Merge branch 'datahub-project:master' into master

docs/what/urn.md

@@ -41,4 +41,4 @@ There are a few restrictions when creating an urn:
 2. Parentheses are reserved characters in URN fields: `( , )`
 3. Colons are reserved characters in URN fields: `:`
 
-Please do not use these characters when creating or generating urns.
+Please do not use these characters when creating or generating urns. One approach is to use URL encoding for the characters.

metadata-ingestion/src/datahub/ingestion/source/iceberg/iceberg.py

@@ -1,10 +1,15 @@
 import json
 import logging
+import threading
 import uuid
 from typing import Any, Dict, Iterable, List, Optional
 
 from pyiceberg.catalog import Catalog
-from pyiceberg.exceptions import NoSuchIcebergTableError
+from pyiceberg.exceptions import (
+    NoSuchIcebergTableError,
+    NoSuchNamespaceError,
+    NoSuchPropertyException,
+)
 from pyiceberg.schema import Schema, SchemaVisitorPerPrimitiveType, visit
 from pyiceberg.table import Table
 from pyiceberg.typedef import Identifier
@@ -75,6 +80,8 @@
     OwnershipClass,
     OwnershipTypeClass,
 )
+from datahub.utilities.perf_timer import PerfTimer
+from datahub.utilities.threaded_iterator_executor import ThreadedIteratorExecutor
 
 LOGGER = logging.getLogger(__name__)
 logging.getLogger("azure.core.pipeline.policies.http_logging_policy").setLevel(
@@ -130,74 +137,149 @@ def get_workunit_processors(self) -> List[Optional[MetadataWorkUnitProcessor]]:
         ]
 
     def _get_datasets(self, catalog: Catalog) -> Iterable[Identifier]:
-        for namespace in catalog.list_namespaces():
-            yield from catalog.list_tables(namespace)
+        namespaces = catalog.list_namespaces()
+        LOGGER.debug(
+            f"Retrieved {len(namespaces)} namespaces, first 10: {namespaces[:10]}"
+        )
+        self.report.report_no_listed_namespaces(len(namespaces))
+        tables_count = 0
+        for namespace in namespaces:
+            try:
+                tables = catalog.list_tables(namespace)
+                tables_count += len(tables)
+                LOGGER.debug(
+                    f"Retrieved {len(tables)} tables for namespace: {namespace}, in total retrieved {tables_count}, first 10: {tables[:10]}"
+                )
+                self.report.report_listed_tables_for_namespace(
+                    ".".join(namespace), len(tables)
+                )
+                yield from tables
+            except NoSuchNamespaceError:
+                self.report.report_warning(
+                    "no-such-namespace",
+                    f"Couldn't list tables for namespace {namespace} due to NoSuchNamespaceError exception",
+                )
+                LOGGER.warning(
+                    f"NoSuchNamespaceError exception while trying to get list of tables from namespace {namespace}, skipping it",
+                )
+            except Exception as e:
+                self.report.report_failure(
+                    "listing-tables-exception",
+                    f"Couldn't list tables for namespace {namespace} due to {e}",
+                )
+                LOGGER.exception(
+                    f"Unexpected exception while trying to get list of tables for namespace {namespace}, skipping it"
+                )
 
     def get_workunits_internal(self) -> Iterable[MetadataWorkUnit]:
-        try:
-            catalog = self.config.get_catalog()
-        except Exception as e:
-            LOGGER.error("Failed to get catalog", exc_info=True)
-            self.report.report_failure("get-catalog", f"Failed to get catalog: {e}")
-            return
+        thread_local = threading.local()
 
-        for dataset_path in self._get_datasets(catalog):
+        def _process_dataset(dataset_path: Identifier) -> Iterable[MetadataWorkUnit]:
+            LOGGER.debug(f"Processing dataset for path {dataset_path}")
             dataset_name = ".".join(dataset_path)
             if not self.config.table_pattern.allowed(dataset_name):
                 # Dataset name is rejected by pattern, report as dropped.
                 self.report.report_dropped(dataset_name)
-                continue
-
+                return
             try:
-                # Try to load an Iceberg table.  Might not contain one, this will be caught by NoSuchIcebergTableError.
-                table = catalog.load_table(dataset_path)
+                if not hasattr(thread_local, "local_catalog"):
+                    LOGGER.debug(
+                        f"Didn't find local_catalog in thread_local ({thread_local}), initializing new catalog"
+                    )
+                    thread_local.local_catalog = self.config.get_catalog()
+
+                with PerfTimer() as timer:
+                    table = thread_local.local_catalog.load_table(dataset_path)
+                    time_taken = timer.elapsed_seconds()
+                    self.report.report_table_load_time(time_taken)
+                LOGGER.debug(
+                    f"Loaded table: {table.identifier}, time taken: {time_taken}"
+                )
                 yield from self._create_iceberg_workunit(dataset_name, table)
+            except NoSuchPropertyException as e:
+                self.report.report_warning(
+                    "table-property-missing",
+                    f"Failed to create workunit for {dataset_name}. {e}",
+                )
+                LOGGER.warning(
+                    f"NoSuchPropertyException while processing table {dataset_path}, skipping it.",
+                )
             except NoSuchIcebergTableError as e:
+                self.report.report_warning(
+                    "no-iceberg-table",
+                    f"Failed to create workunit for {dataset_name}. {e}",
+                )
+                LOGGER.warning(
+                    f"NoSuchIcebergTableError while processing table {dataset_path}, skipping it.",
+                )
+            except Exception as e:
                 self.report.report_failure("general", f"Failed to create workunit: {e}")
                 LOGGER.exception(
                     f"Exception while processing table {dataset_path}, skipping it.",
                 )
 
+        try:
+            catalog = self.config.get_catalog()
+        except Exception as e:
+            self.report.report_failure("get-catalog", f"Failed to get catalog: {e}")
+            return
+
+        for wu in ThreadedIteratorExecutor.process(
+            worker_func=_process_dataset,
+            args_list=[(dataset_path,) for dataset_path in self._get_datasets(catalog)],
+            max_workers=self.config.processing_threads,
+        ):
+            yield wu
+
     def _create_iceberg_workunit(
         self, dataset_name: str, table: Table
     ) -> Iterable[MetadataWorkUnit]:
-        self.report.report_table_scanned(dataset_name)
-        dataset_urn: str = make_dataset_urn_with_platform_instance(
-            self.platform,
-            dataset_name,
-            self.config.platform_instance,
-            self.config.env,
-        )
-        dataset_snapshot = DatasetSnapshot(
-            urn=dataset_urn,
-            aspects=[Status(removed=False)],
-        )
-
-        # Dataset properties aspect.
-        custom_properties = table.metadata.properties.copy()
-        custom_properties["location"] = table.metadata.location
-        custom_properties["format-version"] = str(table.metadata.format_version)
-        custom_properties["partition-spec"] = str(self._get_partition_aspect(table))
-        if table.current_snapshot():
-            custom_properties["snapshot-id"] = str(table.current_snapshot().snapshot_id)
-            custom_properties["manifest-list"] = table.current_snapshot().manifest_list
-        dataset_properties = DatasetPropertiesClass(
-            name=table.name()[-1],
-            tags=[],
-            description=table.metadata.properties.get("comment", None),
-            customProperties=custom_properties,
-        )
-        dataset_snapshot.aspects.append(dataset_properties)
+        with PerfTimer() as timer:
+            self.report.report_table_scanned(dataset_name)
+            LOGGER.debug(f"Processing table {dataset_name}")
+            dataset_urn: str = make_dataset_urn_with_platform_instance(
+                self.platform,
+                dataset_name,
+                self.config.platform_instance,
+                self.config.env,
+            )
+            dataset_snapshot = DatasetSnapshot(
+                urn=dataset_urn,
+                aspects=[Status(removed=False)],
+            )
 
-        # Dataset ownership aspect.
-        dataset_ownership = self._get_ownership_aspect(table)
-        if dataset_ownership:
-            dataset_snapshot.aspects.append(dataset_ownership)
+            # Dataset properties aspect.
+            custom_properties = table.metadata.properties.copy()
+            custom_properties["location"] = table.metadata.location
+            custom_properties["format-version"] = str(table.metadata.format_version)
+            custom_properties["partition-spec"] = str(self._get_partition_aspect(table))
+            if table.current_snapshot():
+                custom_properties["snapshot-id"] = str(
+                    table.current_snapshot().snapshot_id
+                )
+                custom_properties[
+                    "manifest-list"
+                ] = table.current_snapshot().manifest_list
+            dataset_properties = DatasetPropertiesClass(
+                name=table.name()[-1],
+                tags=[],
+                description=table.metadata.properties.get("comment", None),
+                customProperties=custom_properties,
+            )
+            dataset_snapshot.aspects.append(dataset_properties)
+            # Dataset ownership aspect.
+            dataset_ownership = self._get_ownership_aspect(table)
+            if dataset_ownership:
+                LOGGER.debug(
+                    f"Adding ownership: {dataset_ownership} to the dataset {dataset_name}"
+                )
+                dataset_snapshot.aspects.append(dataset_ownership)
 
-        schema_metadata = self._create_schema_metadata(dataset_name, table)
-        dataset_snapshot.aspects.append(schema_metadata)
+            schema_metadata = self._create_schema_metadata(dataset_name, table)
+            dataset_snapshot.aspects.append(schema_metadata)
 
-        mce = MetadataChangeEvent(proposedSnapshot=dataset_snapshot)
+            mce = MetadataChangeEvent(proposedSnapshot=dataset_snapshot)
+        self.report.report_table_processing_time(timer.elapsed_seconds())
         yield MetadataWorkUnit(id=dataset_name, mce=mce)
 
         dpi_aspect = self._get_dataplatform_instance_aspect(dataset_urn=dataset_urn)

metadata-ingestion/src/datahub/ingestion/source/iceberg/iceberg_common.py

@@ -2,6 +2,7 @@
 from dataclasses import dataclass, field
 from typing import Any, Dict, List, Optional
 
+from humanfriendly import format_timespan
 from pydantic import Field, validator
 from pyiceberg.catalog import Catalog, load_catalog
 
@@ -18,6 +19,7 @@
     OperationConfig,
     is_profiling_enabled,
 )
+from datahub.utilities.stats_collections import TopKDict, int_top_k_dict
 
 logger = logging.getLogger(__name__)
 
@@ -75,6 +77,9 @@ class IcebergSourceConfig(StatefulIngestionConfigBase, DatasetSourceConfigMixin)
         description="Iceberg table property to look for a `CorpGroup` owner.  Can only hold a single group value.  If property has no value, no owner information will be emitted.",
     )
     profiling: IcebergProfilingConfig = IcebergProfilingConfig()
+    processing_threads: int = Field(
+        default=1, description="How many threads will be processing tables"
+    )
 
     @validator("catalog", pre=True, always=True)
     def handle_deprecated_catalog_format(cls, value):
@@ -131,17 +136,72 @@ def get_catalog(self) -> Catalog:
 
         # Retrieve the dict associated with the one catalog entry
         catalog_name, catalog_config = next(iter(self.catalog.items()))
+        logger.debug(
+            "Initializing the catalog %s with config: %s", catalog_name, catalog_config
+        )
         return load_catalog(name=catalog_name, **catalog_config)
 
 
+class TimingClass:
+    times: List[int]
+
+    def __init__(self):
+        self.times = []
+
+    def add_timing(self, t):
+        self.times.append(t)
+
+    def __str__(self):
+        if len(self.times) == 0:
+            return "no timings reported"
+        self.times.sort()
+        total = sum(self.times)
+        avg = total / len(self.times)
+        return str(
+            {
+                "average_time": format_timespan(avg, detailed=True, max_units=3),
+                "min_time": format_timespan(self.times[0], detailed=True, max_units=3),
+                "max_time": format_timespan(self.times[-1], detailed=True, max_units=3),
+                # total_time does not provide correct information in case we run in more than 1 thread
+                "total_time": format_timespan(total, detailed=True, max_units=3),
+            }
+        )
+
+
 @dataclass
 class IcebergSourceReport(StaleEntityRemovalSourceReport):
     tables_scanned: int = 0
     entities_profiled: int = 0
     filtered: List[str] = field(default_factory=list)
+    load_table_timings: TimingClass = field(default_factory=TimingClass)
+    processing_table_timings: TimingClass = field(default_factory=TimingClass)
+    profiling_table_timings: TimingClass = field(default_factory=TimingClass)
+    listed_namespaces: int = 0
+    total_listed_tables: int = 0
+    tables_listed_per_namespace: TopKDict[str, int] = field(
+        default_factory=int_top_k_dict
+    )
+
+    def report_listed_tables_for_namespace(
+        self, namespace: str, no_tables: int
+    ) -> None:
+        self.tables_listed_per_namespace[namespace] = no_tables
+        self.total_listed_tables += no_tables
+
+    def report_no_listed_namespaces(self, amount: int) -> None:
+        self.listed_namespaces = amount
 
     def report_table_scanned(self, name: str) -> None:
         self.tables_scanned += 1
 
     def report_dropped(self, ent_name: str) -> None:
         self.filtered.append(ent_name)
+
+    def report_table_load_time(self, t: float) -> None:
+        self.load_table_timings.add_timing(t)
+
+    def report_table_processing_time(self, t: float) -> None:
+        self.processing_table_timings.add_timing(t)
+
+    def report_table_profiling_time(self, t: float) -> None:
+        self.profiling_table_timings.add_timing(t)