The ingestion job spec is used while generating, running, and pushing segments from the input files.
The Job spec can be in either YAML or JSON format (0.5.0 onwards). Property names remain the same in both formats.
To use the JSON format, add the propertyjob-spec-format=jsonin the properties file while launching the ingestion job. The properties file can be passed as follows
pinot-admin.sh LaunchDataIngestionJob \
-jobSpecFile /path/to/job_spec.json \
-propertyFile /path/to/job.properties
Users are allowed to define some variables in the job spec file to make it a template then passing the variables at runtime.
Templating is based on Groovy SimpleTemplateEngine.
E.g. users can specify below in the job spec file:
inputDirURI: 'file:///path/to/input/${year}/${month}/${day}/${hour}'
The values for the template strings in the jobSpecFile can be passed in one of the following three ways mentioned in their order of precedence, for same key, 1 will override 2 will override 3.
- Values from the
-valuesarray passed from the Cmd Line. See Launch Data Ingestion Job - Values from the environment variables
- Values from the propertyFile
Still take above inputDirURI as example,
We can define a job.config file with below content:
year=2020
month=05
day=01
hour=00
Above properties can be override by environment variables
export month=06
export day=02
export hour=03
From the command line, user can further override those keys using flag -values,
pinot-admin.sh LaunchDataIngestionJob \
-jobSpecFile /path/to/job_spec.json \
-propertyFile job.confg \
-values day=03 hour=04After that the real ingestion spec passed to ingestion job will have inputDirURI as 'file:///path/to/input/2020/06/03/04'
The following configurations are supported by Pinot
| Property | Description |
|---|---|
| executionFrameworkSpec | Contains config related to the executor to use to ingest data. See Execution Framework Spec |
| jobType | Type of job to execute. The following types are supported
Note: For production environments where Pinot Deep Store is configured, it's recommended to use SegmentCreationAndMetadataPush |
| inputDirURI | Absolute Path along with scheme of the directory containing all the files to be ingested, e.g. s3://bucket/path/to/input, /path/to/local/input |
| includeFileNamePattern | Only Files matching this pattern will be included from Examples: Use Alternatively, use |
| excludeFileNamePattern | Exclude file name pattern, supported glob pattern. Similar usage as includeFilePatternName |
| searchRecursively | Set to true to explicitly search input files recursively from inputDirURI. It is set to true by default for now. |
| outputDirURI | Absolute Path along with scheme of the directory where to output all the segments. |
| overwriteOutput | Set to true to overwrite segments if already present in the output directory. Or set tofalseto raise exceptions. |
| pinotFSSpecs | List of all the filesystems to be used for ingestions. You can mention multiple values in case input and output directories are present in different filesystems. For more details, scroll down to Pinot FS Spec. |
| tableSpec | Defines table name and where to fetch corresponding table config and table schema. For more details, scroll down to Table Spec. |
| recordReaderSpec | Parser to use to read and decode input data. For more details, scroll down to Record Reader Spec. |
| segmentNameGeneratorSpec | Defines how the names of the segments will be. For more details, scroll down to Segment Name Generator Spec. |
| pinotClusterSpecs | Defines the Pinot Cluster Access Point. For more details, scroll down to Pinot Cluster Spec. |
| pushJobSpec | Defines segment push job-related configuration. For more details, scroll down to Push Job Spec. |
executionFrameworkSpec:
name: 'spark'
segmentGenerationJobRunnerClassName: 'org.apache.pinot.plugin.ingestion.batch.spark.SparkSegmentGenerationJobRunner'
segmentTarPushJobRunnerClassName: 'org.apache.pinot.plugin.ingestion.batch.spark.SparkSegmentTarPushJobRunner'
segmentUriPushJobRunnerClassName: 'org.apache.pinot.plugin.ingestion.batch.spark.SparkSegmentUriPushJobRunner'
segmentMetadataPushJobRunnerClassName: 'org.apache.pinot.plugin.ingestion.batch.spark.SparkSegmentMetadataPushJobRunner'
extraConfigs:
stagingDir: hdfs://examples/batch/airlineStats/staging
# Recommended to set jobType to SegmentCreationAndMetadataPush for production environments where Pinot Deep Store is configured
jobType: SegmentCreationAndTarPush
inputDirURI: 'examples/batch/airlineStats/rawdata'
includeFileNamePattern: 'glob:**/*.avro'
searchRecursively: true
outputDirURI: 'hdfs:///examples/batch/airlineStats/segments'
overwriteOutput: true
pinotFSSpecs:
- scheme: hdfs
className: org.apache.pinot.plugin.filesystem.HadoopPinotFS
- scheme: file
className: org.apache.pinot.spi.filesystem.LocalPinotFS
recordReaderSpec:
className: 'org.apache.pinot.plugin.inputformat.avro.AvroRecordReader'
tableSpec:
tableName: 'airlineStats'
schemaURI: 'http://localhost:9000/tables/airlineStats/schema'
tableConfigURI: 'http://localhost:9000/tables/airlineStats'
segmentNameGeneratorSpec:
type: normalizedDate
configs:
segment.name.prefix: 'airlineStats_batch'
exclude.sequence.id: true
pinotClusterSpecs:
- controllerURI: 'http://localhost:9000'
pushJobSpec:
pushParallelism: 2
pushAttempts: 2
pushRetryIntervalMillis: 1000
The configs specify the execution framework to use to ingest data. Check out Batch Ingestion for configs related to all the supported frameworks
| Property | Description |
|---|---|
| name | name of the execution framework. can be one of spark,hadoop or standalone |
| segmentGenerationJobRunnerClassName | The class name implements org.apache.pinot.spi.ingestion.batch.runner.IngestionJobRunner interface to run the segment generation job |
| segmentTarPushJobRunnerClassName | The class name implements org.apache.pinot.spi.ingestion.batch.runner.IngestionJobRunner interface to push the segment TAR file |
| segmentUriPushJobRunnerClassName | The class name implements org.apache.pinot.spi.ingestion.batch.runner.IngestionJobRunner interface to send segment URI |
| segmentMetadataPushJobRunnerClassName | The class name implements org.apache.pinot.spi.ingestion.batch.runner.IngestionJobRunner interface to send segment Metadata |
| extraConfigs | Key-value pairs of configs related to the framework of the executions |
executionFrameworkSpec:
name: 'standalone'
segmentGenerationJobRunnerClassName: 'org.apache.pinot.plugin.ingestion.batch.standalone.SegmentGenerationJobRunner'
segmentTarPushJobRunnerClassName: 'org.apache.pinot.plugin.ingestion.batch.standalone.SegmentTarPushJobRunner'
segmentUriPushJobRunnerClassName: 'org.apache.pinot.plugin.ingestion.batch.standalone.SegmentUriPushJobRunner'
segmentMetadataPushJobRunnerClassName: 'org.apache.pinot.plugin.ingestion.batch.standalone.SegmentMetadataPushJobRunner'
| field | description |
|---|---|
| schema | used to identify a PinotFS. E.g. local, hdfs, dbfs, etc |
| className | Class name used to create the PinotFS instance. E.g.
|
| configs | configs used to init PinotFS instance |
Table spec is used to specify the table in which data should be populated along with schema.
| Property | Description |
|---|---|
| tableName | name of the table in which to populate the data |
| schemaURI | location from which to read the schema for the table. Supports both File systems as well as HTTP URI |
| tableConfigURI | location from which to read the config for the table. Supports both File systems as well as HTTP URI |
tableSpec:
tableName: 'airlineStats'
schemaURI: 'http://localhost:9000/tables/airlineStats/schema'
tableConfigURI: 'http://localhost:9000/tables/airlineStats'
| field | description |
|---|---|
| dataFormat | Record data format, e.g. 'avro', 'parquet', 'orc', 'csv', 'json', 'thrift' etc. |
| className | Corresponding RecordReader class name. E.g. org.apache.pinot.plugin.inputformat.avro.AvroRecordReader org.apache.pinot.plugin.inputformat.csv.CSVRecordReader org.apache.pinot.plugin.inputformat.parquet.ParquetRecordReader org.apache.pinot.plugin.inputformat.json.JSONRecordReader org.apache.pinot.plugin.inputformat.orc.ORCRecordReader org.apache.pinot.plugin.inputformat.thrift.ThriftRecordReader |
| configClassName | Corresponding RecordReaderConfig class name, it's mandatory for CSV and Thrift file format. E.g. org.apache.pinot.plugin.inputformat.csv.CSVRecordReaderConfig org.apache.pinot.plugin.inputformat.thrift.ThriftRecordReaderConfig |
| configs | Used to init RecordReaderConfig class name, this config is required for CSV and Thrift data format. |
| Property | Description |
|---|---|
| type | The type of name generator to use. If not specified, an appropriate type will be inferred based on segment generator config properties. The following values are supported -
|
| configs | Configs to init SegmentNameGenerator |
| segment.name | For fixed SegmentNameGenerator. Explicitly set the segment name. |
| segment.name.postfix | For |
| segment.name.prefix | For |
| exclude.sequence.id | Whether to include sequence ids in segment name. Needed when there are multiple segments for the same time range. |
| use.global.directory.sequence.id | Assign sequence ids to input files based on all input files under the directory. Set to |
| append.uuid.to.segment.name | If the input data doesn't contain a time column, set this to true to generate unique segment names. Can be used with any name generator type. |
| file.path.pattern | For inputFile, a Java regular expression used to match against the input file URI. e.g. '.+/(.+).gz' to extract file name from a .gz file without the extension |
| segment.name.template | For inputFile , the string template that should be used to substitute extracted fileName. Currently only supports ${filePathPattern:<match group>} |
segmentNameGeneratorSpec:
type: normalizedDate
configs:
segment.name.prefix: 'airlineStats_batch'
exclude.sequence.id: true
To set the segment name to be the same as the input file name (without the trailing .gz), use:
segmentNameGeneratorSpec:
type: inputFile
configs:
file.path.pattern: '.+/(.+)\.gz'
segment.name.template: '\${filePathPattern:\1}'
Note that $ in the yaml file must be escaped, since Pinot uses Groovy's SimpleTemplateEngine to process the yaml file, and a raw $ is treated as a template specifier.
| Property | Description |
|---|---|
| controllerURI | URI to use to fetch table/schema information and push data |
pinotClusterSpecs:
- controllerURI: 'http://localhost:9000'
| Property | Description |
|---|---|
| pushAttempts | Number of attempts for push job. Default is 1, which means no retry |
| pushParallelism | Workers to use for push job. Default is 1 |
| pushRetryIntervalMillis | Time in milliseconds to wait for between retry attempts Default is 1 second. |
| segmentUriPrefix | append this string before the path of the push destination. Generally, it is the scheme of the filesystem e.g. s3:// , file:// etc. |
| segmentUriSuffix | append this string after the path of the push destination. |
| pushFileNamePattern | segment name pattern for which segments to push, supported glob and regex patterns. E.g. 'glob:**2023-01*' will push all the segment files under the outputDirURI whose names contain '2023-01'. |
| batchSegmentUpload | Boolean field for which the default value is false. When the value is set to true segments are uploaded in batch mode which is faster than uploading segments one after the other. Works when the jobType is set to SegmentMetadataPush |
pushJobSpec:
pushParallelism: 2
pushAttempts: 2
pushRetryIntervalMillis: 1000
segmentUriPrefix : 'file://'
segmentUriSuffix : my-dir/
pushFileNamePattern : glob:\*\*2023-01\*