdToStagesFunc.apply(node.id) // We could skip the entire wholeStage if it is duplicate; but we will lose the information of // the children nodes. val isDupNode = reusedNodeIds.contains(node.id) val childNodes = node.nodes.flatMap { c => - SQLPlanParser.parsePlanNode(c, sqlID, checker, app, reusedNodeIds) + // Pass the nodeToStagesFunc to the child nodes so they can get the stages. + SQLPlanParser.parsePlanNode(c, sqlID, checker, app, reusedNodeIds, + nodeIdToStagesFunc = nodeIdToStagesFunc) } - // For the childNodes, we need to append the stages. Otherwise, nodes without metrics won't be - // assigned to stage - childNodes.foreach(_.appendToStages(stagesInNode)) // if any of the execs in WholeStageCodegen supported mark this entire thing as supported val anySupported = childNodes.exists(_.isSupported == true) val unSupportedExprsArray = @@ -55,14 +55,11 @@ abstract class WholeStageExecParserBase( // average speedup across the execs in the WholeStageCodegen for now val supportedChildren = childNodes.filterNot(_.shouldRemove) val avSpeedupFactor = SQLPlanParser.averageSpeedup(supportedChildren.map(_.speedupFactor)) - // can't rely on the wholeStagecodeGen having a stage if children do so aggregate them together - // for now - val allStagesIncludingChildren = childNodes.flatMap(_.stages).toSet ++ stagesInNode.toSet - // Finally, the node should be marked as shouldRemove when all the children of the + // The node should be marked as shouldRemove when all the children of the // wholeStageCodeGen are marked as shouldRemove. val removeNode = isDupNode || childNodes.forall(_.shouldRemove) val execInfo = ExecInfo(node, sqlID, node.name, node.name, avSpeedupFactor, maxDuration, - node.id, anySupported, Some(childNodes), allStagesIncludingChildren, + node.id, anySupported, Some(childNodes), stagesInNode, shouldRemove = removeNode, unsupportedExprs = unSupportedExprsArray) Seq(execInfo) } @@ -73,5 +70,6 @@ case class WholeStageExecParser( checker: PluginTypeChecker, sqlID: Long, app: AppBase, - reusedNodeIds: Set[Long]) - extends WholeStageExecParserBase(node, checker, sqlID, app, reusedNodeIds) + reusedNodeIds: Set[Long], + nodeIdToStagesFunc: Long => Set[Int]) + extends WholeStageExecParserBase(node, checker, sqlID, app, reusedNodeIds, nodeIdToStagesFunc) diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/photon/PhotonStageExecParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/photon/PhotonStageExecParser.scala index d49192d27..ceb59e712 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/photon/PhotonStageExecParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/photon/PhotonStageExecParser.scala @@ -35,5 +35,6 @@ case class PhotonStageExecParser( checker: PluginTypeChecker, sqlID: Long, app: AppBase, - reusedNodeIds: Set[Long]) - extends WholeStageExecParserBase(node, checker, sqlID, app, reusedNodeIds) + reusedNodeIds: Set[Long], + nodeIdToStagesFunc: Long => Set[Int]) + extends WholeStageExecParserBase(node, checker, sqlID, app, reusedNodeIds, nodeIdToStagesFunc) diff --git a/core/src/main/scala/org/apache/spark/sql/rapids/tool/AccumToStageRetriever.scala b/core/src/main/scala/org/apache/spark/sql/rapids/tool/AccumToStageRetriever.scala new file mode 100644 index 000000000..7da118a0e --- /dev/null +++ b/core/src/main/scala/org/apache/spark/sql/rapids/tool/AccumToStageRetriever.scala @@ -0,0 +1,31 @@ +/* + * Copyright (c) 2024, NVIDIA CORPORATION. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.rapids.tool + +/** + * Trait that defines the interface for retrieving stage IDs from accumulables. + * This is used to map accumulables to stages. We use it as interface in order to allow to separate + * the logic and use dummy different implementations and mocks for testing when needed. + */ +trait AccumToStageRetriever { + /** + * Given a sequence of accumIds, return a set of stage IDs that are associated with the + * accumIds. Note that this method can only be called after the accumulables have been fully + * processed. + */ + def getStageIDsFromAccumIds(accumIds: Seq[Long]): Set[Int] +} diff --git a/core/src/main/scala/org/apache/spark/sql/rapids/tool/AppBase.scala b/core/src/main/scala/org/apache/spark/sql/rapids/tool/AppBase.scala index e3313b832..f8d4d7703 100644 --- a/core/src/main/scala/org/apache/spark/sql/rapids/tool/AppBase.scala +++ b/core/src/main/scala/org/apache/spark/sql/rapids/tool/AppBase.scala @@ -42,7 +42,9 @@ import org.apache.spark.util.Utils abstract class AppBase( val eventLogInfo: Option[EventLogInfo], - val hadoopConf: Option[Configuration]) extends Logging with ClusterTagPropHandler { + val hadoopConf: Option[Configuration]) extends Logging + with ClusterTagPropHandler + with AccumToStageRetriever { var appMetaData: Option[AppMetaData] = None @@ -105,6 +107,10 @@ abstract class AppBase( def sqlPlans: immutable.Map[Long, SparkPlanInfo] = sqlManager.getPlanInfos + def getStageIDsFromAccumIds(accumIds: Seq[Long]): Set[Int] = { + accumIds.flatMap(accumManager.getAccStageIds).toSet + } + // Returns the String value of the eventlog or empty if it is not defined. Note that the eventlog // won't be defined for running applications def getEventLogPath: String = { diff --git a/core/src/main/scala/org/apache/spark/sql/rapids/tool/util/ToolsPlanGraph.scala b/core/src/main/scala/org/apache/spark/sql/rapids/tool/util/ToolsPlanGraph.scala index 6d6187d80..c9a1f1d3f 100644 --- a/core/src/main/scala/org/apache/spark/sql/rapids/tool/util/ToolsPlanGraph.scala +++ b/core/src/main/scala/org/apache/spark/sql/rapids/tool/util/ToolsPlanGraph.scala @@ -16,16 +16,375 @@ package org.apache.spark.sql.rapids.tool.util -import com.nvidia.spark.rapids.tool.planparser.DatabricksParseHelper import java.util.concurrent.atomic.AtomicLong + import scala.collection.mutable +import com.nvidia.spark.rapids.tool.planparser.DatabricksParseHelper + import org.apache.spark.sql.execution.SparkPlanInfo -import org.apache.spark.sql.execution.ui.{SparkPlanGraph, SparkPlanGraphCluster, SparkPlanGraphEdge, SparkPlanGraphNode, SQLPlanMetric} +import org.apache.spark.sql.execution.ui._ +import org.apache.spark.sql.rapids.tool.AccumToStageRetriever import org.apache.spark.sql.rapids.tool.store.AccumNameRef import org.apache.spark.sql.rapids.tool.util.plangraph.PlanGraphTransformer import org.apache.spark.sql.rapids.tool.util.stubs.{GraphReflectionAPI, GraphReflectionAPIHelper} +/** + * A wrapper of the original SparkPlanGraph with additional information about the + * node-to-stage mapping. + * 1- The graph is constructed by visiting PlanInfos and creating GraphNodes and Edges. + * Although it is more efficient to assign stages during the construction of the nodes, + * the design is intentionally keeping those two phases separate to make the code more modular + * and easier to maintain. + * 2- Traverse the nodes and assign them to stages based on the metrics. + * 3- Nodes that belong to a graph cluster (childs of WholeStageCodeGen) while missing + * metrics, are assigned same as their WholeStageCodeGen node. + * 4- Iterate on all the orphanNodes and assign them to stages based on their adjacents nodes. + * 5- The iterative process is repeated until no assignment can be made. + * + * @param sparkGraph the original SparkPlanGraph to wrap + * @param accumToStageRetriever The object that eventually can retrieve StageIDs from AccumIds. + */ +class ToolsPlanGraph(val sparkGraph: SparkPlanGraph, + accumToStageRetriever: AccumToStageRetriever) { + // A map between SQLNode Id and the clusterIds that the node belongs to. + // Here, a clusterId means a stageId. + // Note: It is possible to represent the clusters as map [clusterId, Set[SQLNodeIds]]. + // While this is more memory efficient, it is more time-consuming to find the clusters a + // node belongs to since we have to iterate through all the keys. + private val nodeToStageCluster: mutable.Map[Long, Set[Int]] = mutable.HashMap[Long, Set[Int]]() + // shortcut to the nodes + def nodes: collection.Seq[SparkPlanGraphNode] = sparkGraph.nodes + // shortcut to the edges + def edges: collection.Seq[SparkPlanGraphEdge] = sparkGraph.edges + // delegate the call to the original graph + def allNodes: collection.Seq[SparkPlanGraphNode] = sparkGraph.allNodes + + /** + * Get stages that are associated with the accumulators of the node. + * Use this method if the purpose is to get raw information about the node-stage relationship + * based on the AccumIds without applying any logic. + * @param node the node to get the stages for + * @return a set of stageIds or empty if None + */ + private def getNodeStagesByAccum(node: SparkPlanGraphNode): Set[Int] = { + val nodeAccums = node.metrics.map(_.accumulatorId) + accumToStageRetriever.getStageIDsFromAccumIds(nodeAccums) + } + + /** + * Get the stages that the node belongs to. This function is used to get all the stages that can + * be assigned to a node. For example, if we want to get the "Exchange" node stages, then we call + * that method. + * @param node the node to get the stages for + * @return a set of stageIds or empty if None + */ + def getAllNodeStages(node: SparkPlanGraphNode): Set[Int] = { + val stageIdsByAccum = getNodeStagesByAccum(node) + nodeToStageCluster.get(node.id) match { + case Some(stageId) => stageIdsByAccum ++ stageId + case _ => stageIdsByAccum + } + } + + /** + * Check if a node exec is an epilogue. A.k.a, the exec has to be the tail of a stage. + * @param nodeName normalized node name (i.e., no GPU prefix) + * @return true if the node is an epilogue exec + */ + private def isEpilogueExec(nodeName: String): Boolean = { + nodeName match { + case "Exchange" | "BroadcastQueryStage" | "ShuffleQueryStage" | "TableCacheQueryStage" + | "ResultQueryStage" | "BroadcastExchange" => + true + case _ => false + } + } + + /** + * Check if a node exec is a prologue. A.k.a, the exec has to be the head of a stage. + * @param nodeName normalized node name (i.e., no GPU prefix) + * @return true if the node is a prologue exec + */ + private def isPrologueExec(nodeName: String): Boolean = { + nodeName match { + case nName if nName.contains("ShuffleRead") => + true + case _ => false + } + } + + /** + * Given a nodeName, this method returns a code that represents the node type. + * For example, an exchange node has to be at the end of a stage. ShuffleRead has to be at the + * beginning of a stage and so. + * + * @param nodeName the normalized name of the sparkNode (i.e., no GPU prefix). + * @return a code representing thenode type: + * (1) if the node can be assigned based on incoming edges. i.e., all nodes except the + * head of stage like shuffleRead. + * (2) if the node can be assigned based on outgoing edges. i.e., + * all nodes except the tail of stage like shuffleWrite/exchange. + * (3) if the node can be assigned based on both incoming and outgoing edges. + */ + private def multiplexCases(nodeName: String): Int = { + // nodes like shuffleRead should not be assigned to incoming edges + var result = 0 + if (!isPrologueExec(nodeName)) { + // Those are the nodes that can be assigned based on incoming edges. + result |= 1 + } + if (!isEpilogueExec(nodeName)) { + // Those are the nodes that can be assigned based on outgoing edges. + result |= 2 + } + result + } + + /** + * This method is used to assign a node to clusterID during the first walk of the graph. + * A cluster is used to wrap nodes together this could be a stageId. + * @param node the sparkNode to assign + * @return the clusterId that the node belongs to + */ + private def populateNodeClusters(node: SparkPlanGraphNode): Set[Int] = { + // First normalize the name. + val normalizedName = ToolsPlanGraph.processPlanInfo(node.name) + val stageIds = getNodeStagesByAccum(node) + normalizedName match { + case nName if isEpilogueExec(nName) => + // Cases that are tail of the stage cluster. + if (stageIds.size <= 1) { + stageIds + } else { + // Only use the smallest StageId because this would represent the stage that writes + // the data. + Set[Int](stageIds.min) + } + case nName if isPrologueExec(nName) => + // Cases that are head of a new stage. + if (stageIds.size <= 1) { + ToolsPlanGraph.EMPTY_CLUSTERS + } else { + // We should pick the stages associated with the reading metrics. This is likely to be + // the stage with the highest ID value. + Set[Int](stageIds.max) + } + case _ => + // Everything else goes here. + // It is possible to have multiple stages for a given node. + stageIds + } + } + + /** + * Updates the data structure that keeps track of the nodes cluster assignment. + * It adds the node to the map and remove the node from the orphans list if it exists. + * @param node the node to be assigned. + * @param orphanNodes the list of nodes that are not assigned to any cluster. + * @param clusters the clusterIds to assign the node to + */ + private def removeNodeFromOrphans(node: SparkPlanGraphNode, + orphanNodes: mutable.ArrayBuffer[SparkPlanGraphNode], + clusters: Set[Int]): Unit = { + nodeToStageCluster.put(node.id, clusters) + orphanNodes -= node + } + + /** + * Commits a wholeStageNode to a cluster. + * A WholeStageNode is visited after its children are. If any of the children is not assigned to + * a cluster, the wNode will transfer its assignment to the child. + * @param wNode the wholeStageCodeGen node to be visited + * @param orphanNodes the list of nodes that are not assigned to any cluster. + * @param clusters the clusterId to assign the node to. + * @return true if a change is made. + */ + private def commitNodeToStageCluster( + wNode: SparkPlanGraphCluster, + orphanNodes: mutable.ArrayBuffer[SparkPlanGraphNode], + clusters: Set[Int]): Boolean = { + if (nodeToStageCluster.contains(wNode.id) && clusters.subsetOf(nodeToStageCluster(wNode.id))) { + // Nothing to do since the node is assigned to the same cluster before. + false + } else { + val newClusterIds = + clusters ++ nodeToStageCluster.getOrElse(wNode.id, ToolsPlanGraph.EMPTY_CLUSTERS) + // Remove the wNode from orphanNodes if it exists + removeNodeFromOrphans(wNode, orphanNodes, newClusterIds) + // Assign the children to the same clusters if any of them is not assigned already. + wNode.nodes.foreach { childNode => + if (!nodeToStageCluster.contains(childNode.id)) { + // Assign the child node to the same stage of wNode and remove it from orphans + removeNodeFromOrphans(childNode, orphanNodes, newClusterIds) + } + } + true + } + } + + /** + * Assign a node to a clusterId. This method is used to assign a node to a clusterId during the + * first visit. + * @param node sparkNode to be assigned + * @param orphanNodes the list of nodes that are not assigned to any cluster + * @param clusters the clusterIds to assign the node to + * @return true if a change is made. + */ + private def commitNodeToStageCluster( + node: SparkPlanGraphNode, + orphanNodes: mutable.ArrayBuffer[SparkPlanGraphNode], + clusters: Set[Int]): Boolean = { + node match { + case cluster: SparkPlanGraphCluster => + // WholeCodeGen represents a special case because it propagates its assignment to + // children nodes. + commitNodeToStageCluster(cluster, orphanNodes, clusters) + case _ => + removeNodeFromOrphans(node, orphanNodes, clusters) + true + } + } + + /** + * Walk through the graph nodes and assign them to the correct stage cluster. + */ + protected def assignNodesToStageClusters(): Unit = { + // Keep track of nodes that have no assignment to any cluster. + val orphanNodes = mutable.ArrayBuffer[SparkPlanGraphNode]() + // Step(1): Visit all the nodes and assign them to the correct cluster based on AccumIDs. + // In the process, WholeStageCodeGens propagate their assignment to the child nodes if + // they are orphans. + allNodes.foreach { node => + if (!nodeToStageCluster.contains(node.id)) { + // Get clusterIDs based on AccumIds + val clusterIds = populateNodeClusters(node) + if (clusterIds.nonEmpty) { + // Found assignment + commitNodeToStageCluster(node, orphanNodes, clusterIds) + } else { + // This node has no assignment. Add it to the orphanNodes + orphanNodes += node + } + } + } + // Step(2): At this point, we made a quick visit handling all the straightforward cases. + // Iterate on the orphanNodes and try to assign them based on the adjacent nodes. + var changeFlag = orphanNodes.nonEmpty + while (changeFlag) { + // Iterate on the orphanNodes and try to assign them based on the adjacent nodes until no + // changes can be done in a single iteration. + changeFlag = false + // P.S: Copy the orphanNodes because we cannot remove objects inside the loop. + val orphanNodesCopy = orphanNodes.clone() + orphanNodesCopy.foreach { currNode => + if (orphanNodes.contains(currNode)) { // Avoid dup processing caused by wholeStageCodeGen + val currNodeName = ToolsPlanGraph.processPlanInfo(currNode.name) + val updatedFlag = currNode match { + case wNode: SparkPlanGraphCluster => + // WholeStageCodeGen is a corner case because it is not connected by edges. + // The only way to set the clusterID is to get it from the children if any. + wNode.nodes.find { childNode => nodeToStageCluster.contains(childNode.id) } match { + case Some(childNode) => + val clusterIDs = nodeToStageCluster(childNode.id) + commitNodeToStageCluster(wNode, orphanNodes, clusterIDs) + case _ => // do nothing if we could not find a child node with a clusterId + false + } + case _ => + // Handle all other nodes. + // Set the node type to determine the restrictions (i.e., exchange is + // positioned at the tail of a stage and shuffleRead should be the head of a stage). + val nodeCase = multiplexCases(currNodeName) + var clusterIDs = ToolsPlanGraph.EMPTY_CLUSTERS + if ((nodeCase & 1) > 0) { + // Assign cluster based on incoming edges. + val inEdgesWithIds = + edges.filter(e => e.toId == currNode.id && nodeToStageCluster.contains(e.fromId)) + if (inEdgesWithIds.nonEmpty) { + // For simplicity, assign the node based on the first incoming adjacent node. + clusterIDs = nodeToStageCluster(inEdgesWithIds.head.fromId) + } + } + if (clusterIDs.isEmpty && (nodeCase & 2) > 0) { + // Assign cluster based on outgoing edges (i.e., ShuffleRead). + // Corner case: TPC-DS Like Bench q2 (sqlID 24). + // A shuffleReader is reading on driver followed by an exchange without + // metrics. + // The metrics will not have a valid accumID. + // In that case, it is not feasible to match it to a cluster without + // considering the incoming node (exchange in that case). This corner + // case is handled later as a last-ditch effort. + val outEdgesWithIds = + edges.filter(e => e.fromId == currNode.id && nodeToStageCluster.contains(e.toId)) + if (outEdgesWithIds.nonEmpty) { + // For simplicity, assign the node based on the first outgoing adjacent node. + clusterIDs = nodeToStageCluster(outEdgesWithIds.head.toId) + } + } + if (clusterIDs.nonEmpty) { + // There is a possible assignment. Commit it. + commitNodeToStageCluster(currNode, orphanNodes, clusterIDs) + } else { + // nothing has changed + false + } + } // End of setting the UpdatedFlag variable. + changeFlag |= updatedFlag + } // End of if orphanNodes.contains(currNode). + } // End of iteration on orphanNodes. + // Corner case for shuffleRead when it is reading from the driver followed by an exchange that + // has no metrics. + if (!changeFlag && orphanNodes.nonEmpty) { + // This is to handle the special case of a shuffleRead that is reading from the driver. + // We could not assign any node to a cluster. This means that we have a cycle in the graph, + // and we need to break it. + // This is done by breaking the rule, allowing the shuffleRead to pick the highest stage + // order of the ancestor node. + changeFlag |= orphanNodes.filter( + n => isPrologueExec(ToolsPlanGraph.processPlanInfo(n.name))).exists { // Picks shuffleRead + orphanNode => + // Get adjacent nodes to the shuffleRead that have cluster assignment. + val inEdgesWithIds = + edges.filter(e => e.toId == orphanNode.id && nodeToStageCluster.contains(e.fromId)) + if (inEdgesWithIds.nonEmpty) { + // At this point, we need to get all the possible stageIDs that can be assigned to the + // adjacent nodes because and not only the logical ones. + val possibleIds = inEdgesWithIds.map { e => + val adjacentNode = allNodes.find(eN => eN.id == e.fromId).get + getAllNodeStages(adjacentNode) + }.reduce(_ ++ _) + // Assign the maximum value clusterId to the node. + val newIDs = Set[Int](possibleIds.max) + commitNodeToStageCluster(orphanNode, orphanNodes, newIDs) + } else { + false + } + } + } // end of corner case handling + } // end of changeFlag loop + } // end of assignNodesToStageClusters + // Start the construction of the graph + assignNodesToStageClusters() + + // Define public interface methods + /** + * Get the stage clusters that the node belongs to. + * Use this method if this logical representation of the node-to-stage relationship. + * For example, an "Exchange" node returns only a single stageID which is the stage that writes + * the data. + * @param node the node to get the stages for + * @return a set of stageIds or empty if None + */ + def getNodeStageClusters(node: SparkPlanGraphNode): Set[Int] = { + nodeToStageCluster.getOrElse(node.id, ToolsPlanGraph.EMPTY_CLUSTERS) + } + + def getNodeStageClusters(nodeId: Long): Set[Int] = { + nodeToStageCluster.getOrElse(nodeId, ToolsPlanGraph.EMPTY_CLUSTERS) + } +} // end of class ToolsPlanGraph + /** * This code is mostly copied from org.apache.spark.sql.execution.ui.SparkPlanGraph * with changes to handle GPU nodes. Without this special handle, the default SparkPlanGraph @@ -34,6 +393,8 @@ import org.apache.spark.sql.rapids.tool.util.stubs.{GraphReflectionAPI, GraphRef * Build a SparkPlanGraph from the root of a SparkPlan tree. */ object ToolsPlanGraph { + // Empty cluster set used to represent a node that is not assigned to any cluster. + private val EMPTY_CLUSTERS: Set[Int] = Set.empty // Captures the API loaded at runtime if any. var api: GraphReflectionAPI = _ @@ -89,6 +450,12 @@ object ToolsPlanGraph { } } + def createGraphWithStageClusters(planInfo: SparkPlanInfo, + accumStageMapper: AccumToStageRetriever): ToolsPlanGraph = { + val sGraph = ToolsPlanGraph(planInfo) + new ToolsPlanGraph(sGraph, accumStageMapper) + } + private def processPlanInfo(nodeName: String): String = { if (nodeName.startsWith("Gpu")) { nodeName.replaceFirst("Gpu", "") diff --git a/core/src/test/resources/QualificationExpectations/complex_dec_expectation.csv b/core/src/test/resources/QualificationExpectations/complex_dec_expectation.csv index f76c554be..8a9e1f666 100644 --- a/core/src/test/resources/QualificationExpectations/complex_dec_expectation.csv +++ b/core/src/test/resources/QualificationExpectations/complex_dec_expectation.csv @@ -1,2 +1,2 @@ App Name,App ID,SQL DF Duration,SQL Dataframe Task Duration,App Duration,GPU Opportunity,Executor CPU Time Percent,SQL Ids with Failures,Unsupported Read File Formats and Types,Unsupported Write Data Format,Complex Types,Nested Complex Types,Potential Problems,Longest SQL Duration,SQL Stage Durations Sum,NONSQL Task Duration Plus Overhead,Unsupported Task Duration,Supported SQL DF Task Duration,App Duration Estimated,Unsupported Execs,Unsupported Expressions,Estimated Job Frequency (monthly), Total Core Seconds -"Spark shell","local-1626104300434",1500,1469,131104,1315,88.35,"","","","struct,lastname:string>;struct,previous:struct,city:string>>;array>;map;map>;map>;array>;array","struct,lastname:string>;struct,previous:struct,city:string>>;array>;map>;map>;array>","NESTED COMPLEX TYPE",1260,1388,129598,181,1288,false,"CollectLimit","",30,1564 +"Spark shell","local-1626104300434",1500,1469,131104,996,88.35,"","","","struct,lastname:string>;struct,previous:struct,city:string>>;array>;map;map>;map>;array>;array","struct,lastname:string>;struct,previous:struct,city:string>>;array>;map>;map>;array>","NESTED COMPLEX TYPE",1260,1388,129598,493,976,false,"CollectLimit","",30,1564 diff --git a/core/src/test/resources/QualificationExpectations/read_dsv1_expectation.csv b/core/src/test/resources/QualificationExpectations/read_dsv1_expectation.csv index 4cb0d9940..b725defc0 100644 --- a/core/src/test/resources/QualificationExpectations/read_dsv1_expectation.csv +++ b/core/src/test/resources/QualificationExpectations/read_dsv1_expectation.csv @@ -1,2 +1,2 @@ App Name,App ID,SQL DF Duration,SQL Dataframe Task Duration,App Duration,GPU Opportunity,Executor CPU Time Percent,SQL Ids with Failures,Unsupported Read File Formats and Types,Unsupported Write Data Format,Complex Types,Nested Complex Types,Potential Problems,Longest SQL Duration,SQL Stage Durations Sum,NONSQL Task Duration Plus Overhead,Unsupported Task Duration,Supported SQL DF Task Duration,App Duration Estimated,Unsupported Execs,Unsupported Expressions,Estimated Job Frequency (monthly),Total Core Seconds -"Spark shell","local-1624371544219",4575,20421,175293,1557,72.15,"","JSON[string:double:date:int:bigint];Text[*]","JSON","","","",1859,5372,176916,13469,6952,false,"CollectLimit;Scan text;Execute InsertIntoHadoopFsRelationCommand json;Scan json","",30,2096 +"Spark shell","local-1624371544219",4575,20421,175293,1523,72.15,"","JSON[string:double:date:int:bigint];Text[*]","JSON","","","",1859,5372,176916,13622,6799,false,"CollectLimit;Scan text;Execute InsertIntoHadoopFsRelationCommand json;Scan json","",30,2096 diff --git a/core/src/test/resources/QualificationExpectations/read_dsv2_expectation.csv b/core/src/test/resources/QualificationExpectations/read_dsv2_expectation.csv index 404c02755..4c7726207 100644 --- a/core/src/test/resources/QualificationExpectations/read_dsv2_expectation.csv +++ b/core/src/test/resources/QualificationExpectations/read_dsv2_expectation.csv @@ -1,2 +1,2 @@ App Name,App ID,SQL DF Duration,SQL Dataframe Task Duration,App Duration,GPU Opportunity,Executor CPU Time Percent,SQL Ids with Failures,Unsupported Read File Formats and Types,Unsupported Write Data Format,Complex Types,Nested Complex Types,Potential Problems,Longest SQL Duration,SQL Stage Durations Sum,NONSQL Task Duration Plus Overhead,Unsupported Task Duration,Supported SQL DF Task Duration,App Duration Estimated,Unsupported Execs,Unsupported Expressions,Estimated Job Frequency (monthly),Total Core Seconds -"Spark shell","local-1624371906627",4917,21802,83738,1745,71.3,"","Text[*];json[double]","JSON","","","",1984,5438,83336,14064,7738,false,"CollectLimit;Scan text;Execute InsertIntoHadoopFsRelationCommand json;BatchScan json","",30,997 +"Spark shell","local-1624371906627",4917,21802,83738,2687,71.3,"","Text[*];json[double]","JSON","","","",1984,5438,83336,9889,11913,false,"CollectLimit;Scan text;Execute InsertIntoHadoopFsRelationCommand json;BatchScan json","",30,997 diff --git a/core/src/test/resources/QualificationExpectations/truncated_1_end_expectation.csv b/core/src/test/resources/QualificationExpectations/truncated_1_end_expectation.csv index 6ef5acd56..f7737d508 100644 --- a/core/src/test/resources/QualificationExpectations/truncated_1_end_expectation.csv +++ b/core/src/test/resources/QualificationExpectations/truncated_1_end_expectation.csv @@ -1,2 +1,2 @@ App Name,App ID,SQL DF Duration,SQL Dataframe Task Duration,App Duration,GPU Opportunity,Executor CPU Time Percent,SQL Ids with Failures,Unsupported Read File Formats and Types,Unsupported Write Data Format,Complex Types,Nested Complex Types,Potential Problems,Longest SQL Duration,SQL Stage Durations Sum,NONSQL Task Duration Plus Overhead,Unsupported Task Duration,Supported SQL DF Task Duration,App Duration Estimated,Unsupported Execs,Unsupported Expressions,Estimated Job Frequency (monthly),Total Core Seconds -"Rapids Spark Profiling Tool Unit Tests","local-1622043423018",395,14353,4872,142,62.67,"","","JSON","","","",1306,794,4477,9164,5189,true,"SerializeFromObject;Execute InsertIntoHadoopFsRelationCommand json;DeserializeToObject;Filter;MapElements;Scan","",30,49 +"Rapids Spark Profiling Tool Unit Tests","local-1622043423018",395,14353,4872,164,62.67,"","","JSON","","","",1306,794,4477,8376,5977,true,"SerializeFromObject;Execute InsertIntoHadoopFsRelationCommand json;DeserializeToObject;Filter;MapElements;Scan","",30,49 diff --git a/core/src/test/scala/com/nvidia/spark/rapids/tool/planparser/BasePlanParserSuite.scala b/core/src/test/scala/com/nvidia/spark/rapids/tool/planparser/BasePlanParserSuite.scala index 54cad1b1c..b7966d4d2 100644 --- a/core/src/test/scala/com/nvidia/spark/rapids/tool/planparser/BasePlanParserSuite.scala +++ b/core/src/test/scala/com/nvidia/spark/rapids/tool/planparser/BasePlanParserSuite.scala @@ -80,4 +80,27 @@ class BasePlanParserSuite extends BaseTestSuite { e.children.getOrElse(Seq.empty) :+ e } } + def verifyPlanExecToStageMap(toolsPlanInfo: PlanInfo): Unit = { + val allExecInfos = toolsPlanInfo.execInfo.flatMap { e => + e.children.getOrElse(Seq.empty) :+ e + } + // Test that all execs are assigned to stages + assert (allExecInfos.forall(_.stages.nonEmpty)) + // assert that exchange is assigned to a single stage + val exchangeExecs = allExecInfos.filter(_.exec == "Exchange") + if (exchangeExecs.nonEmpty) { + assert (exchangeExecs.forall(_.stages.size == 1)) + } + } + + def verifyExecToStageMapping(plans: Seq[PlanInfo], + qualApp: QualificationAppInfo, funcCB: Option[PlanInfo => Unit] = None): Unit = { + // Only iterate on plans with that are associated to jobs + val associatedSqls = qualApp.jobIdToSqlID.values.toSeq + val filteredPlans = plans.filter(p => associatedSqls.contains(p.sqlID)) + val func = funcCB.getOrElse(verifyPlanExecToStageMap(_)) + filteredPlans.foreach { plan => + func(plan) + } + } } diff --git a/core/src/test/scala/com/nvidia/spark/rapids/tool/planparser/SqlPlanParserSuite.scala b/core/src/test/scala/com/nvidia/spark/rapids/tool/planparser/SqlPlanParserSuite.scala index a3d6211bf..6fc9357cf 100644 --- a/core/src/test/scala/com/nvidia/spark/rapids/tool/planparser/SqlPlanParserSuite.scala +++ b/core/src/test/scala/com/nvidia/spark/rapids/tool/planparser/SqlPlanParserSuite.scala @@ -109,7 +109,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { app.sqlPlans.foreach { case (sqlID, plan) => val planInfo = SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) - + verifyPlanExecToStageMap(planInfo) val wholeStages = planInfo.execInfo.filter(_.exec.contains("WholeStageCodegen")) val allChildren = wholeStages.flatMap(_.children).flatten val sorts = allChildren.filter(_.exec == "Sort") @@ -205,6 +205,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { app.sqlPlans.foreach { case (sqlID, plan) => val planInfo = SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) + verifyPlanExecToStageMap(planInfo) val allExecInfo = planInfo.execInfo // Note that: // Spark320+ will generate the following execs: @@ -247,6 +248,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { app.sqlPlans.foreach { case (sqlID, plan) => val planInfo = SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) + verifyPlanExecToStageMap(planInfo) val wholeStages = planInfo.execInfo.filter(_.exec.contains("WholeStageCodegen")) assert(wholeStages.size == 2) val numSupported = wholeStages.filter(_.isSupported).size @@ -267,6 +269,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val json = allExecInfo.filter(_.exec.contains("Scan json")) val orc = allExecInfo.filter(_.exec.contains("Scan orc")) @@ -289,6 +292,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) // Note that the text scan from this file is v1 so ignore it val json = allExecInfo.filter(_.exec.contains("BatchScan json")) @@ -319,6 +323,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val subqueryExecs = allExecInfo.filter(_.exec.contains(s"Subquery")) val summaryRecs = subqueryExecs.flatten { sqExec => @@ -354,6 +359,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val writeExecs = allExecInfo.filter(_.exec.contains(s"$dataWriteCMD")) val text = writeExecs.filter(_.expr.contains("text")) @@ -393,6 +399,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val writeExecs = allExecInfo.filter(_.exec.contains(s"$dataWriteCMD")) val text = writeExecs.filter(_.expr.contains("text")) @@ -425,6 +432,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val parquet = { allExecInfo.filter(_.exec.contains("CreateDataSourceTableAsSelectCommand")) @@ -454,6 +462,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val tableScan = allExecInfo.filter(_.exec == ("InMemoryTableScan")) assertSizeAndSupported(1, tableScan.toSeq) @@ -468,6 +477,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val broadcasts = allExecInfo.filter(_.exec == "BroadcastExchange") assertSizeAndSupported(3, broadcasts.toSeq, @@ -488,6 +498,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) // reusedExchange is added as a supportedExec val reusedExchangeExecs = allExecInfo.filter(_.exec == "ReusedExchange") @@ -509,6 +520,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val reader = allExecInfo.filter(_.exec == "CustomShuffleReader") assertSizeAndSupported(2, reader.toSeq) @@ -523,6 +535,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val reader = allExecInfo.filter(_.exec == "AQEShuffleRead") assertSizeAndSupported(2, reader.toSeq) @@ -552,15 +565,17 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) for (execName <- supportedExecs) { val execs = allExecInfo.filter(_.exec == execName) - assertSizeAndSupported(1, execs.toSeq, expectedDur = Seq.empty, extraText = execName) + assertSizeAndSupported(1, execs, expectedDur = Seq.empty, extraText = execName) } for (execName <- unsupportedExecs) { val execs = allExecInfo.filter(_.exec == execName) - assertSizeAndNotSupported(1, execs.toSeq) + assertSizeAndNotSupported(1, execs) } + verifyExecToStageMapping(parsedPlans.toSeq, app) } } @@ -581,6 +596,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) for (execName <- supportedExecs) { val supportedExec = allExecInfo.filter(_.exec == execName) @@ -617,6 +633,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val bhj = allExecInfo.filter(_.exec == "BroadcastHashJoin") assertSizeAndSupported(1, bhj) @@ -659,6 +676,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val bhj = allExecInfo.filter(_.exec == "BroadcastHashJoin") assertSizeAndNotSupported(1, bhj) @@ -692,6 +710,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val smj = allExecInfo.filter(_.exec == "SortMergeJoin") assertSizeAndNotSupported(1, smj) @@ -714,6 +733,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val execInfo = getAllExecsFromPlan(parsedPlans.toSeq) val sortAggregate = execInfo.filter(_.exec == "SortAggregate") assertSizeAndSupported(2, sortAggregate) @@ -734,6 +754,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val execInfo = getAllExecsFromPlan(parsedPlans.toSeq) val objectHashAggregate = execInfo.filter(_.exec == "ObjectHashAggregate") // OHA will get sql time metrics "time in aggregation build" @@ -760,6 +781,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val execInfo = getAllExecsFromPlan(parsedPlans.toSeq) val windowExecs = execInfo.filter(_.exec == "Window") assertSizeAndSupported(1, windowExecs) @@ -775,6 +797,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val flatMapGroups = allExecInfo.filter(_.exec == "FlatMapGroupsInPandas") assertSizeAndSupported(1, flatMapGroups) @@ -800,6 +823,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val supportedExecs = Array("GlobalLimit", "LocalLimit") app.sqlPlans.foreach { case (sqlID, plan) => val planInfo = SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) + verifyPlanExecToStageMap(planInfo) // GlobalLimit and LocalLimit are inside WholeStageCodegen. So getting the children of // WholeStageCodegenExec val wholeStages = planInfo.execInfo.filter(_.exec.contains("WholeStageCodegen")) @@ -825,6 +849,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { app.sqlPlans.foreach { case (sqlID, plan) => val planInfo = SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) + verifyPlanExecToStageMap(planInfo) val wholeStages = planInfo.execInfo.filter(_.exec.contains("WholeStageCodegen")) assert(wholeStages.size == 1) val allChildren = wholeStages.flatMap(_.children).flatten @@ -849,6 +874,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { app.sqlPlans.foreach { case (sqlID, plan) => val planInfo = SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) + verifyPlanExecToStageMap(planInfo) val wholeStages = planInfo.execInfo.filter(_.exec.contains("WholeStageCodegen")) assert(wholeStages.size == 2) val allChildren = wholeStages.flatMap(_.children).flatten @@ -873,6 +899,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val execInfo = getAllExecsFromPlan(parsedPlans.toSeq) val takeOrderedAndProject = execInfo.filter(_.exec == "TakeOrderedAndProject") assertSizeAndNotSupported(1, takeOrderedAndProject) @@ -897,6 +924,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val execInfo = getAllExecsFromPlan(parsedPlans.toSeq) val generateExprs = execInfo.filter(_.exec == "Generate") assertSizeAndSupported(1, generateExprs) @@ -924,6 +952,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val execInfo = getAllExecsFromPlan(parsedPlans.toSeq) val projectExprs = execInfo.filter(_.exec == "Project") assertSizeAndSupported(1, projectExprs) @@ -948,6 +977,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val execInfo = getAllExecsFromPlan(parsedPlans.toSeq) val sortAggregate = execInfo.filter(_.exec == "SortAggregate") assertSizeAndSupported(2, sortAggregate) @@ -974,6 +1004,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val sortExec = allExecInfo.filter(_.exec.contains("Sort")) assert(sortExec.size == 3) @@ -1001,6 +1032,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val wholeStages = allExecInfo.filter(_.exec.contains("WholeStageCodegen")) assert(wholeStages.size == 1) @@ -1029,6 +1061,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "test desc", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) parsedPlans.foreach { pInfo => assert(pInfo.sqlDesc == "test desc") } @@ -1061,6 +1094,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val wholeStages = allExecInfo.filter(_.exec.contains("WholeStageCodegen")) assert(wholeStages.size == 1) @@ -1091,6 +1125,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val wholeStages = allExecInfo.filter(_.exec.contains("WholeStageCodegen")) assert(wholeStages.size == 1) @@ -1121,6 +1156,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val wholeStages = allExecInfo.filter(_.exec.contains("WholeStageCodegen")) assert(wholeStages.size == 1) @@ -1183,6 +1219,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val projects = allExecInfo.filter(_.exec.contains("Project")) assertSizeAndNotSupported(1, projects) @@ -1211,6 +1248,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val wholeStages = allExecInfo.filter(_.exec.contains("WholeStageCodegen")) assert(wholeStages.size == 1) @@ -1239,6 +1277,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val execInfo = getAllExecsFromPlan(parsedPlans.toSeq) val hashAggregate = execInfo.filter(_.exec == "HashAggregate") assertSizeAndSupported(2, hashAggregate, checkDurations = false) @@ -1265,6 +1304,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val wholeStages = allExecInfo.filter(_.exec.contains("WholeStageCodegen")) assert(wholeStages.size == 1) @@ -1344,6 +1384,11 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + // TODO: Spark shows a weird behavior as the entire plan with SQL 65 loses the metrics + // and the associated jobs. This causes some execs to be isolated without stage. + // The UI won't be able to visualize that job anymore. So, we need to investigate + // what happens in that query before we test the execs-to-stage mapping. + val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val deltaLakeWrites = allExecInfo.filter(_.exec.contains(s"$dataWriteCMD")) assertSizeAndSupported(1, deltaLakeWrites) @@ -1406,6 +1451,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) // The promote_precision should be part of the project exec. val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val projExecs = allExecInfo.filter(_.exec.contains("Project")) @@ -1449,6 +1495,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) // The current_database should be part of the project-exec and the parser should ignore it. val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val projExecs = allExecInfo.filter(_.exec.contains("Project")) @@ -1697,6 +1744,18 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + // Note that the generated plan, there are skipped stages that causes some execs to appear + // without their relevant stages. so we skip the stage verification here. + verifyExecToStageMapping(parsedPlans.toSeq, app, Some( planInfo => + if (planInfo.sqlID == 73) { + // Nodes should not have any stages + val allExecInfos = planInfo.execInfo.flatMap { e => + e.children.getOrElse(Seq.empty) :+ e + } + // exclude all stages higher than 8 because those ones belong to a skipped stage + allExecInfos.filter(_.nodeId <= 8).forall(_.stages.nonEmpty) + }) + ) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val windowGroupLimitExecs = allExecInfo.filter(_.exec.contains(windowGroupLimitExecCmd)) // We should have two WindowGroupLimitExec operators (Partial and Final). @@ -1728,6 +1787,18 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + // Note that the generated plan, there are skipped stages that causes some execs to appear + // without their relevant stages. so we skip the stage verification here. + verifyExecToStageMapping(parsedPlans.toSeq, app, Some( planInfo => + if (planInfo.sqlID == 76) { + // Nodes should not have any stages + val allExecInfos = planInfo.execInfo.flatMap { e => + e.children.getOrElse(Seq.empty) :+ e + } + // exclude all stages higher than 8 because those ones belong to a skipped stage + allExecInfos.filter(_.nodeId <= 8).forall(_.stages.nonEmpty) + }) + ) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val windowExecNotSupportedExprs = allExecInfo.filter( _.exec.contains(windowGroupLimitExecCmd)).flatMap(x => x.unsupportedExprs) @@ -1793,6 +1864,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) // we should have 2 hash aggregates with min_by and max_by expressions // if the min_by and max_by were not recognized, the test would fail val hashAggExecs = @@ -1822,6 +1894,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parsedPlans = app.sqlPlans.map { case (sqlID, plan) => SQLPlanParser.parseSQLPlan(app.appId, plan, sqlID, "", pluginTypeChecker, app) } + verifyExecToStageMapping(parsedPlans.toSeq, app) val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val projectExecs = allExecInfo.filter(_.exec == "Project") assertSizeAndSupported(1, projectExecs) From 091af086eaf37b31211c7aa0abcdd3280e67e44b Mon Sep 17 00:00:00 2001 From: YanxuanLiu <104543031+YanxuanLiu@users.noreply.github.com> Date: Wed, 4 Dec 2024 04:11:08 +0800 Subject: [PATCH 17/22] enable license header check and add header for files (#1440) Signed-off-by: YanxuanLiu --- .github/workflows/license-header-check.yml | 50 +++++++++++++++++++ ...fo-autotuner-example-8cores-16gmemory.yaml | 14 ++++++ data_validation/pyproject.toml | 14 ++++++ data_validation/templates/datavalid_conf.yml | 14 ++++++ data_validation/tox.ini | 14 ++++++ user_tools/pyproject.toml | 14 ++++++ .../resources/bootstrap-conf.yaml | 14 ++++++ .../resources/cluster-configs.yaml | 14 ++++++ .../dev/process_databricks_azure_pricing.py | 14 ++++++ .../resources/diagnostic-conf.yaml | 14 ++++++ .../resources/profiling-conf.yaml | 14 ++++++ .../resources/qualification-conf.yaml | 14 ++++++ .../resources/cluster/dataproc/cpu-00.yaml | 14 ++++++ .../cluster/dataproc_gke/cpu-00.yaml | 14 ++++++ .../resources/cluster/onprem/cpu-00.yaml | 14 ++++++ .../invalid/tools_config_inv_00.yaml | 14 ++++++ .../invalid/tools_config_inv_01.yaml | 14 ++++++ .../invalid/tools_config_inv_02.yaml | 14 ++++++ .../tools_config/valid/tools_config_00.yaml | 14 ++++++ .../resources/worker_info.yaml | 14 ++++++ user_tools/tox.ini | 14 ++++++ 21 files changed, 330 insertions(+) create mode 100644 .github/workflows/license-header-check.yml diff --git a/.github/workflows/license-header-check.yml b/.github/workflows/license-header-check.yml new file mode 100644 index 000000000..1b27aa454 --- /dev/null +++ b/.github/workflows/license-header-check.yml @@ -0,0 +1,50 @@ +# Copyright (c) 2024, NVIDIA CORPORATION. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A workflow to check copyright/license header +name: license header check + +on: + pull_request: + types: [opened, synchronize, reopened] + +jobs: + license-header-check: + runs-on: ubuntu-latest + if: "!contains(github.event.pull_request.title, '[bot]')" + steps: + - name: Get checkout depth + run: | + echo "PR_FETCH_DEPTH=$(( ${{ github.event.pull_request.commits }} + 10 ))" >> $GITHUB_ENV + + - name: Checkout code + uses: actions/checkout@v4 + with: + fetch-depth: ${{ env.PR_FETCH_DEPTH }} + + - name: license-header-check + uses: NVIDIA/spark-rapids-common/license-header-check@main + with: + included_file_patterns: | + *.py, + *.toml, + *.ini, + *.yml, + *.yaml, + *.sh, + *.properties, + *.xml, + *.feature, + *.scala + \ No newline at end of file diff --git a/core/src/test/resources/worker_info-autotuner-example-8cores-16gmemory.yaml b/core/src/test/resources/worker_info-autotuner-example-8cores-16gmemory.yaml index 9ad530544..12091e726 100644 --- a/core/src/test/resources/worker_info-autotuner-example-8cores-16gmemory.yaml +++ b/core/src/test/resources/worker_info-autotuner-example-8cores-16gmemory.yaml @@ -1,3 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + system: numCores: 8 memory: 16384MiB diff --git a/data_validation/pyproject.toml b/data_validation/pyproject.toml index 0516a2b98..8bff2bb93 100644 --- a/data_validation/pyproject.toml +++ b/data_validation/pyproject.toml @@ -1,3 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + [build-system] requires = ["setuptools"] build-backend = "setuptools.build_meta" diff --git a/data_validation/templates/datavalid_conf.yml b/data_validation/templates/datavalid_conf.yml index 5fe2d1f31..8c864d1fe 100644 --- a/data_validation/templates/datavalid_conf.yml +++ b/data_validation/templates/datavalid_conf.yml @@ -1,3 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + sparkConf: spark.executor.memory: 4g spark.executor.cores: 3 diff --git a/data_validation/tox.ini b/data_validation/tox.ini index 58c3a0212..4725be6de 100644 --- a/data_validation/tox.ini +++ b/data_validation/tox.ini @@ -1,3 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + # tox (https://tox.readthedocs.io/) is a tool for running tests # in multiple virtualenvs. This configuration file will run the # test suite on all supported python versions. To use it, "pip install tox" diff --git a/user_tools/pyproject.toml b/user_tools/pyproject.toml index c92bff303..2c903919f 100644 --- a/user_tools/pyproject.toml +++ b/user_tools/pyproject.toml @@ -1,3 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + [build-system] requires = ["setuptools"] build-backend = "setuptools.build_meta" diff --git a/user_tools/src/spark_rapids_pytools/resources/bootstrap-conf.yaml b/user_tools/src/spark_rapids_pytools/resources/bootstrap-conf.yaml index ee24afdd4..a339a4d0f 100644 --- a/user_tools/src/spark_rapids_pytools/resources/bootstrap-conf.yaml +++ b/user_tools/src/spark_rapids_pytools/resources/bootstrap-conf.yaml @@ -1,3 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + platform: shortName: 'boot' # workDir: rapids_user_tools_bootstrap diff --git a/user_tools/src/spark_rapids_pytools/resources/cluster-configs.yaml b/user_tools/src/spark_rapids_pytools/resources/cluster-configs.yaml index 700c181a5..d64b1ff95 100644 --- a/user_tools/src/spark_rapids_pytools/resources/cluster-configs.yaml +++ b/user_tools/src/spark_rapids_pytools/resources/cluster-configs.yaml @@ -1,3 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + clusterConfigs: constants: # Maximum amount of pinned memory to use per executor in megabytes diff --git a/user_tools/src/spark_rapids_pytools/resources/dev/process_databricks_azure_pricing.py b/user_tools/src/spark_rapids_pytools/resources/dev/process_databricks_azure_pricing.py index 19953f393..9ca2ddc1c 100644 --- a/user_tools/src/spark_rapids_pytools/resources/dev/process_databricks_azure_pricing.py +++ b/user_tools/src/spark_rapids_pytools/resources/dev/process_databricks_azure_pricing.py @@ -1,3 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + """Python script used to process Databricks Azure instance pricing information.""" import json diff --git a/user_tools/src/spark_rapids_pytools/resources/diagnostic-conf.yaml b/user_tools/src/spark_rapids_pytools/resources/diagnostic-conf.yaml index 359412120..7786e2aae 100644 --- a/user_tools/src/spark_rapids_pytools/resources/diagnostic-conf.yaml +++ b/user_tools/src/spark_rapids_pytools/resources/diagnostic-conf.yaml @@ -1,2 +1,16 @@ +# Copyright (c) 2024, NVIDIA CORPORATION. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + platform: shortName: 'diag' diff --git a/user_tools/src/spark_rapids_pytools/resources/profiling-conf.yaml b/user_tools/src/spark_rapids_pytools/resources/profiling-conf.yaml index 847e33914..b183a332f 100644 --- a/user_tools/src/spark_rapids_pytools/resources/profiling-conf.yaml +++ b/user_tools/src/spark_rapids_pytools/resources/profiling-conf.yaml @@ -1,3 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + toolOutput: subFolder: rapids_4_spark_profile textFormat: diff --git a/user_tools/src/spark_rapids_pytools/resources/qualification-conf.yaml b/user_tools/src/spark_rapids_pytools/resources/qualification-conf.yaml index 8e998011c..c149669c5 100644 --- a/user_tools/src/spark_rapids_pytools/resources/qualification-conf.yaml +++ b/user_tools/src/spark_rapids_pytools/resources/qualification-conf.yaml @@ -1,3 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + toolOutput: completeOutput: true subFolder: rapids_4_spark_qualification_output diff --git a/user_tools/tests/spark_rapids_tools_ut/resources/cluster/dataproc/cpu-00.yaml b/user_tools/tests/spark_rapids_tools_ut/resources/cluster/dataproc/cpu-00.yaml index c6bc6038d..9a0d74652 100644 --- a/user_tools/tests/spark_rapids_tools_ut/resources/cluster/dataproc/cpu-00.yaml +++ b/user_tools/tests/spark_rapids_tools_ut/resources/cluster/dataproc/cpu-00.yaml @@ -1,3 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + clusterName: dataproc-test-nongpu-cluster clusterUuid: 11111111-1111-1111-1111-111111111111 config: diff --git a/user_tools/tests/spark_rapids_tools_ut/resources/cluster/dataproc_gke/cpu-00.yaml b/user_tools/tests/spark_rapids_tools_ut/resources/cluster/dataproc_gke/cpu-00.yaml index 39bd70ddf..405f6bea5 100644 --- a/user_tools/tests/spark_rapids_tools_ut/resources/cluster/dataproc_gke/cpu-00.yaml +++ b/user_tools/tests/spark_rapids_tools_ut/resources/cluster/dataproc_gke/cpu-00.yaml @@ -1,3 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + clusterName: dataproc-gke-test-nongpu-cluster clusterUuid: 11111111-1111-1111-1111-111111111111 config: diff --git a/user_tools/tests/spark_rapids_tools_ut/resources/cluster/onprem/cpu-00.yaml b/user_tools/tests/spark_rapids_tools_ut/resources/cluster/onprem/cpu-00.yaml index b170d85b0..9a900ae95 100644 --- a/user_tools/tests/spark_rapids_tools_ut/resources/cluster/onprem/cpu-00.yaml +++ b/user_tools/tests/spark_rapids_tools_ut/resources/cluster/onprem/cpu-00.yaml @@ -1,3 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + config: masterConfig: numCores: 2 diff --git a/user_tools/tests/spark_rapids_tools_ut/resources/tools_config/invalid/tools_config_inv_00.yaml b/user_tools/tests/spark_rapids_tools_ut/resources/tools_config/invalid/tools_config_inv_00.yaml index aa566a71f..b656ea7ee 100644 --- a/user_tools/tests/spark_rapids_tools_ut/resources/tools_config/invalid/tools_config_inv_00.yaml +++ b/user_tools/tests/spark_rapids_tools_ut/resources/tools_config/invalid/tools_config_inv_00.yaml @@ -1,3 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + # This yaml file is a configuration file for a tool that uses Spark 3.5.0 as dependency # invalid: API version is smaller than accepted API version api_version: '0.9' diff --git a/user_tools/tests/spark_rapids_tools_ut/resources/tools_config/invalid/tools_config_inv_01.yaml b/user_tools/tests/spark_rapids_tools_ut/resources/tools_config/invalid/tools_config_inv_01.yaml index a723f2e66..dd713e594 100644 --- a/user_tools/tests/spark_rapids_tools_ut/resources/tools_config/invalid/tools_config_inv_01.yaml +++ b/user_tools/tests/spark_rapids_tools_ut/resources/tools_config/invalid/tools_config_inv_01.yaml @@ -1,3 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + # This yaml file is a configuration file # invalid: empty file # Error:1 validation error for ToolsConfig diff --git a/user_tools/tests/spark_rapids_tools_ut/resources/tools_config/invalid/tools_config_inv_02.yaml b/user_tools/tests/spark_rapids_tools_ut/resources/tools_config/invalid/tools_config_inv_02.yaml index 210b4419a..dc8f1df49 100644 --- a/user_tools/tests/spark_rapids_tools_ut/resources/tools_config/invalid/tools_config_inv_02.yaml +++ b/user_tools/tests/spark_rapids_tools_ut/resources/tools_config/invalid/tools_config_inv_02.yaml @@ -1,3 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + # This yaml file is a configuration file for a tool that uses Spark 3.5.0 as dependency # invalid: Local file can be verified during the initialization and it should fail because no such # file exists. diff --git a/user_tools/tests/spark_rapids_tools_ut/resources/tools_config/valid/tools_config_00.yaml b/user_tools/tests/spark_rapids_tools_ut/resources/tools_config/valid/tools_config_00.yaml index f7dccf951..85ef4e15b 100644 --- a/user_tools/tests/spark_rapids_tools_ut/resources/tools_config/valid/tools_config_00.yaml +++ b/user_tools/tests/spark_rapids_tools_ut/resources/tools_config/valid/tools_config_00.yaml @@ -1,3 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + # This yaml file is a configuration file for a tool that uses Spark 3.5.0 as dependency # Minimal file content. api_version: '1.0' diff --git a/user_tools/tests/spark_rapids_tools_ut/resources/worker_info.yaml b/user_tools/tests/spark_rapids_tools_ut/resources/worker_info.yaml index d9aaa14d5..7b3f8f32b 100644 --- a/user_tools/tests/spark_rapids_tools_ut/resources/worker_info.yaml +++ b/user_tools/tests/spark_rapids_tools_ut/resources/worker_info.yaml @@ -1,3 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + system: numCores: 32 memory: 212992MiB diff --git a/user_tools/tox.ini b/user_tools/tox.ini index b7a766d98..f89d18857 100644 --- a/user_tools/tox.ini +++ b/user_tools/tox.ini @@ -1,3 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + # tox (https://tox.readthedocs.io/) is a tool for running tests # in multiple virtualenvs. This configuration file will run the # test suite on all supported python versions. To use it, "pip install tox" From 993bc8f82e5c512349c3485fb15dc144f0bbc9b5 Mon Sep 17 00:00:00 2001 From: Niranjan Artal <50492963+nartal1@users.noreply.github.com> Date: Wed, 4 Dec 2024 14:03:15 -0800 Subject: [PATCH 18/22] Report all operators in the output file (#1444) * first iterations all the UTs pass Signed-off-by: Ahmed Hussein (amahussein) * running end-to-end Signed-off-by: Ahmed Hussein (amahussein) * cleaned-up exec parsers Signed-off-by: Ahmed Hussein (amahussein) * update documentation and fix Signed-off-by: Niranjan Artal * qualx related changes * update qualx changes * Fix for Scan OneRowRelation Signed-off-by: Niranjan Artal * addressed review comments --------- Signed-off-by: Niranjan Artal Co-authored-by: Ahmed Hussein (amahussein) --- .../tool/planparser/BatchScanExecParser.scala | 28 ++++- .../BroadcastExchangeExecParser.scala | 3 +- .../BroadcastHashJoinExecParser.scala | 6 +- .../BroadcastNestedLoopJoinExecParser.scala | 6 +- .../DataWritingCommandExecParser.scala | 6 +- .../tool/planparser/DeltaLakeHelper.scala | 4 +- .../rapids/tool/planparser/ExecParser.scala | 5 +- .../planparser/FileSourceScanExecParser.scala | 35 +++++- .../tool/planparser/GenericExecParser.scala | 14 ++- .../rapids/tool/planparser/ReadParser.scala | 12 +- .../tool/planparser/SQLPlanParser.scala | 73 ++++++++---- .../ShuffleExchangeExecParser.scala | 4 +- .../ShuffledHashJoinExecParser.scala | 4 +- .../planparser/SortMergeJoinExecParser.scala | 4 +- .../SubqueryBroadcastExecParser.scala | 5 +- .../tool/planparser/SubqueryExecParser.scala | 3 +- .../planparser/WholeStageExecParser.scala | 30 ++++- .../planparser/WindowGroupLimitParser.scala | 11 +- .../planparser/WriteFilesExecParser.scala | 5 +- .../rapids/tool/planparser/ops/OpRef.scala | 64 +++++++++++ .../tool/planparser/ops/OperatorCounter.scala | 106 ++++++++++++++++++ .../tool/planparser/ops/OperatorRefBase.scala | 41 +++++++ .../planparser/ops/OperatorRefTrait.scala | 24 ++++ .../planparser/ops/UnsupportedExprOpRef.scala | 43 +++++++ .../qualification/PluginTypeChecker.scala | 6 +- .../tool/qualification/QualOutputWriter.scala | 73 +++++++++++- .../tool/qualification/Qualification.scala | 1 + .../spark/sql/rapids/tool/AppBase.scala | 4 +- .../spark/sql/rapids/tool/ToolUtils.scala | 2 - .../qualification/QualificationAppInfo.scala | 9 +- .../db_sim_test_expectation.csv | 2 +- .../directory_test_expectation.csv | 2 +- .../jdbc_expectation.csv | 2 +- .../qual_test_missing_sql_end_expectation.csv | 2 +- .../qual_test_simple_expectation.csv | 2 +- .../truncated_1_end_expectation.csv | 2 +- .../tool/planparser/SqlPlanParserSuite.scala | 19 ++-- .../PluginTypeCheckerSuite.scala | 2 +- .../qualification/QualificationSuite.scala | 4 +- .../tools/qualx/preprocess.py | 25 +++-- 40 files changed, 574 insertions(+), 119 deletions(-) create mode 100644 core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/OpRef.scala create mode 100644 core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/OperatorCounter.scala create mode 100644 core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/OperatorRefBase.scala create mode 100644 core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/OperatorRefTrait.scala create mode 100644 core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/UnsupportedExprOpRef.scala diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/BatchScanExecParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/BatchScanExecParser.scala index a8188065c..7c591b372 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/BatchScanExecParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/BatchScanExecParser.scala @@ -27,8 +27,8 @@ case class BatchScanExecParser( checker: PluginTypeChecker, sqlID: Long, app: AppBase) extends ExecParser with Logging { - - val fullExecName = "BatchScanExec" + val nodeName = "BatchScan" + val fullExecName = nodeName + "Exec" override def parse: ExecInfo = { val accumId = node.metrics.find(_.name == "scan time").map(_.accumulatorId) @@ -39,8 +39,26 @@ case class BatchScanExecParser( val speedupFactor = checker.getSpeedupFactor(fullExecName) val overallSpeedup = Math.max((speedupFactor * score), 1.0) - // TODO - add in parsing expressions - average speedup across? - ExecInfo(node, sqlID, s"${node.name} ${readInfo.format}", s"Format: ${readInfo.format}", - overallSpeedup, maxDuration, node.id, score > 0, None) + // 1- Set the exec name to be the batchScan + format + // 2- If the format cannot be found, then put the entire node description to make it easy to + // troubleshoot by reading the output files. + val readFormat = readInfo.getReadFormatLC + val execExpression = if (readInfo.hasUnknownFormat) { + node.desc + } else { + s"Format: $readFormat" + } + + ExecInfo.createExecNoNode( + sqlID = sqlID, + exec = s"$nodeName $readFormat", + expr = execExpression, + speedupFactor = overallSpeedup, + duration = maxDuration, + nodeId = node.id, + opType = OpTypes.ReadExec, + isSupported = score > 0.0, + children = None, + expressions = Seq.empty) } } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/BroadcastExchangeExecParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/BroadcastExchangeExecParser.scala index f9c348ea6..e6bbc99d8 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/BroadcastExchangeExecParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/BroadcastExchangeExecParser.scala @@ -44,8 +44,7 @@ case class BroadcastExchangeExecParser( } else { (1.0, false) } - // TODO - add in parsing expressions - average speedup across? ExecInfo(node, sqlID, node.name, "", filterSpeedupFactor, - duration, node.id, isSupported, None) + duration, node.id, isSupported, children = None, expressions = Seq.empty) } } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/BroadcastHashJoinExecParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/BroadcastHashJoinExecParser.scala index 8426f1047..8acd2db7b 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/BroadcastHashJoinExecParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/BroadcastHashJoinExecParser.scala @@ -30,7 +30,7 @@ case class BroadcastHashJoinExecParser( override def parse: ExecInfo = { // BroadcastHashJoin doesn't have duration val duration = None - val exprString = node.desc.replaceFirst("BroadcastHashJoin ", "") + val exprString = node.desc.replaceFirst("^BroadcastHashJoin\\s*", "") val (expressions, supportedJoinType) = SQLPlanParser.parseEquijoinsExpressions(exprString) val notSupportedExprs = expressions.filterNot(expr => checker.isExprSupported(expr)) val (speedupFactor, isSupported) = if (checker.isExecSupported(fullExecName) && @@ -39,7 +39,7 @@ case class BroadcastHashJoinExecParser( } else { (1.0, false) } - // TODO - add in parsing expressions - average speedup across? - ExecInfo(node, sqlID, node.name, "", speedupFactor, duration, node.id, isSupported, None) + ExecInfo(node, sqlID, node.name, "", speedupFactor, duration, node.id, isSupported, + children = None, expressions = expressions) } } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/BroadcastNestedLoopJoinExecParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/BroadcastNestedLoopJoinExecParser.scala index 49f242efc..f6be5decd 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/BroadcastNestedLoopJoinExecParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/BroadcastNestedLoopJoinExecParser.scala @@ -39,7 +39,7 @@ abstract class BroadcastNestedLoopJoinExecParserBase( override def parse: ExecInfo = { // BroadcastNestedLoopJoin doesn't have duration - val exprString = node.desc.replaceFirst("BroadcastNestedLoopJoin ", "") + val exprString = node.desc.replaceFirst("^BroadcastNestedLoopJoin\\s*", "") val (buildSide, joinType) = extractBuildAndJoinTypes(exprString) val (expressions, supportedJoinType) = SQLPlanParser.parseNestedLoopJoinExpressions(exprString, buildSide, joinType) @@ -51,8 +51,8 @@ abstract class BroadcastNestedLoopJoinExecParserBase( } else { (1.0, false) } - // TODO - add in parsing expressions - average speedup across? - ExecInfo(node, sqlID, node.name, "", speedupFactor, duration, node.id, isSupported, None) + ExecInfo(node, sqlID, node.name, "", speedupFactor, duration, node.id, isSupported, + children = None, expressions = expressions) } } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/DataWritingCommandExecParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/DataWritingCommandExecParser.scala index fedbd2ceb..86e553ac1 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/DataWritingCommandExecParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/DataWritingCommandExecParser.scala @@ -37,11 +37,11 @@ case class DataWritingCommandExecParser( val duration = None val speedupFactor = checker.getSpeedupFactor(wStub.mappedExec) val finalSpeedup = if (writeSupported) speedupFactor else 1 - // TODO - add in parsing expressions - average speedup across? // We do not want to parse the node description to avoid mistakenly marking the node as RDD/UDF ExecInfo.createExecNoNode(sqlID, s"${node.name.trim} ${wStub.dataFormat.toLowerCase.trim}", s"Format: ${wStub.dataFormat.toLowerCase.trim}", - finalSpeedup, duration, node.id, opType = OpTypes.WriteExec, writeSupported, None) + finalSpeedup, duration, node.id, opType = OpTypes.WriteExec, writeSupported, + children = None, expressions = Seq.empty) } } @@ -175,4 +175,4 @@ object DataWritingCommandExecParser { parsedString.split(",")(0) // return third parameter from the input string } } -} \ No newline at end of file +} diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/DeltaLakeHelper.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/DeltaLakeHelper.scala index 82ece4f45..884ad8907 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/DeltaLakeHelper.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/DeltaLakeHelper.scala @@ -45,10 +45,10 @@ class DLWriteWithFormatAndSchemaParser(node: SparkPlanGraphNode, val finalSpeedupFactor = if (writeSupported) speedupFactor else 1.0 // execs like SaveIntoDataSourceCommand has prefix "Execute". So, we need to get rid of it. - val nodeName = node.name.replace("Execute ", "") + val nodeName = node.name.replaceFirst("Execute\\s*", "") ExecInfo.createExecNoNode(sqlID, nodeName, s"Format: $dataFormat", finalSpeedupFactor, None, node.id, OpTypes.WriteExec, - isSupported = writeSupported && isExecSupported, children = None) + isSupported = writeSupported && isExecSupported, children = None, expressions = Seq.empty) } } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ExecParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ExecParser.scala index b43d9943f..c0ea0f369 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ExecParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ExecParser.scala @@ -16,7 +16,7 @@ package com.nvidia.spark.rapids.tool.planparser -import org.apache.spark.sql.rapids.tool.UnsupportedExpr +import com.nvidia.spark.rapids.tool.planparser.ops.UnsupportedExprOpRef trait ExecParser { def parse: ExecInfo @@ -32,5 +32,6 @@ trait ExecParser { * @param expressions Array of expression strings to evaluate for support. * @return Empty Seq[UnsupportedExpr], indicating no unsupported expressions by default. */ - def getUnsupportedExprReasonsForExec(expressions: Array[String]): Seq[UnsupportedExpr] = Seq.empty + def getUnsupportedExprReasonsForExec( + expressions: Array[String]): Seq[UnsupportedExprOpRef] = Seq.empty } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/FileSourceScanExecParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/FileSourceScanExecParser.scala index 85387872f..520d05832 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/FileSourceScanExecParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/FileSourceScanExecParser.scala @@ -30,6 +30,9 @@ case class FileSourceScanExecParser( // The node name for Scans is Scan so here we hardcode val fullExecName = "FileSourceScanExec" + // Matches the first alphaneumeric characters of a string after trimming leading/trailing + // white spaces. + val nodeNameRegeX = """^\s*(\w+).*""".r override def parse: ExecInfo = { // Remove trailing spaces from node name @@ -37,7 +40,7 @@ case class FileSourceScanExecParser( val nodeName = node.name.trim val rddCheckRes = RDDCheckHelper.isDatasetOrRDDPlan(nodeName, node.desc) if (rddCheckRes.nodeNameRDD) { - // This is a scanRDD. we do not need to parse it as a normal node. + // This is a scanRDD. We do not need to parse it as a normal node. // cleanup the node name if possible: val newNodeName = if (nodeName.contains("ExistingRDD")) { val nodeNameLength = nodeName.indexOf("ExistingRDD") + "ExistingRDD".length @@ -46,7 +49,7 @@ case class FileSourceScanExecParser( nodeName } ExecInfo.createExecNoNode(sqlID, newNodeName, "", 1.0, duration = None, - node.id, OpTypes.ReadRDD, false, None) + node.id, OpTypes.ReadRDD, false, children = None, expressions = Seq.empty) } else { val accumId = node.metrics.find(_.name == "scan time").map(_.accumulatorId) val maxDuration = SQLPlanParser.getTotalDuration(accumId, app) @@ -57,14 +60,36 @@ case class FileSourceScanExecParser( // Use the default parser (fullExecName, ReadParser.parseReadNode(node)) } + // 1- Set the exec name to nodeLabel + format + // 2- If the format is not found, then put the entire node description to make it easy to + // troubleshoot by reading the output files. + val nodeLabel = nodeNameRegeX.findFirstMatchIn(nodeName) match { + case Some(m) => m.group(1) + // in case not found, use the full exec name + case None => execName + } + val readFormat = readInfo.getReadFormatLC + val exexExpr = if (readInfo.hasUnknownFormat) { + node.desc + } else { + s"Format: ${readFormat}" + } val speedupFactor = checker.getSpeedupFactor(execName) // don't use the isExecSupported because we have finer grain. val score = ReadParser.calculateReadScoreRatio(readInfo, checker) val overallSpeedup = Math.max(speedupFactor * score, 1.0) - // TODO - add in parsing expressions - average speedup across? - ExecInfo.createExecNoNode(sqlID, nodeName, "", overallSpeedup, maxDuration, - node.id, OpTypes.ReadExec, score > 0, None) + ExecInfo.createExecNoNode( + sqlID = sqlID, + exec = s"$nodeLabel $readFormat", + expr = exexExpr, + speedupFactor = overallSpeedup, + duration = maxDuration, + nodeId = node.id, + opType = OpTypes.ReadExec, + isSupported = score > 0, + children = None, + expressions = Seq.empty) } } } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/GenericExecParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/GenericExecParser.scala index 62ffb5eaa..6295c5533 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/GenericExecParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/GenericExecParser.scala @@ -16,10 +16,11 @@ package com.nvidia.spark.rapids.tool.planparser +import com.nvidia.spark.rapids.tool.planparser.ops.UnsupportedExprOpRef import com.nvidia.spark.rapids.tool.qualification.PluginTypeChecker import org.apache.spark.sql.execution.ui.SparkPlanGraphNode -import org.apache.spark.sql.rapids.tool.{AppBase, UnsupportedExpr} +import org.apache.spark.sql.rapids.tool.AppBase class GenericExecParser( val node: SparkPlanGraphNode, @@ -46,7 +47,8 @@ class GenericExecParser( (1.0, false) } - createExecInfo(speedupFactor, isSupported, duration, notSupportedExprs) + createExecInfo(speedupFactor, isSupported, duration, + notSupportedExprs = notSupportedExprs, expressions = expressions) } protected def parseExpressions(): Array[String] = { @@ -63,7 +65,7 @@ class GenericExecParser( node.desc.replaceFirst(s"^${node.name}\\s*", "") } - protected def getNotSupportedExprs(expressions: Array[String]): Seq[UnsupportedExpr] = { + protected def getNotSupportedExprs(expressions: Array[String]): Seq[UnsupportedExprOpRef] = { checker.getNotSupportedExprs(expressions) } @@ -83,7 +85,8 @@ class GenericExecParser( speedupFactor: Double, isSupported: Boolean, duration: Option[Long], - notSupportedExprs: Seq[UnsupportedExpr] + notSupportedExprs: Seq[UnsupportedExprOpRef], + expressions: Array[String] ): ExecInfo = { ExecInfo( node, @@ -95,7 +98,8 @@ class GenericExecParser( node.id, isSupported, None, - unsupportedExprs = notSupportedExprs + unsupportedExprs = notSupportedExprs, + expressions = expressions ) } } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ReadParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ReadParser.scala index 131d6b2d3..ac43bf783 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ReadParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ReadParser.scala @@ -29,11 +29,21 @@ case class ReadMetaData(schema: String, location: String, format: String, def pushedFilters: String = tags(ReadParser.METAFIELD_TAG_PUSHED_FILTERS) def dataFilters: String = tags(ReadParser.METAFIELD_TAG_DATA_FILTERS) def partitionFilters: String = tags(ReadParser.METAFIELD_TAG_PARTITION_FILTERS) + + def hasUnknownFormat: Boolean = format.equals(ReadParser.UNKNOWN_METAFIELD) + + /** + * Returns the read format in lowercase. This is used to be consistent. + * @return the lower case of the read format + */ + def getReadFormatLC: String = format.toLowerCase } object ReadParser extends Logging { // It was found that some eventlogs could have "NativeScan" instead of "Scan" val SCAN_NODE_PREFIXES = Seq("Scan", "NativeScan") + // Do not include OneRowRelation in the scan nodes, consider it as regular Exec + val SCAN_ONE_ROW_RELATION = "Scan OneRowRelation" // DatasourceV2 node names that exactly match the following labels val DATASOURCE_V2_NODE_EXACT_PREF = Set( "BatchScan") @@ -58,7 +68,7 @@ object ReadParser extends Logging { ) def isScanNode(nodeName: String): Boolean = { - SCAN_NODE_PREFIXES.exists(nodeName.startsWith(_)) + SCAN_NODE_PREFIXES.exists(nodeName.startsWith(_)) && !nodeName.startsWith(SCAN_ONE_ROW_RELATION) } def isScanNode(node: SparkPlanGraphNode): Boolean = { diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SQLPlanParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SQLPlanParser.scala index ad2634c41..17159842b 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SQLPlanParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SQLPlanParser.scala @@ -21,16 +21,18 @@ import scala.collection.mutable.{ArrayBuffer, WeakHashMap} import scala.util.control.NonFatal import scala.util.matching.Regex +import com.nvidia.spark.rapids.tool.planparser.ops.{OperatorRefBase, OpRef, UnsupportedExprOpRef} import com.nvidia.spark.rapids.tool.planparser.photon.{PhotonPlanParser, PhotonStageExecParser} import com.nvidia.spark.rapids.tool.qualification.PluginTypeChecker import org.apache.spark.internal.Logging import org.apache.spark.sql.execution.SparkPlanInfo import org.apache.spark.sql.execution.ui.{SparkPlanGraph, SparkPlanGraphCluster, SparkPlanGraphNode} -import org.apache.spark.sql.rapids.tool.{AppBase, BuildSide, ExecHelper, JoinType, RDDCheckHelper, ToolUtils, UnsupportedExpr} +import org.apache.spark.sql.rapids.tool.{AppBase, BuildSide, ExecHelper, JoinType, RDDCheckHelper, ToolUtils} import org.apache.spark.sql.rapids.tool.util.ToolsPlanGraph import org.apache.spark.sql.rapids.tool.util.plangraph.{PhotonSparkPlanGraphCluster, PhotonSparkPlanGraphNode} + object OpActions extends Enumeration { type OpAction = Value val NONE, IgnoreNoPerf, IgnorePerf, Triage = Value @@ -73,11 +75,10 @@ object UnsupportedReasons extends Enumeration { case class UnsupportedExecSummary( sqlId: Long, execId: Long, - execValue: String, + execRef: OperatorRefBase, opType: OpTypes.OpType, reason: UnsupportedReasons.UnsupportedReason, - opAction: OpActions.OpAction, - isExpression: Boolean = false) { + opAction: OpActions.OpAction) { val finalOpType: String = if (opType.equals(OpTypes.UDF) || opType.equals(OpTypes.DataSet)) { s"${OpTypes.Exec.toString}" @@ -85,14 +86,16 @@ case class UnsupportedExecSummary( s"${opType.toString}" } - val unsupportedOperator: String = execValue + val unsupportedOperatorCSVFormat: String = execRef.getOpNameCSV val details: String = UnsupportedReasons.reportUnsupportedReason(reason) + + def isExpression: Boolean = execRef.isInstanceOf[UnsupportedExprOpRef] } case class ExecInfo( sqlID: Long, - exec: String, + execRef: OpRef, expr: String, speedupFactor: Double, duration: Option[Long], @@ -103,10 +106,11 @@ case class ExecInfo( var stages: Set[Int], var shouldRemove: Boolean, var unsupportedExecReason: String, - unsupportedExprs: Seq[UnsupportedExpr], + unsupportedExprs: Seq[UnsupportedExprOpRef], dataSet: Boolean, udf: Boolean, - shouldIgnore: Boolean) { + shouldIgnore: Boolean, + expressions: Seq[OpRef]) { private def childrenToString = { val str = children.map { c => @@ -119,6 +123,12 @@ case class ExecInfo( } } + def exec: String = execRef.value + + def isClusterNode: Boolean = { + execRef.getOpName.contains("StageCodegen") || execRef.getOpName.contains("PhotonResultStage") + } + override def toString: String = { s"exec: $exec, expr: $expr, sqlID: $sqlID , speedupFactor: $speedupFactor, " + s"duration: $duration, nodeId: $nodeId, " + @@ -194,7 +204,7 @@ case class ExecInfo( getUnsupportedReason) // Initialize the result with the exec summary - val res = ArrayBuffer(UnsupportedExecSummary(sqlID, execId, exec, opType, + val res = ArrayBuffer(UnsupportedExecSummary(sqlID, execId, execRef, opType, execUnsupportedReason, getOpAction)) // TODO: Should we iterate on exec children? @@ -211,8 +221,8 @@ case class ExecInfo( unsupportedExprs.foreach { expr => val exprUnsupportedReason = determineUnsupportedReason(expr.unsupportedReason, exprKnownReason) - res += UnsupportedExecSummary(sqlID, execId, expr.exprName, OpTypes.Expr, - exprUnsupportedReason, getOpAction, isExpression = true) + res += UnsupportedExecSummary(sqlID, execId, expr, OpTypes.Expr, + exprUnsupportedReason, getOpAction) } } res @@ -235,9 +245,10 @@ object ExecInfo { stages: Set[Int] = Set.empty, shouldRemove: Boolean = false, unsupportedExecReason: String = "", - unsupportedExprs: Seq[UnsupportedExpr] = Seq.empty, + unsupportedExprs: Seq[UnsupportedExprOpRef] = Seq.empty, dataSet: Boolean = false, - udf: Boolean = false): ExecInfo = { + udf: Boolean = false, + expressions: Seq[String]): ExecInfo = { // Set the ignoreFlag // 1- we ignore any exec with UDF // 2- we ignore any exec with dataset @@ -259,7 +270,7 @@ object ExecInfo { val supportedFlag = isSupported && !udf && !finalDataSet ExecInfo( sqlID, - exec, + OpRef.fromExec(exec), expr, speedupFactor, duration, @@ -273,7 +284,9 @@ object ExecInfo { unsupportedExprs, finalDataSet, udf, - shouldIgnore + shouldIgnore, + // convert array of string expressions to OpRefs + expressions = expressions.map(OpRef.fromExpr) ) } @@ -290,10 +303,11 @@ object ExecInfo { stages: Set[Int] = Set.empty, shouldRemove: Boolean = false, unsupportedExecReason:String = "", - unsupportedExprs: Seq[UnsupportedExpr] = Seq.empty, + unsupportedExprs: Seq[UnsupportedExprOpRef] = Seq.empty, dataSet: Boolean = false, udf: Boolean = false, - opType: OpTypes.OpType = OpTypes.Exec): ExecInfo = { + opType: OpTypes.OpType = OpTypes.Exec, + expressions: Seq[String]): ExecInfo = { // Some execs need to be trimmed such as "Scan" // Example: Scan parquet . -> Scan parquet. // scan nodes needs trimming @@ -307,7 +321,7 @@ object ExecInfo { // if the expression is RDD because of the node name, then we do not want to add the // unsupportedExpressions because it becomes bogus. val finalUnsupportedExpr = if (rddCheckRes.nodeDescRDD) { - Seq.empty[UnsupportedExpr] + Seq.empty[UnsupportedExprOpRef] } else { unsupportedExprs } @@ -326,7 +340,8 @@ object ExecInfo { unsupportedExecReason, finalUnsupportedExpr, ds, - containsUDF + containsUDF, + expressions = expressions ) } } @@ -335,8 +350,18 @@ case class PlanInfo( appID: String, sqlID: Long, sqlDesc: String, - execInfo: Seq[ExecInfo] -) + execInfo: Seq[ExecInfo]) { + def getUnsupportedExpressions: Seq[OperatorRefBase] = { + execInfo.flatMap { e => + if (e.isClusterNode) { + // wholeStageCodeGen does not have expressions/unsupported-expressions + e.children.getOrElse(Seq.empty).flatMap(_.unsupportedExprs) + } else { + e.unsupportedExprs + } + } + } +} object SQLPlanParser extends Logging { @@ -528,7 +553,8 @@ object SQLPlanParser extends Logging { // supported but with shouldRemove flag set to True. // Setting the "shouldRemove" is handled at the end of the function. ExecInfo(node, sqlID, normalizedNodeName, expr = "", 1, duration = None, node.id, - isSupported = reuseExecs.contains(normalizedNodeName), None) + isSupported = reuseExecs.contains(normalizedNodeName), children = None, + expressions = Seq.empty) } } @@ -584,7 +610,8 @@ object SQLPlanParser extends Logging { logWarning(s"Unexpected error parsing plan node ${normalizedNodeName}. " + s" sqlID = ${sqlID}", e) ExecInfo(node, sqlID, normalizedNodeName, expr = "", 1, duration = None, node.id, - isSupported = false, None) + isSupported = false, children = None, + expressions = Seq.empty) } val stagesInNode = nodeIdToStagesFunc(node.id) execInfo.setStages(stagesInNode) diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ShuffleExchangeExecParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ShuffleExchangeExecParser.scala index 2a1315718..2026a2a17 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ShuffleExchangeExecParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ShuffleExchangeExecParser.scala @@ -44,7 +44,7 @@ case class ShuffleExchangeExecParser( } else { (1.0, false) } - // TODO - add in parsing expressions - average speedup across? - ExecInfo(node, sqlID, node.name, "", filterSpeedupFactor, duration, node.id, isSupported, None) + ExecInfo(node, sqlID, node.name, "", filterSpeedupFactor, duration, node.id, isSupported, + children = None, expressions = Seq.empty) } } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ShuffledHashJoinExecParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ShuffledHashJoinExecParser.scala index b81f33fd6..4c90928a4 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ShuffledHashJoinExecParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ShuffledHashJoinExecParser.scala @@ -43,9 +43,7 @@ case class ShuffledHashJoinExecParser( } else { (1.0, false) } - - // TODO - add in parsing expressions - average speedup across? ExecInfo(node, sqlID, node.name, "", speedupFactor, - maxDuration, node.id, isSupported, None) + maxDuration, node.id, isSupported, children = None, expressions = expressions) } } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SortMergeJoinExecParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SortMergeJoinExecParser.scala index f98a0542b..4828d8ac9 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SortMergeJoinExecParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SortMergeJoinExecParser.scala @@ -42,8 +42,8 @@ case class SortMergeJoinExecParser( } else { (1.0, false) } - // TODO - add in parsing expressions - average speedup across? - ExecInfo(node, sqlID, opName, "", speedupFactor, duration, node.id, isSupported, None) + ExecInfo(node, sqlID, opName, "", speedupFactor, duration, node.id, isSupported, + children = None, expressions = expressions) } } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SubqueryBroadcastExecParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SubqueryBroadcastExecParser.scala index 64fc5ff5e..048a317b0 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SubqueryBroadcastExecParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SubqueryBroadcastExecParser.scala @@ -38,8 +38,7 @@ case class SubqueryBroadcastExecParser( } else { (1.0, false) } - // TODO - check is broadcast associated can be replaced - // TODO - add in parsing expressions - average speedup across? - ExecInfo(node, sqlID, node.name, "", filterSpeedupFactor, duration, node.id, isSupported, None) + ExecInfo(node, sqlID, node.name, "", filterSpeedupFactor, duration, node.id, isSupported, + children = None, expressions = Seq.empty) } } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SubqueryExecParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SubqueryExecParser.scala index c60eff7ac..e01f7a27a 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SubqueryExecParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SubqueryExecParser.scala @@ -39,7 +39,8 @@ case class SubqueryExecParser( // TODO: Should we also collect the "data size" metric? val duration = SQLPlanParser.getDriverTotalDuration(collectTimeId, app) // should remove is kept in 1 place. So no need to set it here. - ExecInfo(node, sqlID, node.name, "", 1.0, duration, node.id, isSupported = false, None) + ExecInfo(node, sqlID, node.name, "", 1.0, duration, node.id, isSupported = false, + children = None, expressions = Seq.empty) } } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/WholeStageExecParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/WholeStageExecParser.scala index cdef3b225..5b8730938 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/WholeStageExecParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/WholeStageExecParser.scala @@ -31,6 +31,9 @@ abstract class WholeStageExecParserBase( nodeIdToStagesFunc: Long => Set[Int]) extends Logging { val fullExecName = "WholeStageCodegenExec" + // Matches the first alphanumeric characters of a string after trimming leading/trailing + // white spaces. + val nodeNameRegeX = """^\s*(\w+).*""".r def parse: Seq[ExecInfo] = { // TODO - does metrics for time have previous ops? per op thing, only some do @@ -50,17 +53,34 @@ abstract class WholeStageExecParserBase( } // if any of the execs in WholeStageCodegen supported mark this entire thing as supported val anySupported = childNodes.exists(_.isSupported == true) - val unSupportedExprsArray = - childNodes.filter(_.unsupportedExprs.nonEmpty).flatMap(x => x.unsupportedExprs).toArray // average speedup across the execs in the WholeStageCodegen for now val supportedChildren = childNodes.filterNot(_.shouldRemove) val avSpeedupFactor = SQLPlanParser.averageSpeedup(supportedChildren.map(_.speedupFactor)) // The node should be marked as shouldRemove when all the children of the // wholeStageCodeGen are marked as shouldRemove. val removeNode = isDupNode || childNodes.forall(_.shouldRemove) - val execInfo = ExecInfo(node, sqlID, node.name, node.name, avSpeedupFactor, maxDuration, - node.id, anySupported, Some(childNodes), stagesInNode, - shouldRemove = removeNode, unsupportedExprs = unSupportedExprsArray) + // Remove any suffix in order to get the node label without any trailing number. + val nodeLabel = nodeNameRegeX.findFirstMatchIn(node.name) match { + case Some(m) => m.group(1) + // in case not found, use the full exec name + case None => fullExecName + } + val execInfo = ExecInfo( + node = node, + sqlID = sqlID, + exec = nodeLabel, + expr = node.name, + speedupFactor = avSpeedupFactor, + duration = maxDuration, + nodeId = node.id, + isSupported = anySupported, + children = Some(childNodes), + stages = stagesInNode, + shouldRemove = removeNode, + // unsupported expressions should not be set for the cluster nodes. + unsupportedExprs = Seq.empty, + // expressions of wholeStageCodeGen should not be set. They belong to the children nodes. + expressions = Seq.empty) Seq(execInfo) } } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/WindowGroupLimitParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/WindowGroupLimitParser.scala index 01b5edc3d..853c1b767 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/WindowGroupLimitParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/WindowGroupLimitParser.scala @@ -16,10 +16,10 @@ package com.nvidia.spark.rapids.tool.planparser +import com.nvidia.spark.rapids.tool.planparser.ops.UnsupportedExprOpRef import com.nvidia.spark.rapids.tool.qualification.PluginTypeChecker import org.apache.spark.sql.execution.ui.SparkPlanGraphNode -import org.apache.spark.sql.rapids.tool.UnsupportedExpr case class WindowGroupLimitParser( node: SparkPlanGraphNode, @@ -36,10 +36,10 @@ case class WindowGroupLimitParser( } override def getUnsupportedExprReasonsForExec( - expressions: Array[String]): Seq[UnsupportedExpr] = { + expressions: Array[String]): Seq[UnsupportedExprOpRef] = { expressions.flatMap { expr => if (!supportedRankingExprs.contains(expr)) { - Some(UnsupportedExpr(expr, + Some(UnsupportedExprOpRef(expr, s"Ranking function $expr is not supported in $fullExecName")) } else { None @@ -57,7 +57,7 @@ case class WindowGroupLimitParser( * 3. Ranking function is supported by plugin's implementation of WindowGroupLimitExec. */ override def parse: ExecInfo = { - val exprString = node.desc.replaceFirst("WindowGroupLimit ", "") + val exprString = node.desc.replaceFirst("WindowGroupLimit\\s*", "") val expressions = SQLPlanParser.parseWindowGroupLimitExpressions(exprString) val notSupportedExprs = checker.getNotSupportedExprs(expressions) ++ getUnsupportedExprReasonsForExec(expressions) @@ -69,8 +69,7 @@ case class WindowGroupLimitParser( } else { (1.0, false) } - // TODO - add in parsing expressions - average speedup across? ExecInfo(node, sqlID, node.name, "", speedupFactor, None, node.id, isSupported, None, - unsupportedExprs = notSupportedExprs) + unsupportedExprs = notSupportedExprs, expressions = expressions) } } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/WriteFilesExecParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/WriteFilesExecParser.scala index bcd2272e0..0fa6cb254 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/WriteFilesExecParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/WriteFilesExecParser.scala @@ -44,7 +44,10 @@ case class WriteFilesExecParser( "", speedupFactor, duration, - node.id, opType = OpTypes.WriteExec, true, None) + node.id, opType = OpTypes.WriteExec, + isSupported = true, + children = None, + expressions = Seq.empty) } } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/OpRef.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/OpRef.scala new file mode 100644 index 000000000..3e5f22c08 --- /dev/null +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/OpRef.scala @@ -0,0 +1,64 @@ +/* + * Copyright (c) 2024, NVIDIA CORPORATION. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package com.nvidia.spark.rapids.tool.planparser.ops + +import java.util.concurrent.ConcurrentHashMap + +import com.nvidia.spark.rapids.tool.planparser.OpTypes + + +/** + * A reference to an operator(either Exec operator or expression operator) in a Spark plan. + * + * @param value The name of the operator. + * @param opType The type of the operator (e.g., Exec, Expr). + */ +case class OpRef(override val value: String, + override val opType: OpTypes.OpType) extends OperatorRefBase(value, opType) + +object OpRef { + // Dummy OpNameRef to represent None accumulator names. This is an optimization to avoid + // storing an option[string] for all operator names which leads to "get-or-else" everywhere. + private val EMPTY_OP_NAME_REF: OpRef = new OpRef("", OpTypes.Exec) + // A global table to store reference to all operator names. The map is accessible by all + // threads (different applications) running in parallel. This avoids duplicate work across + // different threads. + val OP_NAMES: ConcurrentHashMap[String, OpRef] = { + val initMap = new ConcurrentHashMap[String, OpRef]() + initMap.put(EMPTY_OP_NAME_REF.value, EMPTY_OP_NAME_REF) + // Add the operator to the map because it is being used internally. + initMap + } + + /** + * Retrieves an `OpRef` for an expression operator. + * If the operator name already exists in the cache, it returns the existing `OpRef`. + * Otherwise, it creates a new `OpRef` with the given name and `OpTypes.Expr`. + */ + def fromExpr(name: String): OpRef = { + OP_NAMES.computeIfAbsent(name, OpRef.apply(_, OpTypes.Expr)) + } + + /** + * Retrieves an `OpRef` for an exec operator. + * If the operator name already exists in the cache, it returns the existing `OpRef`. + * Otherwise, it creates a new `OpRef` with the given name and `OpTypes.Exec`. + */ + def fromExec(name: String): OpRef = { + OP_NAMES.computeIfAbsent(name, OpRef.apply(_, OpTypes.Exec)) + } +} diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/OperatorCounter.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/OperatorCounter.scala new file mode 100644 index 000000000..fab9422aa --- /dev/null +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/OperatorCounter.scala @@ -0,0 +1,106 @@ +/* + * Copyright (c) 2024, NVIDIA CORPORATION. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package com.nvidia.spark.rapids.tool.planparser.ops + +import scala.collection.mutable + +import com.nvidia.spark.rapids.tool.planparser.{ExecInfo, PlanInfo} + +/** + * `OperatorCounter` is responsible for counting the occurrences of execs and expressions + * in a given execution plan (`PlanInfo`). It maintains counts separately for supported and + * unsupported execs and expressions. + * + * @param planInfo The execution plan information to analyze. + */ +case class OperatorCounter(planInfo: PlanInfo) { + + /** + * Represents data for an exec or expression, including its reference, + * occurrence count, and stages where it appears. + * + * @param opRef The operator reference. + * @param count The number of times the operator appears. + * @param stages The set of stages where the operator appears. + */ + case class OperatorData( + opRef: OperatorRefBase, + var count: Int = 0, + var stages: Set[Int] = Set()) + + // Summarizes the count information for an exec or expression, including whether it is supported. + case class OperatorCountSummary( + opData: OperatorData, + isSupported: Boolean) + + private val supportedMap: mutable.Map[OperatorRefBase, OperatorData] = mutable.Map() + private val unsupportedMap: mutable.Map[OperatorRefBase, OperatorData] = mutable.Map() + + // Returns a sequence of `OperatorCountSummary`, combining both supported and + // unsupported operators. + def getOpsCountSummary(): Seq[OperatorCountSummary] = { + supportedMap.values.map(OperatorCountSummary(_, isSupported = true)).toSeq ++ + unsupportedMap.values.map(OperatorCountSummary(_, isSupported = false)).toSeq + } + + + // Updates the operator data in the given map (supported or unsupported). + // Increments the count and updates the stages where the operator appears. + private def updateOpRefEntry(opRef: OperatorRefBase, stages: Set[Int], + targetMap: mutable.Map[OperatorRefBase, OperatorData]): Unit = { + val operatorData = targetMap.getOrElseUpdate(opRef, OperatorData(opRef)) + operatorData.count += 1 + operatorData.stages ++= stages + } + + // Processes an `ExecInfo` node to update exec and expression counts. + // Separates supported and unsupported execs and expressions into their respective maps. + private def processExecInfo(execInfo: ExecInfo): Unit = { + val opMap = execInfo.isSupported match { + case true => supportedMap + case false => unsupportedMap + } + updateOpRefEntry(execInfo.execRef, execInfo.stages, opMap) + // update the map for supported expressions. We should exclude the unsupported expressions. + execInfo.expressions.filterNot( + e => execInfo.unsupportedExprs.exists(exp => exp.opRef.equals(e))).foreach { expr => + updateOpRefEntry(expr, execInfo.stages, supportedMap) + } + // update the map for unsupported expressions + execInfo.unsupportedExprs.foreach { expr => + updateOpRefEntry(expr, execInfo.stages, unsupportedMap) + } + } + + // Counts the execs and expressions in the execution plan. + private def countOperators(): Unit = { + planInfo.execInfo.foreach { exec => + exec.isClusterNode match { + // we do not want to count the cluster nodes in that aggregation + case true => + if (exec.children.nonEmpty) { + exec.children.get.foreach { child => + processExecInfo(child) + } + } + case false => processExecInfo(exec) + } + } + } + + countOperators() +} diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/OperatorRefBase.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/OperatorRefBase.scala new file mode 100644 index 000000000..04bd9a190 --- /dev/null +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/OperatorRefBase.scala @@ -0,0 +1,41 @@ +/* + * Copyright (c) 2024, NVIDIA CORPORATION. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package com.nvidia.spark.rapids.tool.planparser.ops + +import com.nvidia.spark.rapids.tool.planparser.OpTypes + +import org.apache.spark.sql.rapids.tool.util.StringUtils + +/** + * Base class representing a reference to an operator (either exec operator or expression operator). + * It provides methods to retrieve the operator's name and type in both raw and + * CSV-friendly formats. + * + * @param value The name of the operator. + * @param opType The type of the operator (e.g., Exec, Expr). + */ + +class OperatorRefBase(val value: String, val opType: OpTypes.OpType) extends OperatorRefTrait { + // Preformatted values for CSV output to avoid reformatting multiple times. + val csvValue: String = StringUtils.reformatCSVString(value) + val csvOpType: String = StringUtils.reformatCSVString(opType.toString) + + override def getOpName: String = value + override def getOpNameCSV: String = csvValue + override def getOpType: String = opType.toString + override def getOpTypeCSV: String = csvOpType +} diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/OperatorRefTrait.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/OperatorRefTrait.scala new file mode 100644 index 000000000..40385ba7a --- /dev/null +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/OperatorRefTrait.scala @@ -0,0 +1,24 @@ +/* + * Copyright (c) 2024, NVIDIA CORPORATION. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package com.nvidia.spark.rapids.tool.planparser.ops + +trait OperatorRefTrait { + def getOpName: String + def getOpNameCSV: String + def getOpType: String + def getOpTypeCSV: String +} diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/UnsupportedExprOpRef.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/UnsupportedExprOpRef.scala new file mode 100644 index 000000000..0e17d8f0d --- /dev/null +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/UnsupportedExprOpRef.scala @@ -0,0 +1,43 @@ +/* + * Copyright (c) 2024, NVIDIA CORPORATION. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package com.nvidia.spark.rapids.tool.planparser.ops + + +/** + * Represents a reference to an unsupported expression operator. + * Extends `OperatorRefBase` and includes a reason why the expression is unsupported. + * + * @param opRef The underlying `OpRef` for the expression. + * @param unsupportedReason A string describing why the expression is unsupported. + */ +case class UnsupportedExprOpRef(opRef: OpRef, + unsupportedReason: String) extends OperatorRefBase(opRef.value, opRef.opType) + +// Provides a factory method to create an instance from an expression name and unsupported reason. +object UnsupportedExprOpRef { + /** + * Creates an `UnsupportedExprOpRef` for the given expression name and unsupported reason. + * + * @param exprName The name of the unsupported expression. + * @param unsupportedReason A string describing why the expression is unsupported. + * @return An instance of `UnsupportedExprOpRef`. + */ + def apply(exprName: String, unsupportedReason: String): UnsupportedExprOpRef = { + val opRef = OpRef.fromExpr(exprName) + UnsupportedExprOpRef(opRef, unsupportedReason) + } +} diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/PluginTypeChecker.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/PluginTypeChecker.scala index f04ddcac7..44bbf9fa3 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/PluginTypeChecker.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/PluginTypeChecker.scala @@ -21,11 +21,11 @@ import scala.io.BufferedSource import scala.util.control.NonFatal import com.nvidia.spark.rapids.tool.{Platform, PlatformFactory} +import com.nvidia.spark.rapids.tool.planparser.ops.UnsupportedExprOpRef import org.apache.hadoop.conf.Configuration import org.apache.hadoop.fs.{FileSystem, Path} import org.apache.spark.internal.Logging -import org.apache.spark.sql.rapids.tool.UnsupportedExpr import org.apache.spark.sql.rapids.tool.util.UTF8Source object OpSuppLevel extends Enumeration { @@ -387,11 +387,11 @@ class PluginTypeChecker(platform: Platform = PlatformFactory.createInstance(), exprSupported.isSupported } - def getNotSupportedExprs(exprs: Seq[String]): Seq[UnsupportedExpr] = { + def getNotSupportedExprs(exprs: Seq[String]): Seq[UnsupportedExprOpRef] = { exprs.collect { case expr if !isExprSupported(expr) => val reason = unsupportedOpsReasons.getOrElse(expr, "") - UnsupportedExpr(expr, reason) + UnsupportedExprOpRef(expr, reason) } } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/QualOutputWriter.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/QualOutputWriter.scala index ed101d820..9dbe7c920 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/QualOutputWriter.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/QualOutputWriter.scala @@ -23,6 +23,7 @@ import scala.collection.mutable.{Buffer, LinkedHashMap, ListBuffer} import com.nvidia.spark.rapids.tool.ToolTextFileWriter import com.nvidia.spark.rapids.tool.planparser.{DatabricksParseHelper, ExecInfo, PlanInfo, UnsupportedExecSummary} +import com.nvidia.spark.rapids.tool.planparser.ops.OperatorCounter import com.nvidia.spark.rapids.tool.profiling.AppStatusResult import com.nvidia.spark.rapids.tool.profiling.ProfileUtils.replaceDelimiter import com.nvidia.spark.rapids.tool.qualification.QualOutputWriter.{CLUSTER_ID, CLUSTER_ID_STR_SIZE, JOB_ID, JOB_ID_STR_SIZE, RUN_NAME, RUN_NAME_STR_SIZE, TEXT_DELIMITER} @@ -172,6 +173,24 @@ class QualOutputWriter(outputDir: String, reportReadSchema: Boolean, } } + def writeAllOpsSummaryCSVReport( + sums: Seq[QualificationSummaryInfo]): Unit = { + val csvFileWriter = new ToolTextFileWriter(outputDir, + s"${QualOutputWriter.LOGFILE_NAME}_operatorsStats.csv", + "All Operators CSV Report", hadoopConf) + try { + val headersAndSizes = QualOutputWriter.getAllOperatorsHeaderStrings + csvFileWriter.write(QualOutputWriter.constructOutputRowFromMap(headersAndSizes, + QualOutputWriter.CSV_DELIMITER)) + sums.foreach { sum => + QualOutputWriter.constructAllOperatorsInfo(csvFileWriter, sum.planInfo, sum.appId, + QualOutputWriter.CSV_DELIMITER) + } + } finally { + csvFileWriter.close() + } + } + def writePerSqlCSVReport(sums: Seq[QualificationSummaryInfo], maxSQLDescLength: Int): Unit = { val csvFileWriter = new ToolTextFileWriter(outputDir, s"${QualOutputWriter.LOGFILE_NAME}_persql.csv", @@ -282,7 +301,7 @@ class QualOutputWriter(outputDir: String, reportReadSchema: Boolean, } else { ("", "") } - Seq(appIDCSVStr, sqlIDStr, StringUtils.reformatCSVString(info.exec), + Seq(appIDCSVStr, sqlIDStr, info.execRef.getOpNameCSV, StringUtils.reformatCSVString(info.expr), if (info.duration.isDefined) info.duration.get.toString else zeroDurationStr, info.nodeId.toString, @@ -445,6 +464,11 @@ object QualOutputWriter { val UNSUPPORTED_TASK_DURATION_STR = "Unsupported Task Duration" val SUPPORTED_SQL_TASK_DURATION_STR = "Supported SQL DF Task Duration" val LONGEST_SQL_DURATION_STR = "Longest SQL Duration" + val OPERATOR_TYPE = "Operator Type" + val OPERATOR_NAME = "Operator Name" + val COUNT = "Count" + val IS_SUPPORTED = "Supported" + val STAGES = "Stages" val EXEC_STR = "Exec Name" val EXPR_STR = "Expression Name" val EXEC_DURATION = "Exec Duration" @@ -838,6 +862,49 @@ object QualOutputWriter { mutable.LinkedHashMap(headersAndFields: _*) } + private def getAllOperatorsHeaderStrings: LinkedHashMap[String, Int] = { + val detailedHeaderAndFields = LinkedHashMap[String, Int]( + APP_ID_STR -> APP_ID_STR.size, + SQL_ID_STR -> SQL_ID_STR.size, + OPERATOR_TYPE -> OPERATOR_TYPE.size, + OPERATOR_NAME -> OPERATOR_NAME.size, + COUNT -> COUNT.size, + IS_SUPPORTED -> IS_SUPPORTED.size, + STAGES -> STAGES.size + ) + detailedHeaderAndFields + } + + private def constructAllOperatorsInfo( + csvWriter: ToolTextFileWriter, + planInfos: Seq[PlanInfo], + appId: String, + delimiter: String): Unit = { + // This method iterates on PlanInfo which are sorted by SqlID. It constructs the operators per + // SQLPlan and sumps it to the CSV as a bufferedString instead of writing one row at a time. + val appIDCSVStr = StringUtils.reformatCSVString(appId) + val supportedCSVStr = "true" + val unsupportedCSVStr = "false" + planInfos.foreach { planInfo => + val sqlIDCSVStr = planInfo.sqlID.toString + val allOpsCount = OperatorCounter(planInfo) + .getOpsCountSummary().sortBy(oInfo => (-oInfo.opData.count, oInfo.opData.opRef.getOpName)) + if (allOpsCount.nonEmpty) { + val planBuffer = allOpsCount.map { opInfo => + val supportFlag = if (opInfo.isSupported) supportedCSVStr else unsupportedCSVStr + val stageStr = StringUtils.reformatCSVString(opInfo.opData.stages.mkString(":")) + s"$appIDCSVStr$delimiter" + + s"$sqlIDCSVStr$delimiter" + + s"${opInfo.opData.opRef.getOpTypeCSV}$delimiter" + + s"${opInfo.opData.opRef.getOpNameCSV}$delimiter${opInfo.opData.count}$delimiter" + + s"$supportFlag$delimiter" + + s"$stageStr" + } + csvWriter.write(s"${planBuffer.mkString("\n")}\n") + } + } + } + def constructClusterInfo( sumInfo: QualificationSummaryInfo, headersAndSizes: LinkedHashMap[String, Int], @@ -940,7 +1007,7 @@ object QualOutputWriter { // need to remove the WholeStageCodegen wrappers since they aren't actual // execs that we want to get timings of execs.flatMap { e => - if (e.exec.contains("WholeStageCodegen")) { + if (e.isClusterNode) { e.children.getOrElse(Seq.empty) } else { e.children.getOrElse(Seq.empty) :+ e @@ -1048,7 +1115,7 @@ object QualOutputWriter { stageId.toString -> headersAndSizes(STAGE_ID_STR), reformatCSVFunc(unSupExecInfo.execId.toString) -> headersAndSizes(EXEC_ID), reformatCSVFunc(unSupExecInfo.finalOpType) -> headersAndSizes(UNSUPPORTED_TYPE), - reformatCSVFunc(unSupExecInfo.unsupportedOperator) -> headersAndSizes(UNSUPPORTED_OPERATOR), + unSupExecInfo.unsupportedOperatorCSVFormat -> headersAndSizes(UNSUPPORTED_OPERATOR), reformatCSVFunc(unSupExecInfo.details) -> headersAndSizes(DETAILS), stageAppDuration.toString -> headersAndSizes(STAGE_WALLCLOCK_DUR_STR), appDuration.toString -> headersAndSizes(APP_DUR_STR), diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/Qualification.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/Qualification.scala index 49d70b80e..fa59e8b3e 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/Qualification.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/Qualification.scala @@ -255,6 +255,7 @@ class Qualification(outputPath: String, numRows: Int, hadoopConf: Configuration, qWriter.writeExecReport(allAppsSum) qWriter.writeStageReport(allAppsSum, order) qWriter.writeUnsupportedOpsSummaryCSVReport(allAppsSum) + qWriter.writeAllOpsSummaryCSVReport(allAppsSum) val appStatusResult = generateStatusResults(appStatusReporter.asScala.values.toSeq) logOutputPath() qWriter.writeStatusReport(appStatusResult, order) diff --git a/core/src/main/scala/org/apache/spark/sql/rapids/tool/AppBase.scala b/core/src/main/scala/org/apache/spark/sql/rapids/tool/AppBase.scala index f8d4d7703..b90917cd8 100644 --- a/core/src/main/scala/org/apache/spark/sql/rapids/tool/AppBase.scala +++ b/core/src/main/scala/org/apache/spark/sql/rapids/tool/AppBase.scala @@ -378,11 +378,11 @@ abstract class AppBase( allMetaWithSchema.foreach { plan => val meta = plan.metadata val readSchema = ReadParser.formatSchemaStr(meta.getOrElse("ReadSchema", "")) - val scanNode = allNodes.filter(node => { + val scanNode = allNodes.filter(ReadParser.isScanNode(_)).filter(node => { // Get ReadSchema of each Node and sanitize it for comparison val trimmedNode = AppBase.trimSchema(ReadParser.parseReadNode(node).schema) readSchema.contains(trimmedNode) - }).filter(ReadParser.isScanNode(_)) + }) // If the ReadSchema is empty or if it is PhotonScan, then we don't need to // add it to the dataSourceInfo diff --git a/core/src/main/scala/org/apache/spark/sql/rapids/tool/ToolUtils.scala b/core/src/main/scala/org/apache/spark/sql/rapids/tool/ToolUtils.scala index fc276a064..021337495 100644 --- a/core/src/main/scala/org/apache/spark/sql/rapids/tool/ToolUtils.scala +++ b/core/src/main/scala/org/apache/spark/sql/rapids/tool/ToolUtils.scala @@ -401,8 +401,6 @@ object ExecHelper { } } -case class UnsupportedExpr(exprName: String, unsupportedReason: String) - object MlOps { val sparkml = "spark.ml." val xgBoost = "spark.XGBoost" diff --git a/core/src/main/scala/org/apache/spark/sql/rapids/tool/qualification/QualificationAppInfo.scala b/core/src/main/scala/org/apache/spark/sql/rapids/tool/qualification/QualificationAppInfo.scala index 887075c8c..1ef8b7315 100644 --- a/core/src/main/scala/org/apache/spark/sql/rapids/tool/qualification/QualificationAppInfo.scala +++ b/core/src/main/scala/org/apache/spark/sql/rapids/tool/qualification/QualificationAppInfo.scala @@ -281,7 +281,7 @@ class QualificationAppInfo( // need to remove the WholeStageCodegen wrappers since they aren't actual // execs that we want to get timings of execs.flatMap { e => - if (e.exec.contains("WholeStageCodegen")) { + if (e.isClusterNode) { e.children.getOrElse(Seq.empty) } else { e.children.getOrElse(Seq.empty) :+ e @@ -573,7 +573,7 @@ class QualificationAppInfo( val unSupportedExecs = planInfos.flatMap { p => // WholeStageCodeGen is excluded from the result. val topLevelExecs = p.execInfo.filterNot(_.isSupported).filterNot( - x => x.exec.startsWith("WholeStage")) + x => x.isClusterNode) val childrenExecs = p.execInfo.flatMap { e => e.children.map(x => x.filterNot(_.isSupported)) }.flatten @@ -581,9 +581,8 @@ class QualificationAppInfo( }.map(_.exec).toSet.mkString(";").trim.replaceAll("\n", "").replace(",", ":") // Get all the unsupported Expressions from the plan - val unSupportedExprs = origPlanInfos.map(_.execInfo.flatMap( - _.unsupportedExprs.map(_.exprName))).flatten.filter(_.nonEmpty).toSet.mkString(";") - .trim.replaceAll("\n", "").replace(",", ":") + val unSupportedExprs = origPlanInfos.flatMap(p => p.getUnsupportedExpressions) + .map(s => s.getOpName).toSet.mkString(";").trim.replaceAll("\n", "").replace(",", ":") // TODO - this is not correct as this is using the straight stage wall // clock time and hasn't been adjusted to the app duration wall clock diff --git a/core/src/test/resources/QualificationExpectations/db_sim_test_expectation.csv b/core/src/test/resources/QualificationExpectations/db_sim_test_expectation.csv index 5c618e929..35d5d6f1b 100644 --- a/core/src/test/resources/QualificationExpectations/db_sim_test_expectation.csv +++ b/core/src/test/resources/QualificationExpectations/db_sim_test_expectation.csv @@ -1,2 +1,2 @@ App Name,App ID,SQL DF Duration,SQL Dataframe Task Duration,App Duration,GPU Opportunity,Executor CPU Time Percent,SQL Ids with Failures,Unsupported Read File Formats and Types,Unsupported Write Data Format,Complex Types,Nested Complex Types,Potential Problems,Longest SQL Duration,SQL Stage Durations Sum,NONSQL Task Duration Plus Overhead,Unsupported Task Duration,Supported SQL DF Task Duration,App Duration Estimated,Unsupported Execs,Unsupported Expressions,Estimated Job Frequency (monthly),Total Core Seconds -"Spark shell","local-1623876083964",119353,1417661,133857,92667,91.14,"","","","","","",119903,143821,14504,316964,1100697,false,"Scan;SerializeFromObject","",30,1599 +"Spark shell","local-1623876083964",119353,1417661,133857,92667,91.14,"","","","","","",119903,143821,14504,316964,1100697,false,"Scan unknown;SerializeFromObject","",30,1599 diff --git a/core/src/test/resources/QualificationExpectations/directory_test_expectation.csv b/core/src/test/resources/QualificationExpectations/directory_test_expectation.csv index 5c618e929..35d5d6f1b 100644 --- a/core/src/test/resources/QualificationExpectations/directory_test_expectation.csv +++ b/core/src/test/resources/QualificationExpectations/directory_test_expectation.csv @@ -1,2 +1,2 @@ App Name,App ID,SQL DF Duration,SQL Dataframe Task Duration,App Duration,GPU Opportunity,Executor CPU Time Percent,SQL Ids with Failures,Unsupported Read File Formats and Types,Unsupported Write Data Format,Complex Types,Nested Complex Types,Potential Problems,Longest SQL Duration,SQL Stage Durations Sum,NONSQL Task Duration Plus Overhead,Unsupported Task Duration,Supported SQL DF Task Duration,App Duration Estimated,Unsupported Execs,Unsupported Expressions,Estimated Job Frequency (monthly),Total Core Seconds -"Spark shell","local-1623876083964",119353,1417661,133857,92667,91.14,"","","","","","",119903,143821,14504,316964,1100697,false,"Scan;SerializeFromObject","",30,1599 +"Spark shell","local-1623876083964",119353,1417661,133857,92667,91.14,"","","","","","",119903,143821,14504,316964,1100697,false,"Scan unknown;SerializeFromObject","",30,1599 diff --git a/core/src/test/resources/QualificationExpectations/jdbc_expectation.csv b/core/src/test/resources/QualificationExpectations/jdbc_expectation.csv index df554c136..50e8986ba 100644 --- a/core/src/test/resources/QualificationExpectations/jdbc_expectation.csv +++ b/core/src/test/resources/QualificationExpectations/jdbc_expectation.csv @@ -1,2 +1,2 @@ App Name,App ID,SQL DF Duration,SQL Dataframe Task Duration,App Duration,GPU Opportunity,Executor CPU Time Percent,SQL Ids with Failures,Unsupported Read File Formats and Types,Unsupported Write Data Format,Complex Types,Nested Complex Types,Potential Problems,Longest SQL Duration,SQL Stage Durations Sum,NONSQL Task Duration Plus Overhead,Unsupported Task Duration,Supported SQL DF Task Duration,App Duration Estimated,Unsupported Execs,Unsupported Expressions,Estimated Job Frequency (monthly),Total Core Seconds -"Spark shell","app-20211019113801-0001",2942,19894,571967,2814,28.41,"","JDBC[*]","","","","",1812,2883,569025,859,19035,false,"CollectLimit;Scan JDBCRelation(TBLS) [numPartitions=1];Execute CreateViewCommand","",30,9110 +"Spark shell","app-20211019113801-0001",2942,19894,571967,2814,28.41,"","JDBC[*]","","","","",1812,2883,569025,859,19035,false,"CollectLimit;Scan jdbc;Execute CreateViewCommand","",30,9110 diff --git a/core/src/test/resources/QualificationExpectations/qual_test_missing_sql_end_expectation.csv b/core/src/test/resources/QualificationExpectations/qual_test_missing_sql_end_expectation.csv index 2561e6ca5..428f89654 100644 --- a/core/src/test/resources/QualificationExpectations/qual_test_missing_sql_end_expectation.csv +++ b/core/src/test/resources/QualificationExpectations/qual_test_missing_sql_end_expectation.csv @@ -1,2 +1,2 @@ App Name,App ID,SQL DF Duration,SQL Dataframe Task Duration,App Duration,GPU Opportunity,Executor CPU Time Percent,SQL Ids with Failures,Unsupported Read File Formats and Types,Unsupported Write Data Format,Complex Types,Nested Complex Types,Potential Problems,Longest SQL Duration,SQL Stage Durations Sum,NONSQL Task Duration Plus Overhead,Unsupported Task Duration,Supported SQL DF Task Duration,App Duration Estimated,Unsupported Execs,Unsupported Expressions,Estimated Job Frequency (monthly),Total Core Seconds -"Rapids Spark Profiling Tool Unit Tests","local-1622561780883",0,40448,7673,0,55.94,"","","","","","",0,5000,7673,8096,32352,false,"Scan;SerializeFromObject","",30,82 +"Rapids Spark Profiling Tool Unit Tests","local-1622561780883",0,40448,7673,0,55.94,"","","","","","",0,5000,7673,8096,32352,false,"Scan unknown;SerializeFromObject","",30,82 diff --git a/core/src/test/resources/QualificationExpectations/qual_test_simple_expectation.csv b/core/src/test/resources/QualificationExpectations/qual_test_simple_expectation.csv index a3a847ad0..62421d9bf 100644 --- a/core/src/test/resources/QualificationExpectations/qual_test_simple_expectation.csv +++ b/core/src/test/resources/QualificationExpectations/qual_test_simple_expectation.csv @@ -1,5 +1,5 @@ App Name,App ID,SQL DF Duration,SQL Dataframe Task Duration,App Duration,GPU Opportunity,Executor CPU Time Percent,SQL Ids with Failures,Unsupported Read File Formats and Types,Unsupported Write Data Format,Complex Types,Nested Complex Types,Potential Problems,Longest SQL Duration,SQL Stage Durations Sum,NONSQL Task Duration Plus Overhead,Unsupported Task Duration,Supported SQL DF Task Duration,App Duration Estimated,Unsupported Execs,Unsupported Expressions,Estimated Job Frequency (monthly),Total Core Seconds -"Rapids Spark Profiling Tool Unit Tests","local-1622043423018",11600,132257,16319,9868,37.7,"","","JSON","","","",7143,13770,4719,19744,112513,false,"SerializeFromObject;Execute InsertIntoHadoopFsRelationCommand json;DeserializeToObject;Filter;MapElements;Scan","",1,186 +"Rapids Spark Profiling Tool Unit Tests","local-1622043423018",11600,132257,16319,9868,37.7,"","","JSON","","","",7143,13770,4719,19744,112513,false,"SerializeFromObject;Scan unknown;Execute InsertIntoHadoopFsRelationCommand json;DeserializeToObject;Filter;MapElements","",1,186 "Spark shell","local-1651187225439",224,180,355637,74,87.88,"","JSON[string:bigint:int]","","","","",498,228,355101,120,60,false,"SerializeFromObject;CollectLimit;DeserializeToObject;Scan json;Filter;MapElements","",1,2834 "Spark shell","local-1651188809790",347,283,166215,14,81.18,"","JSON[string:bigint:int]","","","","UDF",715,318,165572,271,12,false,"CollectLimit;Scan json;Project","UDF",1,1318 "Rapids Spark Profiling Tool Unit Tests","local-1623281204390",1156,4666,6240,1,46.27,"","JSON[string:bigint:int]","JSON","","","UDF",1209,1130,5809,4661,5,false,"Execute InsertIntoHadoopFsRelationCommand json;LocalTableScan;Project;Scan json;Execute CreateViewCommand","UDF",1,64 diff --git a/core/src/test/resources/QualificationExpectations/truncated_1_end_expectation.csv b/core/src/test/resources/QualificationExpectations/truncated_1_end_expectation.csv index f7737d508..79cb8dede 100644 --- a/core/src/test/resources/QualificationExpectations/truncated_1_end_expectation.csv +++ b/core/src/test/resources/QualificationExpectations/truncated_1_end_expectation.csv @@ -1,2 +1,2 @@ App Name,App ID,SQL DF Duration,SQL Dataframe Task Duration,App Duration,GPU Opportunity,Executor CPU Time Percent,SQL Ids with Failures,Unsupported Read File Formats and Types,Unsupported Write Data Format,Complex Types,Nested Complex Types,Potential Problems,Longest SQL Duration,SQL Stage Durations Sum,NONSQL Task Duration Plus Overhead,Unsupported Task Duration,Supported SQL DF Task Duration,App Duration Estimated,Unsupported Execs,Unsupported Expressions,Estimated Job Frequency (monthly),Total Core Seconds -"Rapids Spark Profiling Tool Unit Tests","local-1622043423018",395,14353,4872,164,62.67,"","","JSON","","","",1306,794,4477,8376,5977,true,"SerializeFromObject;Execute InsertIntoHadoopFsRelationCommand json;DeserializeToObject;Filter;MapElements;Scan","",30,49 +"Rapids Spark Profiling Tool Unit Tests","local-1622043423018",395,14353,4872,164,62.67,"","","JSON","","","",1306,794,4477,8376,5977,true,"SerializeFromObject;Scan unknown;Execute InsertIntoHadoopFsRelationCommand json;DeserializeToObject;Filter;MapElements","",30,49 diff --git a/core/src/test/scala/com/nvidia/spark/rapids/tool/planparser/SqlPlanParserSuite.scala b/core/src/test/scala/com/nvidia/spark/rapids/tool/planparser/SqlPlanParserSuite.scala index 6fc9357cf..e31064851 100644 --- a/core/src/test/scala/com/nvidia/spark/rapids/tool/planparser/SqlPlanParserSuite.scala +++ b/core/src/test/scala/com/nvidia/spark/rapids/tool/planparser/SqlPlanParserSuite.scala @@ -276,12 +276,12 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val parquet = allExecInfo.filter(_.exec.contains("Scan parquet")) val text = allExecInfo.filter(_.exec.contains("Scan text")) val csv = allExecInfo.filter(_.exec.contains("Scan csv")) - assertSizeAndNotSupported(2, json.toSeq) - assertSizeAndNotSupported(1, text.toSeq) + assertSizeAndNotSupported(2, json) + assertSizeAndNotSupported(1, text) for (t <- Seq(parquet, csv)) { - assertSizeAndSupported(1, t.toSeq) + assertSizeAndSupported(1, t) } - assertSizeAndSupported(2, orc.toSeq) + assertSizeAndSupported(2, orc) } test("BatchScan") { @@ -299,10 +299,10 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val orc = allExecInfo.filter(_.exec.contains("BatchScan orc")) val parquet = allExecInfo.filter(_.exec.contains("BatchScan parquet")) val csv = allExecInfo.filter(_.exec.contains("BatchScan csv")) - assertSizeAndNotSupported(3, json.toSeq) - assertSizeAndSupported(1, csv.toSeq) + assertSizeAndNotSupported(3, json) + assertSizeAndSupported(1, csv) for (t <- Seq(orc, parquet)) { - assertSizeAndSupported(2, t.toSeq) + assertSizeAndSupported(2, t) } } @@ -1224,7 +1224,8 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val projects = allExecInfo.filter(_.exec.contains("Project")) assertSizeAndNotSupported(1, projects) val expectedExprss = Seq("parse_url_ref", "parse_url_userinfo") - projects(0).unsupportedExprs.map(_.exprName) should contain theSameElementsAs expectedExprss + projects(0) + .unsupportedExprs.map(_.getOpName) should contain theSameElementsAs expectedExprss } } } @@ -1802,7 +1803,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { val allExecInfo = getAllExecsFromPlan(parsedPlans.toSeq) val windowExecNotSupportedExprs = allExecInfo.filter( _.exec.contains(windowGroupLimitExecCmd)).flatMap(x => x.unsupportedExprs) - windowExecNotSupportedExprs.head.exprName shouldEqual "row_number" + windowExecNotSupportedExprs.head.getOpName shouldEqual "row_number" windowExecNotSupportedExprs.head.unsupportedReason shouldEqual "Ranking function row_number is not supported in WindowGroupLimitExec" val windowGroupLimitExecs = allExecInfo.filter(_.exec.contains(windowGroupLimitExecCmd)) diff --git a/core/src/test/scala/com/nvidia/spark/rapids/tool/qualification/PluginTypeCheckerSuite.scala b/core/src/test/scala/com/nvidia/spark/rapids/tool/qualification/PluginTypeCheckerSuite.scala index 3e9988c41..6b7821d3f 100644 --- a/core/src/test/scala/com/nvidia/spark/rapids/tool/qualification/PluginTypeCheckerSuite.scala +++ b/core/src/test/scala/com/nvidia/spark/rapids/tool/qualification/PluginTypeCheckerSuite.scala @@ -241,6 +241,6 @@ class PluginTypeCheckerSuite extends FunSuite with Logging { val expressions = SQLPlanParser.parseAggregateExpressions(hashAggregateExpr) assert(expressions.contains("decimalsum")) val notSupportedExprs = checker.getNotSupportedExprs(expressions) - assert(notSupportedExprs.find(_.exprName == "decimalsum").isEmpty) + assert(notSupportedExprs.find(_.getOpName == "decimalsum").isEmpty) } } diff --git a/core/src/test/scala/com/nvidia/spark/rapids/tool/qualification/QualificationSuite.scala b/core/src/test/scala/com/nvidia/spark/rapids/tool/qualification/QualificationSuite.scala index 57b6f1cb3..03943d463 100644 --- a/core/src/test/scala/com/nvidia/spark/rapids/tool/qualification/QualificationSuite.scala +++ b/core/src/test/scala/com/nvidia/spark/rapids/tool/qualification/QualificationSuite.scala @@ -1066,7 +1066,7 @@ class QualificationSuite extends BaseTestSuite { val stdOutunsupportedExecs = stdOutValues(stdOutValues.length - 3) // index of unsupportedExprs val stdOutunsupportedExprs = stdOutValues(stdOutValues.length - 2) - val expectedstdOutExecs = "Scan;Filter;SerializeF..." + val expectedstdOutExecs = "Scan unknown;Filter;Se..." assert(stdOutunsupportedExecs == expectedstdOutExecs) // Exec value is Scan;Filter;SerializeFromObject and UNSUPPORTED_EXECS_MAX_SIZE is 25 val expectedStdOutExecsMaxLength = 25 @@ -1096,7 +1096,7 @@ class QualificationSuite extends BaseTestSuite { val rows = outputActual.collect() assert(rows.size == 1) - val expectedExecs = "Scan;Filter;SerializeFromObject" // Unsupported Execs + val expectedExecs = "Scan unknown;Filter;SerializeFromObject" // Unsupported Execs val expectedExprs = "hex" //Unsupported Exprs val unsupportedExecs = outputActual.select(QualOutputWriter.UNSUPPORTED_EXECS).first.getString(0) diff --git a/user_tools/src/spark_rapids_tools/tools/qualx/preprocess.py b/user_tools/src/spark_rapids_tools/tools/qualx/preprocess.py index 320615b7c..1bdbd76b7 100644 --- a/user_tools/src/spark_rapids_tools/tools/qualx/preprocess.py +++ b/user_tools/src/spark_rapids_tools/tools/qualx/preprocess.py @@ -108,7 +108,12 @@ 'sqlOp_CustomShuffleReader', 'sqlOp_DeserializeToObject', 'sqlOp_Exchange', - 'sqlOp_Execute InsertIntoHadoopFsRelationCommand', + 'sqlOp_Execute InsertIntoHadoopFsRelationCommand csv', + 'sqlOp_Execute InsertIntoHadoopFsRelationCommand parquet', + 'sqlOp_Execute InsertIntoHadoopFsRelationCommand orc', + 'sqlOp_Execute InsertIntoHadoopFsRelationCommand json', + 'sqlOp_Execute InsertIntoHadoopFsRelationCommand text', + 'sqlOp_Execute InsertIntoHadoopFsRelationCommand unknown', 'sqlOp_Expand', 'sqlOp_Filter', 'sqlOp_Generate', @@ -125,15 +130,17 @@ 'sqlOp_Project', 'sqlOp_ReusedSort', 'sqlOp_RunningWindowFunction', - 'sqlOp_Scan csv ', + 'sqlOp_Scan csv', 'sqlOp_Scan ExistingRDD Delta Table Checkpoint', 'sqlOp_Scan ExistingRDD Delta Table State', - 'sqlOp_Scan JDBCRelation', - 'sqlOp_Scan json ', + 'sqlOp_Scan ExistingRDD', + 'sqlOp_Scan jdbc', + 'sqlOp_Scan json', 'sqlOp_Scan OneRowRelation', - 'sqlOp_Scan orc ', - 'sqlOp_Scan parquet ', - 'sqlOp_Scan text ', + 'sqlOp_Scan orc', + 'sqlOp_Scan parquet', + 'sqlOp_Scan text', + 'sqlOp_Scan unknown', 'sqlOp_SerializeFromObject', 'sqlOp_Sort', 'sqlOp_SortAggregate', @@ -481,8 +488,8 @@ def combine_tables(table_name: str) -> pd.DataFrame: 'Scan DeltaCDFRelation', 'Scan ExistingRDD Delta Table Checkpoint', 'Scan ExistingRDD Delta Table State', - 'Scan JDBCRelation', - 'Scan parquet ', # trailing space is also in default sql op name + 'Scan jdbc', + 'Scan parquet', # GPU 'GpuScan parquet', ] From a414e095b85858ab73f0d8684d3e1627b04eefee Mon Sep 17 00:00:00 2001 From: Cindy Jiang <47068112+cindyyuanjiang@users.noreply.github.com> Date: Wed, 4 Dec 2024 18:25:25 -0800 Subject: [PATCH 19/22] [BUG] Fix sync plugin files script to handle empty or non-existing cvs files Signed-off-by: cindyyuanjiang --- scripts/sync_plugin_files/process_supported_files.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/scripts/sync_plugin_files/process_supported_files.py b/scripts/sync_plugin_files/process_supported_files.py index 8ff1ba3c9..9eecf8ac2 100644 --- a/scripts/sync_plugin_files/process_supported_files.py +++ b/scripts/sync_plugin_files/process_supported_files.py @@ -118,7 +118,11 @@ def unify_all_files(root_dir, file_name, key_names): for dir_name in os.listdir(root_dir): # List entries in root_dir if os.path.isdir(os.path.join(root_dir, dir_name)): csv_file_path = os.path.join(root_dir, dir_name, file_name) - cur_df = pd.read_csv(csv_file_path, keep_default_na=False) + try: + cur_df = pd.read_csv(csv_file_path, keep_default_na=False) + except Exception as e: + logging.debug(f"Encountered exception when reading file {csv_file_path}: {e}") + continue if final_df.empty: final_df = pd.DataFrame(columns=cur_df.columns.tolist()) From 746c8986e0c607d3dd6beb81952798837538185d Mon Sep 17 00:00:00 2001 From: Lee Yang Date: Thu, 5 Dec 2024 11:27:51 -0800 Subject: [PATCH 20/22] Update models for latest tools code (#1448) * updated models for latest tools code * remove deprecated models Signed-off-by: Lee Yang --------- Signed-off-by: Lee Yang --- .../qualx/models/xgboost/combined.cfg | 2 +- .../qualx/models/xgboost/combined.json | 2 +- .../qualx/models/xgboost/combined.metrics | 219 ++++++++--------- .../qualx/models/xgboost/databricks-aws.cfg | 2 +- .../qualx/models/xgboost/databricks-aws.json | 2 +- .../models/xgboost/databricks-aws.metrics | 123 +++++----- .../models/xgboost/databricks-aws_photon.cfg | 2 +- .../models/xgboost/databricks-aws_photon.json | 2 +- .../xgboost/databricks-aws_photon.metrics | 139 +++++------ .../qualx/models/xgboost/databricks-azure.cfg | 2 +- .../models/xgboost/databricks-azure.json | 2 +- .../models/xgboost/databricks-azure.metrics | 139 +++++------ .../xgboost/databricks-azure_photon.cfg | 2 +- .../xgboost/databricks-azure_photon.json | 2 +- .../xgboost/databricks-azure_photon.metrics | 135 ++++++----- .../qualx/models/xgboost/dataproc.cfg | 2 +- .../qualx/models/xgboost/dataproc.json | 2 +- .../qualx/models/xgboost/dataproc.metrics | 221 +++++++++--------- .../models/xgboost/dataproc_2.0-parquet.json | 1 - .../models/xgboost/dataproc_2.1-orc.json | 1 - .../resources/qualx/models/xgboost/emr.cfg | 2 +- .../resources/qualx/models/xgboost/emr.json | 2 +- .../qualx/models/xgboost/emr.metrics | 127 +++++----- .../resources/qualx/models/xgboost/onprem.cfg | 2 +- .../qualx/models/xgboost/onprem.json | 2 +- .../qualx/models/xgboost/onprem.metrics | 109 +++++---- 26 files changed, 650 insertions(+), 596 deletions(-) delete mode 100644 user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/dataproc_2.0-parquet.json delete mode 100644 user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/dataproc_2.1-orc.json diff --git a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.cfg b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.cfg index f84abdfcb..8cbac1ad7 100644 --- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.cfg +++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.cfg @@ -1 +1 @@ -{"learner":{"generic_param":{"device":"cpu","fail_on_invalid_gpu_id":"0","n_jobs":"0","nthread":"0","random_state":"0","seed":"0","seed_per_iteration":"0","validate_parameters":"1"},"gradient_booster":{"gbtree_model_param":{"num_parallel_tree":"1","num_trees":"97"},"gbtree_train_param":{"process_type":"default","tree_method":"auto","updater":"grow_quantile_histmaker","updater_seq":"grow_quantile_histmaker"},"name":"gbtree","specified_updater":false,"tree_train_param":{"alpha":"0","cache_opt":"1","colsample_bylevel":"1","colsample_bynode":"1","colsample_bytree":"1","eta":"0.0478905365","gamma":"0.100665279","grow_policy":"depthwise","interaction_constraints":"","lambda":"1","learning_rate":"0.0478905365","max_bin":"256","max_cat_threshold":"64","max_cat_to_onehot":"4","max_delta_step":"0","max_depth":"7","max_leaves":"0","min_child_weight":"2","min_split_loss":"0.100665279","monotone_constraints":"()","refresh_leaf":"1","reg_alpha":"0","reg_lambda":"1","sampling_method":"uniform","sketch_ratio":"2","sparse_threshold":"0.20000000000000001","subsample":"0.799700022"},"updater":[{"hist_train_param":{"debug_synchronize":"0","max_cached_hist_node":"65536"},"name":"grow_quantile_histmaker"}]},"learner_model_param":{"base_score":"5.681664E-1","boost_from_average":"1","num_class":"0","num_feature":"108","num_target":"1"},"learner_train_param":{"booster":"gbtree","disable_default_eval_metric":"0","multi_strategy":"one_output_per_tree","objective":"reg:squarederror"},"metrics":[{"name":"mae"},{"name":"mape"}],"objective":{"name":"reg:squarederror","reg_loss_param":{"scale_pos_weight":"1"}}},"version":[2,0,3]} \ No newline at end of file +{"learner":{"generic_param":{"device":"cpu","fail_on_invalid_gpu_id":"0","n_jobs":"0","nthread":"0","random_state":"0","seed":"0","seed_per_iteration":"0","validate_parameters":"1"},"gradient_booster":{"gbtree_model_param":{"num_parallel_tree":"1","num_trees":"93"},"gbtree_train_param":{"process_type":"default","tree_method":"auto","updater":"grow_quantile_histmaker","updater_seq":"grow_quantile_histmaker"},"name":"gbtree","specified_updater":false,"tree_train_param":{"alpha":"0","cache_opt":"1","colsample_bylevel":"1","colsample_bynode":"1","colsample_bytree":"1","eta":"0.0452739485","gamma":"0.0653549582","grow_policy":"depthwise","interaction_constraints":"","lambda":"1","learning_rate":"0.0452739485","max_bin":"256","max_cat_threshold":"64","max_cat_to_onehot":"4","max_delta_step":"0","max_depth":"8","max_leaves":"0","min_child_weight":"2","min_split_loss":"0.0653549582","monotone_constraints":"()","refresh_leaf":"1","reg_alpha":"0","reg_lambda":"1","sampling_method":"uniform","sketch_ratio":"2","sparse_threshold":"0.20000000000000001","subsample":"0.662151933"},"updater":[{"hist_train_param":{"debug_synchronize":"0","max_cached_hist_node":"65536"},"name":"grow_quantile_histmaker"}]},"learner_model_param":{"base_score":"5.681664E-1","boost_from_average":"1","num_class":"0","num_feature":"115","num_target":"1"},"learner_train_param":{"booster":"gbtree","disable_default_eval_metric":"0","multi_strategy":"one_output_per_tree","objective":"reg:squarederror"},"metrics":[{"name":"mae"},{"name":"mape"}],"objective":{"name":"reg:squarederror","reg_loss_param":{"scale_pos_weight":"1"}}},"version":[2,0,3]} \ No newline at end of file diff --git a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.json b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.json index d08771d24..2526694b7 100644 --- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.json +++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.json @@ -1 +1 @@ -{"learner":{"attributes":{},"feature_names":["numTasks_sum","duration_sum","duration_max","duration_min","duration_mean","input_recordsRead_sum","output_recordsWritten_sum","peakExecutionMemory_max","resultSerializationTime_sum","resultSize_max","sr_localBlocksFetched_sum","sr_remoteBlocksFetched_sum","sw_recordsWritten_sum","sqlOp_Exchange","sqlOp_Execute InsertIntoHadoopFsRelationCommand","sqlOp_Scan parquet 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\ No newline at end of file diff --git a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.metrics b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.metrics index 4895b8807..ade7f596d 100644 --- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.metrics +++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.metrics @@ -1,109 +1,116 @@ ,feature,shap_value,mean,std,min,25%,50%,75%,max -0,maxOnHeapMem,0.24525835,12891675333.097458,7443156274.854312,455501414.0,8974132838.0,10119177830.0,10119177830.0,26104509235.0 -1,duration_max,0.122840814,19727.637005649718,132756.56647030966,15.0,1000.75,2626.5,6606.5,3183955.0 -2,executorCPUTime_mean,0.116636105,1600.0121232217436,8490.83160303521,3.875,196.08367473240125,438.1275815373426,1135.2854603729604,227947.84615384616 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b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-aws.cfg index bb4140578..787e26392 100644 --- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-aws.cfg +++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-aws.cfg @@ -1 +1 @@ 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\ No newline at end of file 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a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-aws_photon.cfg b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-aws_photon.cfg index f4badc4d1..b0ab129c4 100644 --- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-aws_photon.cfg +++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-aws_photon.cfg @@ -1 +1 @@ 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\ No newline at end of file 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\ No newline at end of file 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a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/dataproc_2.0-parquet.json +++ /dev/null @@ -1 +0,0 @@ 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\ No newline at end of file +{"learner":{"generic_param":{"device":"cpu","fail_on_invalid_gpu_id":"0","n_jobs":"0","nthread":"0","random_state":"0","seed":"0","seed_per_iteration":"0","validate_parameters":"1"},"gradient_booster":{"gbtree_model_param":{"num_parallel_tree":"1","num_trees":"83"},"gbtree_train_param":{"process_type":"default","tree_method":"auto","updater":"grow_quantile_histmaker","updater_seq":"grow_quantile_histmaker"},"name":"gbtree","specified_updater":false,"tree_train_param":{"alpha":"0","cache_opt":"1","colsample_bylevel":"1","colsample_bynode":"1","colsample_bytree":"1","eta":"0.0461990498","gamma":"0.0150604062","grow_policy":"depthwise","interaction_constraints":"","lambda":"1","learning_rate":"0.0461990498","max_bin":"256","max_cat_threshold":"64","max_cat_to_onehot":"4","max_delta_step":"0","max_depth":"10","max_leaves":"0","min_child_weight":"4","min_split_loss":"0.0150604062","monotone_constraints":"()","refresh_leaf":"1","reg_alpha":"0","reg_lambda":"1","sampling_method":"uniform","sketch_ratio":"2","sparse_threshold":"0.20000000000000001","subsample":"0.671188235"},"updater":[{"hist_train_param":{"debug_synchronize":"0","max_cached_hist_node":"65536"},"name":"grow_quantile_histmaker"}]},"learner_model_param":{"base_score":"8.761862E-1","boost_from_average":"1","num_class":"0","num_feature":"115","num_target":"1"},"learner_train_param":{"booster":"gbtree","disable_default_eval_metric":"0","multi_strategy":"one_output_per_tree","objective":"reg:squarederror"},"metrics":[{"name":"mae"},{"name":"mape"}],"objective":{"name":"reg:squarederror","reg_loss_param":{"scale_pos_weight":"1"}}},"version":[2,0,3]} \ No newline at end of file diff --git a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/onprem.json b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/onprem.json index 691af8005..d17cd986b 100644 --- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/onprem.json +++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/onprem.json @@ -1 +1 @@ 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\ No newline at end of file diff --git a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/onprem.metrics b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/onprem.metrics index 14ec21817..39973212f 100644 --- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/onprem.metrics +++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/onprem.metrics @@ -56,54 +56,61 @@ 54,sqlOp_BroadcastExchange,9.207968e-05,0.897503285151117,0.3034000972146485,0.0,1.0,1.0,1.0,1.0 55,sqlOp_Exchange,7.649039e-05,0.9579500657030223,0.20076907391845303,0.0,1.0,1.0,1.0,1.0 56,sqlOp_BroadcastNestedLoopJoin,6.7585526e-05,0.03942181340341656,0.19466029547643685,0.0,0.0,0.0,0.0,1.0 -57,sqlOp_HashAggregatePrefixGroupingSets,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -58,sqlOp_GlobalLimit,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -59,sqlOp_GenerateBloomFilter,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -60,sqlOp_Generate,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -61,sqlOp_Execute 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+105,sr_remoteBlocksFetched_sum,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +106,platform_onprem,0.0,1.0,0.0,1.0,1.0,1.0,1.0,1.0 +107,maxOffHeapMem,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +108,platform_databricks-azure,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +109,platform_dataproc,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +110,platform_emr,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +111,sqlOp_CartesianProduct,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +112,sqlOp_CommandResult,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +113,sqlOp_CustomShuffleReader,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +114,sqlOp_WindowSort,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 From ab4cf6abb7125fd6a31b7621ba96d7bb267c6697 Mon Sep 17 00:00:00 2001 From: Ahmed Hussein <50450311+amahussein@users.noreply.github.com> Date: Thu, 5 Dec 2024 17:08:57 -0600 Subject: [PATCH 21/22] Count expressions per Exec in SQLPlanParser (#1449) * Count expressions per Exec in SQLPlanParser Signed-off-by: Ahmed Hussein (amahussein) Fixes #1447 Improves the operators-stats by counting the occurence of each expression within the Exec node. * ckeanup overriding methods Signed-off-by: Ahmed Hussein (amahussein) --------- Signed-off-by: Ahmed Hussein (amahussein) --- .../tool/planparser/SQLPlanParser.scala | 49 ++++----- .../planparser/WholeStageExecParser.scala | 2 +- .../planparser/WindowGroupLimitParser.scala | 2 +- .../tool/planparser/ops/ExprOpRef.scala | 31 ++++++ .../planparser/ops/OpRefWrapperBase.scala | 50 ++++++++++ .../tool/planparser/ops/OperatorCounter.scala | 61 ++++++------ .../planparser/ops/UnsupportedExprOpRef.scala | 2 +- .../qualification/PluginTypeChecker.scala | 2 +- .../tool/qualification/QualOutputWriter.scala | 44 +++++---- .../tool/planparser/SqlPlanParserSuite.scala | 99 +++++++++++++------ 10 files changed, 232 insertions(+), 110 deletions(-) create mode 100644 core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/ExprOpRef.scala create mode 100644 core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/OpRefWrapperBase.scala diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SQLPlanParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SQLPlanParser.scala index 17159842b..4d9c59dd8 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SQLPlanParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/SQLPlanParser.scala @@ -21,7 +21,7 @@ import scala.collection.mutable.{ArrayBuffer, WeakHashMap} import scala.util.control.NonFatal import scala.util.matching.Regex -import com.nvidia.spark.rapids.tool.planparser.ops.{OperatorRefBase, OpRef, UnsupportedExprOpRef} +import com.nvidia.spark.rapids.tool.planparser.ops.{ExprOpRef, OperatorRefTrait, OpRef, UnsupportedExprOpRef} import com.nvidia.spark.rapids.tool.planparser.photon.{PhotonPlanParser, PhotonStageExecParser} import com.nvidia.spark.rapids.tool.qualification.PluginTypeChecker @@ -75,7 +75,7 @@ object UnsupportedReasons extends Enumeration { case class UnsupportedExecSummary( sqlId: Long, execId: Long, - execRef: OperatorRefBase, + execRef: OperatorRefTrait, opType: OpTypes.OpType, reason: UnsupportedReasons.UnsupportedReason, opAction: OpActions.OpAction) { @@ -89,8 +89,6 @@ case class UnsupportedExecSummary( val unsupportedOperatorCSVFormat: String = execRef.getOpNameCSV val details: String = UnsupportedReasons.reportUnsupportedReason(reason) - - def isExpression: Boolean = execRef.isInstanceOf[UnsupportedExprOpRef] } case class ExecInfo( @@ -110,7 +108,7 @@ case class ExecInfo( dataSet: Boolean, udf: Boolean, shouldIgnore: Boolean, - expressions: Seq[OpRef]) { + expressions: Seq[ExprOpRef]) { private def childrenToString = { val str = children.map { c => @@ -141,10 +139,6 @@ case class ExecInfo( stages = stageIDs } - def appendToStages(stageIDs: Set[Int]): Unit = { - stages ++= stageIDs - } - def setShouldRemove(value: Boolean): Unit = { shouldRemove ||= value } @@ -286,7 +280,7 @@ object ExecInfo { udf, shouldIgnore, // convert array of string expressions to OpRefs - expressions = expressions.map(OpRef.fromExpr) + expressions = ExprOpRef.fromRawExprSeq(expressions) ) } @@ -351,7 +345,7 @@ case class PlanInfo( sqlID: Long, sqlDesc: String, execInfo: Seq[ExecInfo]) { - def getUnsupportedExpressions: Seq[OperatorRefBase] = { + def getUnsupportedExpressions: Seq[OperatorRefTrait] = { execInfo.flatMap { e => if (e.isClusterNode) { // wholeStageCodeGen does not have expressions/unsupported-expressions @@ -727,21 +721,21 @@ object SQLPlanParser extends Logging { } private def getAllFunctionNames(regPattern: Regex, expr: String, - groupInd: Int = 1, isAggr: Boolean = true): Set[String] = { + groupInd: Int = 1, isAggr: Boolean = true): Array[String] = { // Returns all matches in an expression. This can be used when the SQL expression is not // tokenized. val newExpr = processSpecialFunctions(expr) // first get all the functionNames val exprss = - regPattern.findAllMatchIn(newExpr).map(_.group(groupInd)).toSet + regPattern.findAllMatchIn(newExpr).map(_.group(groupInd)).toSeq // For aggregate expressions we want to process the results to remove the prefix // DB: remove the "^partial_" and "^finalmerge_" prefixes // TODO: // for performance sake, we can turn off the aggregate processing by enabling it only // when needed. However, for now, we always do this processing until we are confident we know - // the correct place to turn on/off that flag.we can use the argument isAgg only when needed + // the correct place to turn on/off that flag. We can use the argument isAgg only when needed val results = if (isAggr) { exprss.collect { case func => @@ -750,7 +744,7 @@ object SQLPlanParser extends Logging { } else { exprss } - results.filterNot(ignoreExpression(_)) + results.filterNot(ignoreExpression(_)).toArray } def parseProjectExpressions(exprStr: String): Array[String] = { @@ -758,7 +752,7 @@ object SQLPlanParser extends Logging { // This is to split the string such that only function names are extracted. The pattern is // such that function name is succeeded by `(`. We use regex to extract all the function names // below: - getAllFunctionNames(functionPrefixPattern, exprStr).toArray + getAllFunctionNames(functionPrefixPattern, exprStr) } // This parser is used for SortAggregateExec, HashAggregateExec and ObjectHashAggregateExec @@ -792,7 +786,7 @@ object SQLPlanParser extends Logging { } } } - parsedExpressions.distinct.toArray + parsedExpressions.toArray } def parseWindowExpressions(exprStr:String): Array[String] = { @@ -828,7 +822,7 @@ object SQLPlanParser extends Logging { } } } - parsedExpressions.distinct.toArray + parsedExpressions.toArray } def parseWindowGroupLimitExpressions(exprStr: String): Array[String] = { @@ -858,10 +852,10 @@ object SQLPlanParser extends Logging { // - Some values can be NULLs. That's why we cannot limit the extract to the first row. // - Nested brackets/parenthesis makes it challenging to use regex that contains // brackets/parenthesis to extract expressions. - // The implementation Use regex to extract all function names and return distinct set of + // The implementation Use regex to extract all function names and return a list of // function names. // This implementation is 1 line implementation, but it can be a memory/time bottleneck. - getAllFunctionNames(functionPrefixPattern, exprStr).toArray + getAllFunctionNames(functionPrefixPattern, exprStr) } def parseTakeOrderedExpressions(exprStr: String): Array[String] = { @@ -889,7 +883,7 @@ object SQLPlanParser extends Logging { } } } - parsedExpressions.distinct.toArray + parsedExpressions.toArray } def parseGenerateExpressions(exprStr: String): Array[String] = { @@ -897,11 +891,11 @@ object SQLPlanParser extends Logging { // 1. Generate explode(arrays#1306), [id#1304], true, [col#1426] // 2. Generate json_tuple(values#1305, Zipcode, ZipCodeType, City), [id#1304], // false, [c0#1407, c1#1408, c2#1409] - getAllFunctionNames(functionPrefixPattern, exprStr).toArray + getAllFunctionNames(functionPrefixPattern, exprStr) } private def addFunctionNames(exprs: String, parsedExpressions: ArrayBuffer[String]): Unit = { - val functionNames = getAllFunctionNames(functionPrefixPattern, exprs).toArray + val functionNames = getAllFunctionNames(functionPrefixPattern, exprs) functionNames.foreach(parsedExpressions += _) } @@ -946,7 +940,7 @@ object SQLPlanParser extends Logging { val isSortMergeSupported = !(isSortMergeJoin && joinCondition.nonEmpty && isSMJConditionUnsupported(joinCondition)) - (parsedExpressions.distinct.toArray, equiJoinSupportedTypes(buildSide, joinType) + (parsedExpressions.toArray, equiJoinSupportedTypes(buildSide, joinType) && isSortMergeSupported) } @@ -1054,7 +1048,7 @@ object SQLPlanParser extends Logging { } } } - parsedExpressions.distinct.toArray + parsedExpressions.toArray } def parseFilterExpressions(exprStr: String): Array[String] = { @@ -1109,7 +1103,7 @@ object SQLPlanParser extends Logging { processedExpr = nonBinaryOperatorsRegEx.replaceAllIn(processedExpr, " ") // Step-4: remove remaining parentheses '(', ')' and commas if we had functionCalls - if (!functionMatches.isEmpty) { + if (functionMatches.nonEmpty) { // remove "," processedExpr = processedExpr.replaceAll(",", " ") } @@ -1147,7 +1141,6 @@ object SQLPlanParser extends Logging { logDebug(s"Unrecognized Token - $token") } } - - parsedExpressions.distinct.toArray + parsedExpressions.toArray } } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/WholeStageExecParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/WholeStageExecParser.scala index 5b8730938..8754b69c6 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/WholeStageExecParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/WholeStageExecParser.scala @@ -59,7 +59,7 @@ abstract class WholeStageExecParserBase( // The node should be marked as shouldRemove when all the children of the // wholeStageCodeGen are marked as shouldRemove. val removeNode = isDupNode || childNodes.forall(_.shouldRemove) - // Remove any suffix in order to get the node label without any trailing number. + // Remove any suffix to get the node label without any trailing number. val nodeLabel = nodeNameRegeX.findFirstMatchIn(node.name) match { case Some(m) => m.group(1) // in case not found, use the full exec name diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/WindowGroupLimitParser.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/WindowGroupLimitParser.scala index 853c1b767..1dd50680b 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/WindowGroupLimitParser.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/WindowGroupLimitParser.scala @@ -37,7 +37,7 @@ case class WindowGroupLimitParser( override def getUnsupportedExprReasonsForExec( expressions: Array[String]): Seq[UnsupportedExprOpRef] = { - expressions.flatMap { expr => + expressions.distinct.flatMap { expr => if (!supportedRankingExprs.contains(expr)) { Some(UnsupportedExprOpRef(expr, s"Ranking function $expr is not supported in $fullExecName")) diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/ExprOpRef.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/ExprOpRef.scala new file mode 100644 index 000000000..48be98c50 --- /dev/null +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/ExprOpRef.scala @@ -0,0 +1,31 @@ +/* + * Copyright (c) 2024, NVIDIA CORPORATION. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package com.nvidia.spark.rapids.tool.planparser.ops + +/** + * Represents a reference to an expression operator that is stored in the ExecInfo expressions + * @param opRef the opRef to wrap + * @param count the count of that expression within the exec. + */ +case class ExprOpRef(opRef: OpRef, count: Int = 1) extends OpRefWrapperBase(opRef) + +object ExprOpRef extends OpRefWrapperBaseTrait[ExprOpRef] { + def fromRawExprSeq(exprArr: Seq[String]): Seq[ExprOpRef] = { + exprArr.groupBy(identity) + .mapValues(expr => ExprOpRef(OpRef.fromExpr(expr.head), expr.size)).values.toSeq + } +} diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/OpRefWrapperBase.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/OpRefWrapperBase.scala new file mode 100644 index 000000000..09cd6bb83 --- /dev/null +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/OpRefWrapperBase.scala @@ -0,0 +1,50 @@ +/* + * Copyright (c) 2024, NVIDIA CORPORATION. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package com.nvidia.spark.rapids.tool.planparser.ops + +/** + * An instance that wraps OpRef and exposes the OpRef methods. + * This is used to provide common interface for all classes that wrap OpRef along with other + * metadata. + * @param opRef the opRef to wrap + */ +class OpRefWrapperBase(opRef: OpRef) extends OperatorRefTrait { + override def getOpName: String = opRef.getOpName + + override def getOpNameCSV: String = opRef.getOpNameCSV + + override def getOpType: String = opRef.getOpType + + override def getOpTypeCSV: String = opRef.getOpTypeCSV + + def getOpRef: OpRef = opRef +} + +/** + * A trait that provides a factory method to create instances of OpRefWrapperBase from a sequence of + * @tparam R the type of the OpRefWrapperBase + */ +trait OpRefWrapperBaseTrait[R <: OpRefWrapperBase] { + /** + * Create instances of OpRefWrapperBase from a sequence of expressions. + * The expressions are grouped by their value and the count of each expression is stored in the + * OpRefWrapperBase entry. + * @param exprArr the sequence of expressions + * @return a sequence of OpRefWrapperBase instances + */ + def fromRawExprSeq(exprArr: Seq[String]): Seq[R] +} diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/OperatorCounter.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/OperatorCounter.scala index fab9422aa..f91bedc49 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/OperatorCounter.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/OperatorCounter.scala @@ -38,21 +38,21 @@ case class OperatorCounter(planInfo: PlanInfo) { * @param stages The set of stages where the operator appears. */ case class OperatorData( - opRef: OperatorRefBase, + opRef: OpRef, var count: Int = 0, - var stages: Set[Int] = Set()) + var stages: Set[Int] = Set()) extends OpRefWrapperBase(opRef) // Summarizes the count information for an exec or expression, including whether it is supported. case class OperatorCountSummary( opData: OperatorData, isSupported: Boolean) - private val supportedMap: mutable.Map[OperatorRefBase, OperatorData] = mutable.Map() - private val unsupportedMap: mutable.Map[OperatorRefBase, OperatorData] = mutable.Map() + private val supportedMap: mutable.Map[OpRef, OperatorData] = mutable.Map() + private val unsupportedMap: mutable.Map[OpRef, OperatorData] = mutable.Map() // Returns a sequence of `OperatorCountSummary`, combining both supported and // unsupported operators. - def getOpsCountSummary(): Seq[OperatorCountSummary] = { + def getOpsCountSummary: Seq[OperatorCountSummary] = { supportedMap.values.map(OperatorCountSummary(_, isSupported = true)).toSeq ++ unsupportedMap.values.map(OperatorCountSummary(_, isSupported = false)).toSeq } @@ -60,44 +60,49 @@ case class OperatorCounter(planInfo: PlanInfo) { // Updates the operator data in the given map (supported or unsupported). // Increments the count and updates the stages where the operator appears. - private def updateOpRefEntry(opRef: OperatorRefBase, stages: Set[Int], - targetMap: mutable.Map[OperatorRefBase, OperatorData]): Unit = { + private def updateOpRefEntry(opRef: OpRef, stages: Set[Int], + targetMap: mutable.Map[OpRef, OperatorData], incrValue: Int = 1): Unit = { val operatorData = targetMap.getOrElseUpdate(opRef, OperatorData(opRef)) - operatorData.count += 1 + operatorData.count += incrValue operatorData.stages ++= stages } // Processes an `ExecInfo` node to update exec and expression counts. // Separates supported and unsupported execs and expressions into their respective maps. private def processExecInfo(execInfo: ExecInfo): Unit = { - val opMap = execInfo.isSupported match { - case true => supportedMap - case false => unsupportedMap + val opMap = if (execInfo.isSupported) { + supportedMap + } else { + unsupportedMap } updateOpRefEntry(execInfo.execRef, execInfo.stages, opMap) - // update the map for supported expressions. We should exclude the unsupported expressions. - execInfo.expressions.filterNot( - e => execInfo.unsupportedExprs.exists(exp => exp.opRef.equals(e))).foreach { expr => - updateOpRefEntry(expr, execInfo.stages, supportedMap) - } - // update the map for unsupported expressions - execInfo.unsupportedExprs.foreach { expr => - updateOpRefEntry(expr, execInfo.stages, unsupportedMap) + // Update the map for supported expressions. For unsupported expressions, + // we use the count stored in the supported expressions. + execInfo.expressions.foreach { expr => + val exprMap = + if (execInfo.unsupportedExprs.exists(unsupExec => + unsupExec.getOpRef.equals(expr.getOpRef))) { + // The expression skips because it exists in the unsupported expressions. + unsupportedMap + } else { + supportedMap + } + updateOpRefEntry(expr.getOpRef, execInfo.stages, exprMap, expr.count) } } - // Counts the execs and expressions in the execution plan. + // Counts the execs and expressions in the execution plan excluding clusterNodes + // (i.e., WholeStageCodeGen). private def countOperators(): Unit = { planInfo.execInfo.foreach { exec => - exec.isClusterNode match { - // we do not want to count the cluster nodes in that aggregation - case true => - if (exec.children.nonEmpty) { - exec.children.get.foreach { child => - processExecInfo(child) - } + if (exec.isClusterNode) { + if (exec.children.nonEmpty) { + exec.children.get.foreach { child => + processExecInfo(child) } - case false => processExecInfo(exec) + } + } else { + processExecInfo(exec) } } } diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/UnsupportedExprOpRef.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/UnsupportedExprOpRef.scala index 0e17d8f0d..e40cfd825 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/UnsupportedExprOpRef.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/ops/UnsupportedExprOpRef.scala @@ -25,7 +25,7 @@ package com.nvidia.spark.rapids.tool.planparser.ops * @param unsupportedReason A string describing why the expression is unsupported. */ case class UnsupportedExprOpRef(opRef: OpRef, - unsupportedReason: String) extends OperatorRefBase(opRef.value, opRef.opType) + unsupportedReason: String) extends OpRefWrapperBase(opRef) // Provides a factory method to create an instance from an expression name and unsupported reason. object UnsupportedExprOpRef { diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/PluginTypeChecker.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/PluginTypeChecker.scala index 44bbf9fa3..9e58ba967 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/PluginTypeChecker.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/PluginTypeChecker.scala @@ -388,7 +388,7 @@ class PluginTypeChecker(platform: Platform = PlatformFactory.createInstance(), } def getNotSupportedExprs(exprs: Seq[String]): Seq[UnsupportedExprOpRef] = { - exprs.collect { + exprs.distinct.collect { case expr if !isExprSupported(expr) => val reason = unsupportedOpsReasons.getOrElse(expr, "") UnsupportedExprOpRef(expr, reason) diff --git a/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/QualOutputWriter.scala b/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/QualOutputWriter.scala index 9dbe7c920..f82124feb 100644 --- a/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/QualOutputWriter.scala +++ b/core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/QualOutputWriter.scala @@ -166,7 +166,7 @@ class QualOutputWriter(outputDir: String, reportReadSchema: Boolean, sums.foreach { sum => QualOutputWriter.constructUnsupportedDetailedStagesDurationInfo(csvFileWriter, sum, headersAndSizes, - QualOutputWriter.CSV_DELIMITER, false) + QualOutputWriter.CSV_DELIMITER, prettyPrint = false) } } finally { csvFileWriter.close() @@ -888,15 +888,15 @@ object QualOutputWriter { planInfos.foreach { planInfo => val sqlIDCSVStr = planInfo.sqlID.toString val allOpsCount = OperatorCounter(planInfo) - .getOpsCountSummary().sortBy(oInfo => (-oInfo.opData.count, oInfo.opData.opRef.getOpName)) + .getOpsCountSummary.sortBy(oInfo => (-oInfo.opData.count, oInfo.opData.opRef.getOpName)) if (allOpsCount.nonEmpty) { val planBuffer = allOpsCount.map { opInfo => val supportFlag = if (opInfo.isSupported) supportedCSVStr else unsupportedCSVStr val stageStr = StringUtils.reformatCSVString(opInfo.opData.stages.mkString(":")) s"$appIDCSVStr$delimiter" + s"$sqlIDCSVStr$delimiter" + - s"${opInfo.opData.opRef.getOpTypeCSV}$delimiter" + - s"${opInfo.opData.opRef.getOpNameCSV}$delimiter${opInfo.opData.count}$delimiter" + + s"${opInfo.opData.getOpTypeCSV}$delimiter" + + s"${opInfo.opData.getOpNameCSV}$delimiter${opInfo.opData.count}$delimiter" + s"$supportFlag$delimiter" + s"$stageStr" } @@ -1102,32 +1102,36 @@ object QualOutputWriter { reformatCSV: Boolean = true): Unit = { val reformatCSVFunc = getReformatCSVFunc(reformatCSV) val appId = sumInfo.appId + val appIDStr = reformatCSVFunc(appId) val appDuration = sumInfo.estimatedInfo.appDur val dummyStageID = -1 val dummyStageDur = 0 val execIdGenerator = new AtomicLong(0) - def constructDetailedUnsupportedRow(unSupExecInfo: UnsupportedExecSummary, - stageId: Int, stageAppDuration: Long): String = { - val data = ListBuffer[(String, Int)]( - reformatCSVFunc(appId) -> headersAndSizes(APP_ID_STR), - unSupExecInfo.sqlId.toString -> headersAndSizes(SQL_ID_STR), - stageId.toString -> headersAndSizes(STAGE_ID_STR), - reformatCSVFunc(unSupExecInfo.execId.toString) -> headersAndSizes(EXEC_ID), - reformatCSVFunc(unSupExecInfo.finalOpType) -> headersAndSizes(UNSUPPORTED_TYPE), - unSupExecInfo.unsupportedOperatorCSVFormat -> headersAndSizes(UNSUPPORTED_OPERATOR), - reformatCSVFunc(unSupExecInfo.details) -> headersAndSizes(DETAILS), - stageAppDuration.toString -> headersAndSizes(STAGE_WALLCLOCK_DUR_STR), - appDuration.toString -> headersAndSizes(APP_DUR_STR), - reformatCSVFunc(unSupExecInfo.opAction.toString) -> headersAndSizes(EXEC_ACTION) - ) - constructOutputRow(data, delimiter, prettyPrint) + def constructDetailedUnsupportedRow( + appID: String, + unSupExecInfo: UnsupportedExecSummary, + stageId: String, + stageAppDuration: String): String = { + val reformatCSVFunc = getReformatCSVFunc(reformatCSV) + s"$appID" + delimiter + + s"${unSupExecInfo.sqlId}" + delimiter + + s"$stageId" + delimiter + + s"${unSupExecInfo.execId.toString}" + delimiter + + s"${reformatCSVFunc(unSupExecInfo.finalOpType)}" + delimiter + + s"${unSupExecInfo.unsupportedOperatorCSVFormat}" + delimiter + + s"${reformatCSVFunc(unSupExecInfo.details)}" + delimiter + + s"$stageAppDuration" + delimiter + + s"$appDuration" + delimiter + + s"${unSupExecInfo.opAction}\n" } def getUnsupportedRows(execI: ExecInfo, stageId: Int, stageDur: Long): String = { val results = execI.getUnsupportedExecSummaryRecord(execIdGenerator.getAndIncrement()) + val stageIDStr = stageId.toString + val stageDurStr = stageDur.toString results.map { unsupportedExecSummary => - constructDetailedUnsupportedRow(unsupportedExecSummary, stageId, stageDur) + constructDetailedUnsupportedRow(appIDStr, unsupportedExecSummary, stageIDStr, stageDurStr) }.mkString } diff --git a/core/src/test/scala/com/nvidia/spark/rapids/tool/planparser/SqlPlanParserSuite.scala b/core/src/test/scala/com/nvidia/spark/rapids/tool/planparser/SqlPlanParserSuite.scala index e31064851..771484c14 100644 --- a/core/src/test/scala/com/nvidia/spark/rapids/tool/planparser/SqlPlanParserSuite.scala +++ b/core/src/test/scala/com/nvidia/spark/rapids/tool/planparser/SqlPlanParserSuite.scala @@ -22,6 +22,7 @@ import scala.collection.mutable import scala.util.control.NonFatal import com.nvidia.spark.rapids.tool.ToolTestUtils +import com.nvidia.spark.rapids.tool.planparser.ops.{ExprOpRef, OpRef} import com.nvidia.spark.rapids.tool.qualification._ import org.scalatest.Matchers.{be, contain, convertToAnyShouldWrapper} import org.scalatest.exceptions.TestFailedException @@ -1319,46 +1320,69 @@ class SQLPlanParserSuite extends BasePlanParserSuite { test("Parsing Conditional Expressions") { // scalastyle:off line.size.limit - val expressionsMap: mutable.HashMap[String, Array[String]] = mutable.HashMap( - "(((lower(partition_act#90) = moduleview) && (isnotnull(productarr#22) && NOT (productarr#22=[]))) || (lower(moduletype#13) = saveforlater))" -> - Array("lower", "isnotnull", "EqualTo", "And", "Not", "Or"), + val expressionsMap: mutable.HashMap[String, Map[String, Int]] = mutable.HashMap( + "(((lower(partition_act#90) = moduleview) && (isnotnull(productarr#22) && NOT (productarr#22 = []))) || (lower(moduletype#13) = saveforlater))" -> + Map("lower" -> 2, + "isnotnull" -> 1, + "EqualTo" -> 3, + "And" -> 2, + "Not" -> 1, + "Or" -> 1), "(IsNotNull(c_customer_id))" -> - Array("IsNotNull"), + Map("IsNotNull" -> 1), "(isnotnull(names#15) AND StartsWith(names#15, OR))" -> - Array("isnotnull", "And", "StartsWith"), + Map("isnotnull" -> 1, + "StartsWith" -> 1, + "And" -> 1), "((isnotnull(s_state#68) AND (s_state#68 = TN)) OR (hex(cast(value#0 as bigint)) = B))" -> - Array("isnotnull", "And", "Or", "hex", "EqualTo"), + Map("isnotnull" -> 1, + "And" -> 1, + "Or" -> 1, + "hex" -> 1, + "EqualTo" -> 2), // Test that AND followed by '(' without space can be parsed "((isnotnull(s_state#68) AND(s_state#68 = TN)) OR (hex(cast(value#0 as bigint)) = B))" -> - Array("isnotnull", "And", "Or", "hex", "EqualTo"), + Map("isnotnull" -> 1, + "And" -> 1, + "Or" -> 1, + "hex" -> 1, + "EqualTo" -> 2), "(((isnotnull(d_year#498) AND isnotnull(d_moy#500)) AND (d_year#498 = 1998)) AND (d_moy#500 = 12))" -> - Array("isnotnull", "And", "EqualTo"), + Map("isnotnull" -> 2, + "And" -> 3, + "EqualTo" -> 2), "IsNotNull(d_year) AND IsNotNull(d_moy) AND EqualTo(d_year,1998) AND EqualTo(d_moy,12)" -> - Array("IsNotNull", "And", "EqualTo"), + Map("IsNotNull" -> 2, + "EqualTo" -> 2, + "And" -> 3), // check that a predicate with a single variable name is fine "flagVariable" -> - Array(), + Map(), // check that a predicate with a single function call "isnotnull(c_customer_sk#412)" -> - Array("isnotnull"), + Map("isnotnull" -> 1), "((substr(ca_zip#457, 1, 5) IN (85669,86197,88274,83405,86475,85392,85460,80348,81792) OR ca_state#456 IN (CA,WA,GA)) OR (cs_sales_price#20 > 500.00))" -> - Array("substr", "In", "Or", "GreaterThan"), + Map("substr" -> 1, + "In" -> 2, + "Or" -> 2, + "GreaterThan" -> 1), // test the operator is at the beginning of expression and not followed by space "NOT(isnotnull(d_moy))" -> - Array("Not", "isnotnull"), + Map("isnotnull" -> 1, + "Not" -> 1), // test the shiftright operator(since spark-4.0) "((isnotnull(d_year#498) AND isnotnull(d_moy#500)) AND (d_year#498 >> 1) >= 100)" -> - Array("isnotnull", "And", "GreaterThanOrEqual", "ShiftRight") + Map("isnotnull" -> 2, + "And" -> 2, + "ShiftRight" -> 1, + "GreaterThanOrEqual" -> 1) ) // scalastyle:on line.size.limit - for ((condExpr, expectedExpression) <- expressionsMap) { - val parsedExpressionsMine = SQLPlanParser.parseConditionalExpressions(condExpr) - val currOutput = parsedExpressionsMine.sorted - val expectedOutput = expectedExpression.sorted - assert(currOutput sameElements expectedOutput, - s"The parsed expressions are not as expected. Expression: ${condExpr}, " + - s"Expected: ${expectedOutput.mkString}, " + - s"Output: ${currOutput.mkString}") + for ((condExpr, expectedExpressionCounts) <- expressionsMap) { + val rawExpressions = SQLPlanParser.parseConditionalExpressions(condExpr) + val expected = expectedExpressionCounts.map(e => ExprOpRef(OpRef.fromExpr(e._1), e._2)) + val actualExpressions = ExprOpRef.fromRawExprSeq(rawExpressions) + actualExpressions should ===(expected) } } @@ -1403,10 +1427,18 @@ class SQLPlanParserSuite extends BasePlanParserSuite { "AND (content_name_16#197L = 1)) AND NOT (split(split(split(replace(replace(replace" + "(replace(trim(replace(cast(unbase64(content#192) as string), , ), Some( )), *., ), *, ), " + "https://, ), http://, ), /, -1)[0], :, -1)[0], \\?, -1)[0] = ))" - val expected = Array("isnotnull", "split", "replace", "trim", "unbase64", "And", - "EqualTo", "Not") - val expressions = SQLPlanParser.parseFilterExpressions(exprString) - expressions should ===(expected) + val expected = Map( + "isnotnull" -> 3, + "split" -> 3, + "replace" -> 5, + "trim" -> 1, + "unbase64" -> 1, + "And" -> 6, + "EqualTo" -> 4, // EqualTo comes from the = operator + "Not" -> 2).map(e => ExprOpRef(OpRef.fromExpr(e._1), e._2)) + val rawExpressions = SQLPlanParser.parseFilterExpressions(exprString) + val actualExpressions = ExprOpRef.fromRawExprSeq(rawExpressions) + actualExpressions should ===(expected) } @@ -1418,9 +1450,16 @@ class SQLPlanParserSuite extends BasePlanParserSuite { "THEN concat(replace(cast(unbase64(content#192) as string), , ), %) " + "ELSE replace(replace(replace(cast(unbase64(content#192) as string), , ), %, " + "\\%), *, %) END#200])" - val expected = Array("replace", "concat", "instr", "split", "trim", "unbase64") - val expressions = SQLPlanParser.parseAggregateExpressions(exprString) - expressions should ===(expected) + val expected = Map( + "replace" -> 10, + "concat" -> 1, + "instr" -> 1, + "split" -> 3, + "trim" -> 1, + "unbase64" -> 4).map(e => ExprOpRef(OpRef.fromExpr(e._1), e._2)) + val rawExpressions = SQLPlanParser.parseAggregateExpressions(exprString) + val actualExpressions = ExprOpRef.fromRawExprSeq(rawExpressions) + actualExpressions should ===(expected) } runConditionalTest("promote_precision is supported for Spark LT 3.4.0: issue-517", @@ -1522,7 +1561,7 @@ class SQLPlanParserSuite extends BasePlanParserSuite { "gid#1296," + "CAST((IF((supersql_t12.`ret_type` = 2), 1, 0)) AS BIGINT)#1300L]]" // Only "IF" should be picked up as a function name - val expected = Array("IF") + val expected = Array("IF", "IF", "IF") val expressions = SQLPlanParser.parseExpandExpressions(exprString) expressions should ===(expected) } From 96041332f9a7d01146ca91d31294433ae472b502 Mon Sep 17 00:00:00 2001 From: spark-rapids automation <70000568+nvauto@users.noreply.github.com> Date: Fri, 6 Dec 2024 16:35:24 +0000 Subject: [PATCH 22/22] Update dev-version by jenkins-spark-rapids-tools-auto-release-96 Signed-off-by: spark-rapids automation <70000568+nvauto@users.noreply.github.com> --- core/pom.xml | 2 +- user_tools/src/spark_rapids_pytools/__init__.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/core/pom.xml b/core/pom.xml index fd9057ddf..cde7561fb 100644 --- a/core/pom.xml +++ b/core/pom.xml @@ -23,7 +23,7 @@ rapids-4-spark-tools_2.12 RAPIDS Accelerator for Apache Spark tools RAPIDS Accelerator for Apache Spark tools - 24.10.2-SNAPSHOT + 24.10.3-SNAPSHOT jar http://github.com/NVIDIA/spark-rapids-tools diff --git a/user_tools/src/spark_rapids_pytools/__init__.py b/user_tools/src/spark_rapids_pytools/__init__.py index 84452ec1c..f4ec6f064 100644 --- a/user_tools/src/spark_rapids_pytools/__init__.py +++ b/user_tools/src/spark_rapids_pytools/__init__.py @@ -16,7 +16,7 @@ from spark_rapids_pytools.build import get_version, get_spark_dep_version -VERSION = '24.10.2' +VERSION = '24.10.3' # defines the default runtime build version for the user tools environment SPARK_DEP_VERSION = '350' __version__ = get_version(VERSION)