From 642fb404ec9848e44b96b1d0c9c8c677dbe92ba0 Mon Sep 17 00:00:00 2001
From: Tamas Nemeth
Date: Tue, 16 Jul 2024 11:50:15 +0200
Subject: [PATCH 01/23] fix(ingest/spark): Fixing Micrometer warning (#10882)
---
metadata-integration/java/spark-lineage-beta/README.md | 4 +++-
.../src/main/java/datahub/spark/DatahubSparkListener.java | 8 +-------
2 files changed, 4 insertions(+), 8 deletions(-)
diff --git a/metadata-integration/java/spark-lineage-beta/README.md b/metadata-integration/java/spark-lineage-beta/README.md
index a643919664b07..b0753936dd677 100644
--- a/metadata-integration/java/spark-lineage-beta/README.md
+++ b/metadata-integration/java/spark-lineage-beta/README.md
@@ -346,8 +346,10 @@ Use Java 8 to build the project. The project uses Gradle as the build tool. To b
+
## Changelog
+### Version 0.2.14
+- Fix warning about MeterFilter warning from Micrometer
-### Version 0.2.12
+### Version 0.2.13
- Silencing some chatty warnings in RddPathUtils
### Version 0.2.12
diff --git a/metadata-integration/java/spark-lineage-beta/src/main/java/datahub/spark/DatahubSparkListener.java b/metadata-integration/java/spark-lineage-beta/src/main/java/datahub/spark/DatahubSparkListener.java
index 54bb3821edded..96fa74d1bca1f 100644
--- a/metadata-integration/java/spark-lineage-beta/src/main/java/datahub/spark/DatahubSparkListener.java
+++ b/metadata-integration/java/spark-lineage-beta/src/main/java/datahub/spark/DatahubSparkListener.java
@@ -287,13 +287,7 @@ private static void initializeMetrics(OpenLineageConfig openLineageConfig) {
} else {
disabledFacets = "";
}
- meterRegistry
- .config()
- .commonTags(
- Tags.of(
- Tag.of("openlineage.spark.integration.version", Versions.getVersion()),
- Tag.of("openlineage.spark.version", sparkVersion),
- Tag.of("openlineage.spark.disabled.facets", disabledFacets)));
+
((CompositeMeterRegistry) meterRegistry)
.getRegistries()
.forEach(
From ea2216ad6453d1b7dad144bef46ca7fd64cb3f00 Mon Sep 17 00:00:00 2001
From: Gabe Lyons
Date: Tue, 16 Jul 2024 08:18:37 -0700
Subject: [PATCH 02/23] fix(structured properties): allow application of
structured properties without schema file (#10918)
---
.../datahub/api/entities/dataset/dataset.py | 98 +++++++++----------
1 file changed, 49 insertions(+), 49 deletions(-)
diff --git a/metadata-ingestion/src/datahub/api/entities/dataset/dataset.py b/metadata-ingestion/src/datahub/api/entities/dataset/dataset.py
index afeedb83f7998..f9a188c65feef 100644
--- a/metadata-ingestion/src/datahub/api/entities/dataset/dataset.py
+++ b/metadata-ingestion/src/datahub/api/entities/dataset/dataset.py
@@ -259,56 +259,56 @@ def generate_mcp(
)
yield mcp
- if self.schema_metadata.fields:
- for field in self.schema_metadata.fields:
- field_urn = field.urn or make_schema_field_urn(
- self.urn, field.id # type: ignore[arg-type]
+ if self.schema_metadata.fields:
+ for field in self.schema_metadata.fields:
+ field_urn = field.urn or make_schema_field_urn(
+ self.urn, field.id # type: ignore[arg-type]
+ )
+ assert field_urn.startswith("urn:li:schemaField:")
+
+ if field.globalTags:
+ mcp = MetadataChangeProposalWrapper(
+ entityUrn=field_urn,
+ aspect=GlobalTagsClass(
+ tags=[
+ TagAssociationClass(tag=make_tag_urn(tag))
+ for tag in field.globalTags
+ ]
+ ),
)
- assert field_urn.startswith("urn:li:schemaField:")
-
- if field.globalTags:
- mcp = MetadataChangeProposalWrapper(
- entityUrn=field_urn,
- aspect=GlobalTagsClass(
- tags=[
- TagAssociationClass(tag=make_tag_urn(tag))
- for tag in field.globalTags
- ]
- ),
- )
- yield mcp
-
- if field.glossaryTerms:
- mcp = MetadataChangeProposalWrapper(
- entityUrn=field_urn,
- aspect=GlossaryTermsClass(
- terms=[
- GlossaryTermAssociationClass(
- urn=make_term_urn(term)
- )
- for term in field.glossaryTerms
- ],
- auditStamp=self._mint_auditstamp("yaml"),
- ),
- )
- yield mcp
-
- if field.structured_properties:
- mcp = MetadataChangeProposalWrapper(
- entityUrn=field_urn,
- aspect=StructuredPropertiesClass(
- properties=[
- StructuredPropertyValueAssignmentClass(
- propertyUrn=f"urn:li:structuredProperty:{prop_key}",
- values=prop_value
- if isinstance(prop_value, list)
- else [prop_value],
- )
- for prop_key, prop_value in field.structured_properties.items()
- ]
- ),
- )
- yield mcp
+ yield mcp
+
+ if field.glossaryTerms:
+ mcp = MetadataChangeProposalWrapper(
+ entityUrn=field_urn,
+ aspect=GlossaryTermsClass(
+ terms=[
+ GlossaryTermAssociationClass(
+ urn=make_term_urn(term)
+ )
+ for term in field.glossaryTerms
+ ],
+ auditStamp=self._mint_auditstamp("yaml"),
+ ),
+ )
+ yield mcp
+
+ if field.structured_properties:
+ mcp = MetadataChangeProposalWrapper(
+ entityUrn=field_urn,
+ aspect=StructuredPropertiesClass(
+ properties=[
+ StructuredPropertyValueAssignmentClass(
+ propertyUrn=f"urn:li:structuredProperty:{prop_key}",
+ values=prop_value
+ if isinstance(prop_value, list)
+ else [prop_value],
+ )
+ for prop_key, prop_value in field.structured_properties.items()
+ ]
+ ),
+ )
+ yield mcp
if self.subtype or self.subtypes:
mcp = MetadataChangeProposalWrapper(
From ee18a174d1a373f692006920077d5b6e11741059 Mon Sep 17 00:00:00 2001
From: Jay <159848059+jayacryl@users.noreply.github.com>
Date: Tue, 16 Jul 2024 12:56:56 -0400
Subject: [PATCH 03/23] fix(data-contracts-web) handle other schedule types
(#10919)
---
.../contract/FreshnessScheduleSummary.tsx | 33 +++++++++++++------
1 file changed, 23 insertions(+), 10 deletions(-)
diff --git a/datahub-web-react/src/app/entity/shared/tabs/Dataset/Validations/contract/FreshnessScheduleSummary.tsx b/datahub-web-react/src/app/entity/shared/tabs/Dataset/Validations/contract/FreshnessScheduleSummary.tsx
index 434ccb985574f..5009587c0d277 100644
--- a/datahub-web-react/src/app/entity/shared/tabs/Dataset/Validations/contract/FreshnessScheduleSummary.tsx
+++ b/datahub-web-react/src/app/entity/shared/tabs/Dataset/Validations/contract/FreshnessScheduleSummary.tsx
@@ -13,16 +13,29 @@ type Props = {
};
export const FreshnessScheduleSummary = ({ definition, evaluationSchedule }: Props) => {
- const scheduleText =
- definition.type === FreshnessAssertionScheduleType.Cron
- ? `${capitalizeFirstLetter(cronstrue.toString(definition.cron?.cron as string))}.`
- : `In the past ${
- definition.fixedInterval?.multiple
- } ${definition.fixedInterval?.unit.toLocaleLowerCase()}s${
- (evaluationSchedule &&
- `, as of ${cronstrue.toString(evaluationSchedule.cron as string).toLowerCase()}`) ||
- ''
- }`;
+ let scheduleText = '';
+ const cronStr = definition.cron?.cron ?? evaluationSchedule?.cron;
+ switch (definition.type) {
+ case FreshnessAssertionScheduleType.Cron:
+ scheduleText = cronStr
+ ? `${capitalizeFirstLetter(cronstrue.toString(cronStr))}.`
+ : `Unknown freshness schedule.`;
+ break;
+ case FreshnessAssertionScheduleType.SinceTheLastCheck:
+ scheduleText = cronStr
+ ? `Since the previous check, as of ${cronstrue.toString(cronStr).toLowerCase()}`
+ : 'Since the previous check';
+ break;
+ case FreshnessAssertionScheduleType.FixedInterval:
+ scheduleText = `In the past ${
+ definition.fixedInterval?.multiple
+ } ${definition.fixedInterval?.unit.toLocaleLowerCase()}s${
+ cronStr ? `, as of ${cronstrue.toString(cronStr).toLowerCase()}` : ''
+ }`;
+ break;
+ default:
+ break;
+ }
return <>{scheduleText}>;
};
From bb1ba091cddda253226aa89ba219f663a2e9f7bc Mon Sep 17 00:00:00 2001
From: sid-acryl <155424659+sid-acryl@users.noreply.github.com>
Date: Tue, 16 Jul 2024 23:06:51 +0530
Subject: [PATCH 04/23] fix(ingestion/tableau): human-readable message for
PERMISSIONS_MODE_SWITCHED error (#10866)
Co-authored-by: Harshal Sheth
---
.../src/datahub/ingestion/source/tableau.py | 32 ++++-
.../setup/permission_mode_switched_error.json | 16 +++
.../tableau/test_tableau_ingest.py | 112 ++++++++++++++----
3 files changed, 132 insertions(+), 28 deletions(-)
create mode 100644 metadata-ingestion/tests/integration/tableau/setup/permission_mode_switched_error.json
diff --git a/metadata-ingestion/src/datahub/ingestion/source/tableau.py b/metadata-ingestion/src/datahub/ingestion/source/tableau.py
index b14a4a8586c7d..50fd8ed3dff59 100644
--- a/metadata-ingestion/src/datahub/ingestion/source/tableau.py
+++ b/metadata-ingestion/src/datahub/ingestion/source/tableau.py
@@ -1009,10 +1009,34 @@ def get_connection_object_page(
error and (error.get(c.EXTENSIONS) or {}).get(c.SEVERITY) == c.WARNING
for error in errors
):
- self.report.warning(
- message=f"Received error fetching Query Connection {connection_type}",
- context=f"Errors: {errors}",
- )
+ # filter out PERMISSIONS_MODE_SWITCHED to report error in human-readable format
+ other_errors = []
+ permission_mode_errors = []
+ for error in errors:
+ if (
+ error.get("extensions")
+ and error["extensions"].get("code")
+ == "PERMISSIONS_MODE_SWITCHED"
+ ):
+ permission_mode_errors.append(error)
+ else:
+ other_errors.append(error)
+
+ if other_errors:
+ self.report.warning(
+ message=f"Received error fetching Query Connection {connection_type}",
+ context=f"Errors: {other_errors}",
+ )
+
+ if permission_mode_errors:
+ self.report.warning(
+ title="Derived Permission Error",
+ message="Turn on your derived permissions. See for details "
+ "https://community.tableau.com/s/question/0D54T00000QnjHbSAJ/how-to-fix-the"
+ "-permissionsmodeswitched-error",
+ context=f"{permission_mode_errors}",
+ )
+
else:
raise RuntimeError(f"Query {connection_type} error: {errors}")
diff --git a/metadata-ingestion/tests/integration/tableau/setup/permission_mode_switched_error.json b/metadata-ingestion/tests/integration/tableau/setup/permission_mode_switched_error.json
new file mode 100644
index 0000000000000..a8593493a5ec7
--- /dev/null
+++ b/metadata-ingestion/tests/integration/tableau/setup/permission_mode_switched_error.json
@@ -0,0 +1,16 @@
+{
+ "errors":[
+ {
+ "message": "One or more of the attributes used in your filter contain sensitive data so your results have been automatically filtered to contain only the results you have permissions to see",
+ "extensions": {
+ "severity": "WARNING",
+ "code": "PERMISSIONS_MODE_SWITCHED",
+ "properties": {
+ "workbooksConnection": [
+ "projectNameWithin"
+ ]
+ }
+ }
+ }
+ ]
+}
\ No newline at end of file
diff --git a/metadata-ingestion/tests/integration/tableau/test_tableau_ingest.py b/metadata-ingestion/tests/integration/tableau/test_tableau_ingest.py
index b64609b6ea605..0891a1e0cd593 100644
--- a/metadata-ingestion/tests/integration/tableau/test_tableau_ingest.py
+++ b/metadata-ingestion/tests/integration/tableau/test_tableau_ingest.py
@@ -2,7 +2,7 @@
import logging
import pathlib
import sys
-from typing import Any, Dict, cast
+from typing import Any, Dict, List, cast
from unittest import mock
import pytest
@@ -232,6 +232,41 @@ def side_effect_site_get_by_id(id, *arg, **kwargs):
return site
+def mock_sdk_client(
+ side_effect_query_metadata_response: List[dict],
+ datasources_side_effect: List[dict],
+ sign_out_side_effect: List[dict],
+) -> mock.MagicMock:
+
+ mock_client = mock.Mock()
+ mocked_metadata = mock.Mock()
+ mocked_metadata.query.side_effect = side_effect_query_metadata_response
+ mock_client.metadata = mocked_metadata
+
+ mock_client.auth = mock.Mock()
+ mock_client.site_id = "190a6a5c-63ed-4de1-8045-site1"
+ mock_client.views = mock.Mock()
+ mock_client.projects = mock.Mock()
+ mock_client.sites = mock.Mock()
+
+ mock_client.projects.get.side_effect = side_effect_project_data
+ mock_client.sites.get.side_effect = side_effect_site_data
+ mock_client.sites.get_by_id.side_effect = side_effect_site_get_by_id
+
+ mock_client.datasources = mock.Mock()
+ mock_client.datasources.get.side_effect = datasources_side_effect
+ mock_client.datasources.get_by_id.side_effect = side_effect_datasource_get_by_id
+
+ mock_client.workbooks = mock.Mock()
+ mock_client.workbooks.get.side_effect = side_effect_workbook_data
+
+ mock_client.views.get.side_effect = side_effect_usage_stat
+ mock_client.auth.sign_in.return_value = None
+ mock_client.auth.sign_out.side_effect = sign_out_side_effect
+
+ return mock_client
+
+
def tableau_ingest_common(
pytestconfig,
tmp_path,
@@ -251,30 +286,11 @@ def tableau_ingest_common(
mock_checkpoint.return_value = mock_datahub_graph
with mock.patch("datahub.ingestion.source.tableau.Server") as mock_sdk:
- mock_client = mock.Mock()
- mocked_metadata = mock.Mock()
- mocked_metadata.query.side_effect = side_effect_query_metadata_response
- mock_client.metadata = mocked_metadata
- mock_client.auth = mock.Mock()
- mock_client.site_id = "190a6a5c-63ed-4de1-8045-site1"
- mock_client.views = mock.Mock()
- mock_client.projects = mock.Mock()
- mock_client.sites = mock.Mock()
-
- mock_client.projects.get.side_effect = side_effect_project_data
- mock_client.sites.get.side_effect = side_effect_site_data
- mock_client.sites.get_by_id.side_effect = side_effect_site_get_by_id
- mock_client.datasources = mock.Mock()
- mock_client.datasources.get.side_effect = datasources_side_effect
- mock_client.datasources.get_by_id.side_effect = (
- side_effect_datasource_get_by_id
+ mock_sdk.return_value = mock_sdk_client(
+ side_effect_query_metadata_response=side_effect_query_metadata_response,
+ datasources_side_effect=datasources_side_effect,
+ sign_out_side_effect=sign_out_side_effect,
)
- mock_client.workbooks = mock.Mock()
- mock_client.workbooks.get.side_effect = side_effect_workbook_data
- mock_client.views.get.side_effect = side_effect_usage_stat
- mock_client.auth.sign_in.return_value = None
- mock_client.auth.sign_out.side_effect = sign_out_side_effect
- mock_sdk.return_value = mock_client
mock_sdk._auth_token = "ABC"
pipeline = Pipeline.create(
@@ -1106,3 +1122,51 @@ def test_site_name_pattern(pytestconfig, tmp_path, mock_datahub_graph):
pipeline_config=new_config,
pipeline_name="test_tableau_site_name_pattern_ingest",
)
+
+
+@freeze_time(FROZEN_TIME)
+@pytest.mark.integration
+def test_permission_mode_switched_error(pytestconfig, tmp_path, mock_datahub_graph):
+
+ with mock.patch(
+ "datahub.ingestion.source.state_provider.datahub_ingestion_checkpointing_provider.DataHubGraph",
+ mock_datahub_graph,
+ ) as mock_checkpoint:
+ mock_checkpoint.return_value = mock_datahub_graph
+
+ with mock.patch("datahub.ingestion.source.tableau.Server") as mock_sdk:
+ mock_sdk.return_value = mock_sdk_client(
+ side_effect_query_metadata_response=[
+ read_response(pytestconfig, "permission_mode_switched_error.json")
+ ],
+ sign_out_side_effect=[{}],
+ datasources_side_effect=[{}],
+ )
+
+ reporter = TableauSourceReport()
+ tableau_source = TableauSiteSource(
+ platform="tableau",
+ config=mock.MagicMock(),
+ ctx=mock.MagicMock(),
+ site=mock.MagicMock(),
+ server=mock_sdk.return_value,
+ report=reporter,
+ )
+
+ tableau_source.get_connection_object_page(
+ query=mock.MagicMock(),
+ connection_type=mock.MagicMock(),
+ query_filter=mock.MagicMock(),
+ retries_remaining=1,
+ )
+
+ warnings = list(reporter.warnings)
+
+ assert len(warnings) == 1
+
+ assert warnings[0].title == "Derived Permission Error"
+
+ assert warnings[0].message == (
+ "Turn on your derived permissions. See for details "
+ "https://community.tableau.com/s/question/0D54T00000QnjHbSAJ/how-to-fix-the-permissionsmodeswitched-error"
+ )
From 12ee4853022fc29ec2f303e994529a8bfb8291b8 Mon Sep 17 00:00:00 2001
From: ethan-cartwright
Date: Tue, 16 Jul 2024 13:54:43 -0400
Subject: [PATCH 05/23] Add feature flag for view defintions (#10914)
Co-authored-by: Ethan Cartwright
---
.../datahub/ingestion/source/snowflake/snowflake_config.py | 5 +++++
.../ingestion/source/snowflake/snowflake_schema_gen.py | 6 +++++-
2 files changed, 10 insertions(+), 1 deletion(-)
diff --git a/metadata-ingestion/src/datahub/ingestion/source/snowflake/snowflake_config.py b/metadata-ingestion/src/datahub/ingestion/source/snowflake/snowflake_config.py
index f6247eb949417..365e32dac3e69 100644
--- a/metadata-ingestion/src/datahub/ingestion/source/snowflake/snowflake_config.py
+++ b/metadata-ingestion/src/datahub/ingestion/source/snowflake/snowflake_config.py
@@ -181,6 +181,11 @@ class SnowflakeV2Config(
description="If enabled, populates the snowflake usage statistics. Requires appropriate grants given to the role.",
)
+ include_view_definitions: bool = Field(
+ default=True,
+ description="If enabled, populates the ingested views' definitions.",
+ )
+
include_technical_schema: bool = Field(
default=True,
description="If enabled, populates the snowflake technical schema and descriptions.",
diff --git a/metadata-ingestion/src/datahub/ingestion/source/snowflake/snowflake_schema_gen.py b/metadata-ingestion/src/datahub/ingestion/source/snowflake/snowflake_schema_gen.py
index e604ed96b8eb6..dcc18635de32c 100644
--- a/metadata-ingestion/src/datahub/ingestion/source/snowflake/snowflake_schema_gen.py
+++ b/metadata-ingestion/src/datahub/ingestion/source/snowflake/snowflake_schema_gen.py
@@ -753,7 +753,11 @@ def gen_dataset_workunits(
view_properties_aspect = ViewProperties(
materialized=table.materialized,
viewLanguage="SQL",
- viewLogic=table.view_definition,
+ viewLogic=(
+ table.view_definition
+ if self.config.include_view_definitions
+ else ""
+ ),
)
yield MetadataChangeProposalWrapper(
From ff1c6b895e2a605263a0a138aeb88aa7703f4d33 Mon Sep 17 00:00:00 2001
From: Mayuri Nehate <33225191+mayurinehate@users.noreply.github.com>
Date: Wed, 17 Jul 2024 00:16:42 +0530
Subject: [PATCH 06/23] feat(ingest/BigQuery): refactor+parallelize dataset
metadata extraction (#10884)
---
.../docs/dev_guides/classification.md | 2 +-
.../datahub/ingestion/glossary/classifier.py | 2 +-
.../ingestion/source/bigquery_v2/bigquery.py | 1248 +----------------
.../bigquery_v2/bigquery_audit_log_api.py | 2 +
.../source/bigquery_v2/bigquery_config.py | 14 +-
.../source/bigquery_v2/bigquery_report.py | 25 +-
.../source/bigquery_v2/bigquery_schema.py | 282 ++--
.../source/bigquery_v2/bigquery_schema_gen.py | 1090 ++++++++++++++
.../bigquery_v2/bigquery_test_connection.py | 178 +++
.../ingestion/source/bigquery_v2/lineage.py | 175 ++-
.../ingestion/source/bigquery_v2/profiler.py | 5 +-
.../ingestion/source/bigquery_v2/usage.py | 60 +-
.../source/snowflake/snowflake_schema_gen.py | 48 +-
.../utilities/threaded_iterator_executor.py | 52 +
.../integration/bigquery_v2/test_bigquery.py | 6 +-
.../tests/unit/test_bigquery_source.py | 30 +-
.../test_threaded_iterator_executor.py | 14 +
17 files changed, 1682 insertions(+), 1551 deletions(-)
create mode 100644 metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery_schema_gen.py
create mode 100644 metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery_test_connection.py
create mode 100644 metadata-ingestion/src/datahub/utilities/threaded_iterator_executor.py
create mode 100644 metadata-ingestion/tests/unit/utilities/test_threaded_iterator_executor.py
diff --git a/metadata-ingestion/docs/dev_guides/classification.md b/metadata-ingestion/docs/dev_guides/classification.md
index f20638a2ab5bd..39eac229a6601 100644
--- a/metadata-ingestion/docs/dev_guides/classification.md
+++ b/metadata-ingestion/docs/dev_guides/classification.md
@@ -10,7 +10,7 @@ Note that a `.` is used to denote nested fields in the YAML recipe.
| ------------------------- | -------- | --------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------- |
| enabled | | boolean | Whether classification should be used to auto-detect glossary terms | False |
| sample_size | | int | Number of sample values used for classification. | 100 |
-| max_workers | | int | Number of worker threads to use for classification. Set to 1 to disable. | Number of cpu cores or 4 |
+| max_workers | | int | Number of worker processes to use for classification. Set to 1 to disable. | Number of cpu cores or 4 |
| info_type_to_term | | Dict[str,string] | Optional mapping to provide glossary term identifier for info type. | By default, info type is used as glossary term identifier. |
| classifiers | | Array of object | Classifiers to use to auto-detect glossary terms. If more than one classifier, infotype predictions from the classifier defined later in sequence take precedance. | [{'type': 'datahub', 'config': None}] |
| table_pattern | | AllowDenyPattern (see below for fields) | Regex patterns to filter tables for classification. This is used in combination with other patterns in parent config. Specify regex to match the entire table name in `database.schema.table` format. e.g. to match all tables starting with customer in Customer database and public schema, use the regex 'Customer.public.customer.*' | {'allow': ['.*'], 'deny': [], 'ignoreCase': True} |
diff --git a/metadata-ingestion/src/datahub/ingestion/glossary/classifier.py b/metadata-ingestion/src/datahub/ingestion/glossary/classifier.py
index 99789a49c0b43..ddcb74e354613 100644
--- a/metadata-ingestion/src/datahub/ingestion/glossary/classifier.py
+++ b/metadata-ingestion/src/datahub/ingestion/glossary/classifier.py
@@ -39,7 +39,7 @@ class ClassificationConfig(ConfigModel):
max_workers: int = Field(
default=(os.cpu_count() or 4),
- description="Number of worker threads to use for classification. Set to 1 to disable.",
+ description="Number of worker processes to use for classification. Set to 1 to disable.",
)
table_pattern: AllowDenyPattern = Field(
diff --git a/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery.py b/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery.py
index 5046f52cdce26..7a96b2f0643ab 100644
--- a/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery.py
+++ b/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery.py
@@ -2,24 +2,9 @@
import functools
import logging
import os
-import re
-import traceback
-from collections import defaultdict
-from datetime import datetime, timedelta
-from typing import Dict, Iterable, List, Optional, Set, Type, Union, cast
+from typing import Iterable, List, Optional
-from google.cloud import bigquery
-from google.cloud.bigquery.table import TableListItem
-
-from datahub.configuration.pattern_utils import is_schema_allowed, is_tag_allowed
-from datahub.emitter.mce_builder import (
- make_data_platform_urn,
- make_dataplatform_instance_urn,
- make_dataset_urn,
- make_tag_urn,
-)
-from datahub.emitter.mcp import MetadataChangeProposalWrapper
-from datahub.emitter.mcp_builder import BigQueryDatasetKey, ContainerKey, ProjectIdKey
+from datahub.emitter.mce_builder import make_dataset_urn
from datahub.ingestion.api.common import PipelineContext
from datahub.ingestion.api.decorators import (
SupportStatus,
@@ -30,54 +15,31 @@
)
from datahub.ingestion.api.incremental_lineage_helper import auto_incremental_lineage
from datahub.ingestion.api.source import (
- CapabilityReport,
MetadataWorkUnitProcessor,
SourceCapability,
TestableSource,
TestConnectionReport,
)
from datahub.ingestion.api.workunit import MetadataWorkUnit
-from datahub.ingestion.glossary.classification_mixin import (
- SAMPLE_SIZE_MULTIPLIER,
- ClassificationHandler,
- classification_workunit_processor,
-)
from datahub.ingestion.source.bigquery_v2.bigquery_audit import (
BigqueryTableIdentifier,
BigQueryTableRef,
)
from datahub.ingestion.source.bigquery_v2.bigquery_config import BigQueryV2Config
-from datahub.ingestion.source.bigquery_v2.bigquery_data_reader import BigQueryDataReader
-from datahub.ingestion.source.bigquery_v2.bigquery_helper import (
- unquote_and_decode_unicode_escape_seq,
-)
from datahub.ingestion.source.bigquery_v2.bigquery_report import BigQueryV2Report
from datahub.ingestion.source.bigquery_v2.bigquery_schema import (
- BigqueryColumn,
- BigqueryDataset,
BigqueryProject,
BigQuerySchemaApi,
- BigqueryTable,
- BigqueryTableSnapshot,
- BigqueryView,
)
-from datahub.ingestion.source.bigquery_v2.common import (
- BQ_EXTERNAL_DATASET_URL_TEMPLATE,
- BQ_EXTERNAL_TABLE_URL_TEMPLATE,
+from datahub.ingestion.source.bigquery_v2.bigquery_schema_gen import (
+ BigQuerySchemaGenerator,
+)
+from datahub.ingestion.source.bigquery_v2.bigquery_test_connection import (
+ BigQueryTestConnection,
)
from datahub.ingestion.source.bigquery_v2.lineage import BigqueryLineageExtractor
from datahub.ingestion.source.bigquery_v2.profiler import BigqueryProfiler
from datahub.ingestion.source.bigquery_v2.usage import BigQueryUsageExtractor
-from datahub.ingestion.source.common.subtypes import (
- DatasetContainerSubTypes,
- DatasetSubTypes,
-)
-from datahub.ingestion.source.sql.sql_utils import (
- add_table_to_schema_container,
- gen_database_container,
- gen_schema_container,
- get_domain_wu,
-)
from datahub.ingestion.source.state.profiling_state_handler import ProfilingHandler
from datahub.ingestion.source.state.redundant_run_skip_handler import (
RedundantLineageRunSkipHandler,
@@ -89,57 +51,11 @@
from datahub.ingestion.source.state.stateful_ingestion_base import (
StatefulIngestionSourceBase,
)
-from datahub.ingestion.source_report.ingestion_stage import (
- METADATA_EXTRACTION,
- PROFILING,
-)
-from datahub.metadata.com.linkedin.pegasus2avro.common import (
- Status,
- SubTypes,
- TimeStamp,
-)
-from datahub.metadata.com.linkedin.pegasus2avro.dataset import (
- DatasetProperties,
- ViewProperties,
-)
-from datahub.metadata.com.linkedin.pegasus2avro.schema import (
- ArrayType,
- BooleanType,
- BytesType,
- DateType,
- MySqlDDL,
- NullType,
- NumberType,
- RecordType,
- SchemaField,
- SchemaFieldDataType,
- SchemaMetadata,
- StringType,
- TimeType,
-)
-from datahub.metadata.schema_classes import (
- DataPlatformInstanceClass,
- GlobalTagsClass,
- TagAssociationClass,
-)
from datahub.sql_parsing.schema_resolver import SchemaResolver
-from datahub.utilities.file_backed_collections import FileBackedDict
-from datahub.utilities.hive_schema_to_avro import (
- HiveColumnToAvroConverter,
- get_schema_fields_for_hive_column,
-)
-from datahub.utilities.mapping import Constants
-from datahub.utilities.perf_timer import PerfTimer
-from datahub.utilities.ratelimiter import RateLimiter
from datahub.utilities.registries.domain_registry import DomainRegistry
logger: logging.Logger = logging.getLogger(__name__)
-# Handle table snapshots
-# See https://cloud.google.com/bigquery/docs/table-snapshots-intro.
-SNAPSHOT_TABLE_REGEX = re.compile(r"^(.+)@(\d{13})$")
-CLUSTERING_COLUMN_TAG = "CLUSTERING_COLUMN"
-
# We can't use close as it is not called if the ingestion is not successful
def cleanup(config: BigQueryV2Config) -> None:
@@ -178,58 +94,18 @@ def cleanup(config: BigQueryV2Config) -> None:
supported=True,
)
class BigqueryV2Source(StatefulIngestionSourceBase, TestableSource):
- # https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types
- # Note: We use the hive schema parser to parse nested BigQuery types. We also have
- # some extra type mappings in that file.
- BIGQUERY_FIELD_TYPE_MAPPINGS: Dict[
- str,
- Type[
- Union[
- ArrayType,
- BytesType,
- BooleanType,
- NumberType,
- RecordType,
- StringType,
- TimeType,
- DateType,
- NullType,
- ]
- ],
- ] = {
- "BYTES": BytesType,
- "BOOL": BooleanType,
- "DECIMAL": NumberType,
- "NUMERIC": NumberType,
- "BIGNUMERIC": NumberType,
- "BIGDECIMAL": NumberType,
- "FLOAT64": NumberType,
- "INT": NumberType,
- "INT64": NumberType,
- "SMALLINT": NumberType,
- "INTEGER": NumberType,
- "BIGINT": NumberType,
- "TINYINT": NumberType,
- "BYTEINT": NumberType,
- "STRING": StringType,
- "TIME": TimeType,
- "TIMESTAMP": TimeType,
- "DATE": DateType,
- "DATETIME": TimeType,
- "GEOGRAPHY": NullType,
- "JSON": RecordType,
- "INTERVAL": NullType,
- "ARRAY": ArrayType,
- "STRUCT": RecordType,
- }
-
def __init__(self, ctx: PipelineContext, config: BigQueryV2Config):
super().__init__(config, ctx)
self.config: BigQueryV2Config = config
self.report: BigQueryV2Report = BigQueryV2Report()
- self.classification_handler = ClassificationHandler(self.config, self.report)
self.platform: str = "bigquery"
+ self.domain_registry: Optional[DomainRegistry] = None
+ if self.config.domain:
+ self.domain_registry = DomainRegistry(
+ cached_domains=[k for k in self.config.domain], graph=self.ctx.graph
+ )
+
BigqueryTableIdentifier._BIGQUERY_DEFAULT_SHARDED_TABLE_REGEX = (
self.config.sharded_table_pattern
)
@@ -247,12 +123,6 @@ def __init__(self, ctx: PipelineContext, config: BigQueryV2Config):
self.sql_parser_schema_resolver = self._init_schema_resolver()
- self.data_reader: Optional[BigQueryDataReader] = None
- if self.classification_handler.is_classification_enabled():
- self.data_reader = BigQueryDataReader.create(
- self.config.get_bigquery_client()
- )
-
redundant_lineage_run_skip_handler: Optional[
RedundantLineageRunSkipHandler
] = None
@@ -289,12 +159,6 @@ def __init__(self, ctx: PipelineContext, config: BigQueryV2Config):
redundant_run_skip_handler=redundant_usage_run_skip_handler,
)
- self.domain_registry: Optional[DomainRegistry] = None
- if self.config.domain:
- self.domain_registry = DomainRegistry(
- cached_domains=[k for k in self.config.domain], graph=self.ctx.graph
- )
-
self.profiling_state_handler: Optional[ProfilingHandler] = None
if self.config.enable_stateful_profiling:
self.profiling_state_handler = ProfilingHandler(
@@ -307,17 +171,15 @@ def __init__(self, ctx: PipelineContext, config: BigQueryV2Config):
config, self.report, self.profiling_state_handler
)
- # Global store of table identifiers for lineage filtering
- self.table_refs: Set[str] = set()
-
- # Maps project -> view_ref, so we can find all views in a project
- self.view_refs_by_project: Dict[str, Set[str]] = defaultdict(set)
- # Maps project -> snapshot_ref, so we can find all snapshots in a project
- self.snapshot_refs_by_project: Dict[str, Set[str]] = defaultdict(set)
- # Maps view ref -> actual sql
- self.view_definitions: FileBackedDict[str] = FileBackedDict()
- # Maps snapshot ref -> Snapshot
- self.snapshots_by_ref: FileBackedDict[BigqueryTableSnapshot] = FileBackedDict()
+ self.bq_schema_extractor = BigQuerySchemaGenerator(
+ self.config,
+ self.report,
+ self.bigquery_data_dictionary,
+ self.domain_registry,
+ self.sql_parser_schema_resolver,
+ self.profiler,
+ self.gen_dataset_urn,
+ )
self.add_config_to_report()
atexit.register(cleanup, config)
@@ -327,161 +189,9 @@ def create(cls, config_dict: dict, ctx: PipelineContext) -> "BigqueryV2Source":
config = BigQueryV2Config.parse_obj(config_dict)
return cls(ctx, config)
- @staticmethod
- def connectivity_test(client: bigquery.Client) -> CapabilityReport:
- ret = client.query("select 1")
- if ret.error_result:
- return CapabilityReport(
- capable=False, failure_reason=f"{ret.error_result['message']}"
- )
- else:
- return CapabilityReport(capable=True)
-
- @property
- def store_table_refs(self):
- return self.config.include_table_lineage or self.config.include_usage_statistics
-
- @staticmethod
- def metadata_read_capability_test(
- project_ids: List[str], config: BigQueryV2Config
- ) -> CapabilityReport:
- for project_id in project_ids:
- try:
- logger.info(f"Metadata read capability test for project {project_id}")
- client: bigquery.Client = config.get_bigquery_client()
- assert client
- bigquery_data_dictionary = BigQuerySchemaApi(
- BigQueryV2Report().schema_api_perf, client
- )
- result = bigquery_data_dictionary.get_datasets_for_project_id(
- project_id, 10
- )
- if len(result) == 0:
- return CapabilityReport(
- capable=False,
- failure_reason=f"Dataset query returned empty dataset. It is either empty or no dataset in project {project_id}",
- )
- tables = bigquery_data_dictionary.get_tables_for_dataset(
- project_id=project_id,
- dataset_name=result[0].name,
- tables={},
- with_data_read_permission=config.have_table_data_read_permission,
- )
- if len(list(tables)) == 0:
- return CapabilityReport(
- capable=False,
- failure_reason=f"Tables query did not return any table. It is either empty or no tables in project {project_id}.{result[0].name}",
- )
-
- except Exception as e:
- return CapabilityReport(
- capable=False,
- failure_reason=f"Dataset query failed with error: {e}",
- )
-
- return CapabilityReport(capable=True)
-
- @staticmethod
- def lineage_capability_test(
- connection_conf: BigQueryV2Config,
- project_ids: List[str],
- report: BigQueryV2Report,
- ) -> CapabilityReport:
- lineage_extractor = BigqueryLineageExtractor(
- connection_conf, report, lambda ref: ""
- )
- for project_id in project_ids:
- try:
- logger.info(f"Lineage capability test for project {project_id}")
- lineage_extractor.test_capability(project_id)
- except Exception as e:
- return CapabilityReport(
- capable=False,
- failure_reason=f"Lineage capability test failed with: {e}",
- )
-
- return CapabilityReport(capable=True)
-
- @staticmethod
- def usage_capability_test(
- connection_conf: BigQueryV2Config,
- project_ids: List[str],
- report: BigQueryV2Report,
- ) -> CapabilityReport:
- usage_extractor = BigQueryUsageExtractor(
- connection_conf,
- report,
- schema_resolver=SchemaResolver(platform="bigquery"),
- dataset_urn_builder=lambda ref: "",
- )
- for project_id in project_ids:
- try:
- logger.info(f"Usage capability test for project {project_id}")
- failures_before_test = len(report.failures)
- usage_extractor.test_capability(project_id)
- if failures_before_test != len(report.failures):
- return CapabilityReport(
- capable=False,
- failure_reason="Usage capability test failed. Check the logs for further info",
- )
- except Exception as e:
- return CapabilityReport(
- capable=False,
- failure_reason=f"Usage capability test failed with: {e} for project {project_id}",
- )
- return CapabilityReport(capable=True)
-
@staticmethod
def test_connection(config_dict: dict) -> TestConnectionReport:
- test_report = TestConnectionReport()
- _report: Dict[Union[SourceCapability, str], CapabilityReport] = dict()
-
- try:
- connection_conf = BigQueryV2Config.parse_obj_allow_extras(config_dict)
- client: bigquery.Client = connection_conf.get_bigquery_client()
- assert client
-
- test_report.basic_connectivity = BigqueryV2Source.connectivity_test(client)
-
- connection_conf.start_time = datetime.now()
- connection_conf.end_time = datetime.now() + timedelta(minutes=1)
-
- report: BigQueryV2Report = BigQueryV2Report()
- project_ids: List[str] = []
- projects = client.list_projects()
-
- for project in projects:
- if connection_conf.project_id_pattern.allowed(project.project_id):
- project_ids.append(project.project_id)
-
- metadata_read_capability = BigqueryV2Source.metadata_read_capability_test(
- project_ids, connection_conf
- )
- if SourceCapability.SCHEMA_METADATA not in _report:
- _report[SourceCapability.SCHEMA_METADATA] = metadata_read_capability
-
- if connection_conf.include_table_lineage:
- lineage_capability = BigqueryV2Source.lineage_capability_test(
- connection_conf, project_ids, report
- )
- if SourceCapability.LINEAGE_COARSE not in _report:
- _report[SourceCapability.LINEAGE_COARSE] = lineage_capability
-
- if connection_conf.include_usage_statistics:
- usage_capability = BigqueryV2Source.usage_capability_test(
- connection_conf, project_ids, report
- )
- if SourceCapability.USAGE_STATS not in _report:
- _report[SourceCapability.USAGE_STATS] = usage_capability
-
- test_report.capability_report = _report
- return test_report
-
- except Exception as e:
- test_report.basic_connectivity = CapabilityReport(
- capable=False, failure_reason=f"{e}"
- )
- return test_report
+ return BigQueryTestConnection.test_connection(config_dict)
def _init_schema_resolver(self) -> SchemaResolver:
schema_resolution_required = (
@@ -509,83 +219,6 @@ def _init_schema_resolver(self) -> SchemaResolver:
)
return SchemaResolver(platform=self.platform, env=self.config.env)
- def get_dataplatform_instance_aspect(
- self, dataset_urn: str, project_id: str
- ) -> MetadataWorkUnit:
- aspect = DataPlatformInstanceClass(
- platform=make_data_platform_urn(self.platform),
- instance=(
- make_dataplatform_instance_urn(self.platform, project_id)
- if self.config.include_data_platform_instance
- else None
- ),
- )
- return MetadataChangeProposalWrapper(
- entityUrn=dataset_urn, aspect=aspect
- ).as_workunit()
-
- def gen_dataset_key(self, db_name: str, schema: str) -> ContainerKey:
- return BigQueryDatasetKey(
- project_id=db_name,
- dataset_id=schema,
- platform=self.platform,
- env=self.config.env,
- backcompat_env_as_instance=True,
- )
-
- def gen_project_id_key(self, database: str) -> ContainerKey:
- return ProjectIdKey(
- project_id=database,
- platform=self.platform,
- env=self.config.env,
- backcompat_env_as_instance=True,
- )
-
- def gen_project_id_containers(self, database: str) -> Iterable[MetadataWorkUnit]:
- database_container_key = self.gen_project_id_key(database)
-
- yield from gen_database_container(
- database=database,
- name=database,
- sub_types=[DatasetContainerSubTypes.BIGQUERY_PROJECT],
- domain_registry=self.domain_registry,
- domain_config=self.config.domain,
- database_container_key=database_container_key,
- )
-
- def gen_dataset_containers(
- self, dataset: str, project_id: str, tags: Optional[Dict[str, str]] = None
- ) -> Iterable[MetadataWorkUnit]:
- schema_container_key = self.gen_dataset_key(project_id, dataset)
-
- tags_joined: Optional[List[str]] = None
- if tags and self.config.capture_dataset_label_as_tag:
- tags_joined = [
- f"{k}:{v}"
- for k, v in tags.items()
- if is_tag_allowed(self.config.capture_dataset_label_as_tag, k)
- ]
-
- database_container_key = self.gen_project_id_key(database=project_id)
-
- yield from gen_schema_container(
- database=project_id,
- schema=dataset,
- sub_types=[DatasetContainerSubTypes.BIGQUERY_DATASET],
- domain_registry=self.domain_registry,
- domain_config=self.config.domain,
- schema_container_key=schema_container_key,
- database_container_key=database_container_key,
- external_url=(
- BQ_EXTERNAL_DATASET_URL_TEMPLATE.format(
- project=project_id, dataset=dataset
- )
- if self.config.include_external_url
- else None
- ),
- tags=tags_joined,
- )
-
def get_workunit_processors(self) -> List[Optional[MetadataWorkUnitProcessor]]:
return [
*super().get_workunit_processors(),
@@ -603,25 +236,23 @@ def get_workunits_internal(self) -> Iterable[MetadataWorkUnit]:
return
if self.config.include_schema_metadata:
- for project_id in projects:
- self.report.set_ingestion_stage(project_id.id, METADATA_EXTRACTION)
- logger.info(f"Processing project: {project_id.id}")
- yield from self._process_project(project_id)
+ for project in projects:
+ yield from self.bq_schema_extractor.get_project_workunits(project)
if self.config.include_usage_statistics:
yield from self.usage_extractor.get_usage_workunits(
- [p.id for p in projects], self.table_refs
+ [p.id for p in projects], self.bq_schema_extractor.table_refs
)
if self.config.include_table_lineage:
yield from self.lineage_extractor.get_lineage_workunits(
[p.id for p in projects],
self.sql_parser_schema_resolver,
- self.view_refs_by_project,
- self.view_definitions,
- self.snapshot_refs_by_project,
- self.snapshots_by_ref,
- self.table_refs,
+ self.bq_schema_extractor.view_refs_by_project,
+ self.bq_schema_extractor.view_definitions,
+ self.bq_schema_extractor.snapshot_refs_by_project,
+ self.bq_schema_extractor.snapshots_by_ref,
+ self.bq_schema_extractor.table_refs,
)
def _get_projects(self) -> List[BigqueryProject]:
@@ -636,15 +267,25 @@ def _get_projects(self) -> List[BigqueryProject]:
return list(self._query_project_list())
def _query_project_list(self) -> Iterable[BigqueryProject]:
- projects = self.bigquery_data_dictionary.get_projects()
- if not projects: # Report failure on exception and if empty list is returned
- self.report.report_failure(
- "metadata-extraction",
- "Get projects didn't return any project. "
- "Maybe resourcemanager.projects.get permission is missing for the service account. "
+ try:
+ projects = self.bigquery_data_dictionary.get_projects()
+
+ if (
+ not projects
+ ): # Report failure on exception and if empty list is returned
+ self.report.failure(
+ title="Get projects didn't return any project. ",
+ message="Maybe resourcemanager.projects.get permission is missing for the service account. "
+ "You can assign predefined roles/bigquery.metadataViewer role to your service account.",
+ )
+ except Exception as e:
+ self.report.failure(
+ title="Failed to get BigQuery Projects",
+ message="Maybe resourcemanager.projects.get permission is missing for the service account. "
"You can assign predefined roles/bigquery.metadataViewer role to your service account.",
+ exc=e,
)
- return
+ projects = []
for project in projects:
if self.config.project_id_pattern.allowed(project.id):
@@ -652,567 +293,6 @@ def _query_project_list(self) -> Iterable[BigqueryProject]:
else:
self.report.report_dropped(project.id)
- def _process_project(
- self, bigquery_project: BigqueryProject
- ) -> Iterable[MetadataWorkUnit]:
- db_tables: Dict[str, List[BigqueryTable]] = {}
- db_views: Dict[str, List[BigqueryView]] = {}
- db_snapshots: Dict[str, List[BigqueryTableSnapshot]] = {}
-
- project_id = bigquery_project.id
- try:
- bigquery_project.datasets = (
- self.bigquery_data_dictionary.get_datasets_for_project_id(project_id)
- )
- except Exception as e:
- error_message = f"Unable to get datasets for project {project_id}, skipping. The error was: {e}"
- if self.config.is_profiling_enabled():
- error_message = f"Unable to get datasets for project {project_id}, skipping. Does your service account has bigquery.datasets.get permission? The error was: {e}"
- logger.error(error_message)
- self.report.report_failure(
- "metadata-extraction",
- f"{project_id} - {error_message}",
- )
- return None
-
- if len(bigquery_project.datasets) == 0:
- more_info = (
- "Either there are no datasets in this project or missing bigquery.datasets.get permission. "
- "You can assign predefined roles/bigquery.metadataViewer role to your service account."
- )
- if self.config.exclude_empty_projects:
- self.report.report_dropped(project_id)
- warning_message = f"Excluded project '{project_id}' since no were datasets found. {more_info}"
- else:
- yield from self.gen_project_id_containers(project_id)
- warning_message = (
- f"No datasets found in project '{project_id}'. {more_info}"
- )
- logger.warning(warning_message)
- return
-
- yield from self.gen_project_id_containers(project_id)
-
- self.report.num_project_datasets_to_scan[project_id] = len(
- bigquery_project.datasets
- )
- for bigquery_dataset in bigquery_project.datasets:
- if not is_schema_allowed(
- self.config.dataset_pattern,
- bigquery_dataset.name,
- project_id,
- self.config.match_fully_qualified_names,
- ):
- self.report.report_dropped(f"{bigquery_dataset.name}.*")
- continue
- try:
- # db_tables, db_views, and db_snapshots are populated in the this method
- yield from self._process_schema(
- project_id, bigquery_dataset, db_tables, db_views, db_snapshots
- )
-
- except Exception as e:
- error_message = f"Unable to get tables for dataset {bigquery_dataset.name} in project {project_id}, skipping. Does your service account has bigquery.tables.list, bigquery.routines.get, bigquery.routines.list permission? The error was: {e}"
- if self.config.is_profiling_enabled():
- error_message = f"Unable to get tables for dataset {bigquery_dataset.name} in project {project_id}, skipping. Does your service account has bigquery.tables.list, bigquery.routines.get, bigquery.routines.list permission, bigquery.tables.getData permission? The error was: {e}"
-
- trace = traceback.format_exc()
- logger.error(trace)
- logger.error(error_message)
- self.report.report_failure(
- "metadata-extraction",
- f"{project_id}.{bigquery_dataset.name} - {error_message} - {trace}",
- )
- continue
-
- if self.config.is_profiling_enabled():
- logger.info(f"Starting profiling project {project_id}")
- self.report.set_ingestion_stage(project_id, PROFILING)
- yield from self.profiler.get_workunits(
- project_id=project_id,
- tables=db_tables,
- )
-
- def _process_schema(
- self,
- project_id: str,
- bigquery_dataset: BigqueryDataset,
- db_tables: Dict[str, List[BigqueryTable]],
- db_views: Dict[str, List[BigqueryView]],
- db_snapshots: Dict[str, List[BigqueryTableSnapshot]],
- ) -> Iterable[MetadataWorkUnit]:
- dataset_name = bigquery_dataset.name
-
- yield from self.gen_dataset_containers(
- dataset_name, project_id, bigquery_dataset.labels
- )
-
- columns = None
-
- rate_limiter: Optional[RateLimiter] = None
- if self.config.rate_limit:
- rate_limiter = RateLimiter(
- max_calls=self.config.requests_per_min, period=60
- )
-
- if (
- self.config.include_tables
- or self.config.include_views
- or self.config.include_table_snapshots
- ):
- columns = self.bigquery_data_dictionary.get_columns_for_dataset(
- project_id=project_id,
- dataset_name=dataset_name,
- column_limit=self.config.column_limit,
- run_optimized_column_query=self.config.run_optimized_column_query,
- extract_policy_tags_from_catalog=self.config.extract_policy_tags_from_catalog,
- report=self.report,
- rate_limiter=rate_limiter,
- )
-
- if self.config.include_tables:
- db_tables[dataset_name] = list(
- self.get_tables_for_dataset(project_id, dataset_name)
- )
-
- for table in db_tables[dataset_name]:
- table_columns = columns.get(table.name, []) if columns else []
- table_wu_generator = self._process_table(
- table=table,
- columns=table_columns,
- project_id=project_id,
- dataset_name=dataset_name,
- )
- yield from classification_workunit_processor(
- table_wu_generator,
- self.classification_handler,
- self.data_reader,
- [project_id, dataset_name, table.name],
- data_reader_kwargs=dict(
- sample_size_percent=(
- self.config.classification.sample_size
- * SAMPLE_SIZE_MULTIPLIER
- / table.rows_count
- if table.rows_count
- else None
- )
- ),
- )
- elif self.store_table_refs:
- # Need table_refs to calculate lineage and usage
- for table_item in self.bigquery_data_dictionary.list_tables(
- dataset_name, project_id
- ):
- identifier = BigqueryTableIdentifier(
- project_id=project_id,
- dataset=dataset_name,
- table=table_item.table_id,
- )
- if not self.config.table_pattern.allowed(identifier.raw_table_name()):
- self.report.report_dropped(identifier.raw_table_name())
- continue
- try:
- self.table_refs.add(
- str(BigQueryTableRef(identifier).get_sanitized_table_ref())
- )
- except Exception as e:
- logger.warning(
- f"Could not create table ref for {table_item.path}: {e}"
- )
-
- if self.config.include_views:
- db_views[dataset_name] = list(
- self.bigquery_data_dictionary.get_views_for_dataset(
- project_id,
- dataset_name,
- self.config.is_profiling_enabled(),
- self.report,
- )
- )
-
- for view in db_views[dataset_name]:
- view_columns = columns.get(view.name, []) if columns else []
- yield from self._process_view(
- view=view,
- columns=view_columns,
- project_id=project_id,
- dataset_name=dataset_name,
- )
-
- if self.config.include_table_snapshots:
- db_snapshots[dataset_name] = list(
- self.bigquery_data_dictionary.get_snapshots_for_dataset(
- project_id,
- dataset_name,
- self.config.is_profiling_enabled(),
- self.report,
- )
- )
-
- for snapshot in db_snapshots[dataset_name]:
- snapshot_columns = columns.get(snapshot.name, []) if columns else []
- yield from self._process_snapshot(
- snapshot=snapshot,
- columns=snapshot_columns,
- project_id=project_id,
- dataset_name=dataset_name,
- )
-
- # This method is used to generate the ignore list for datatypes the profiler doesn't support we have to do it here
- # because the profiler doesn't have access to columns
- def generate_profile_ignore_list(self, columns: List[BigqueryColumn]) -> List[str]:
- ignore_list: List[str] = []
- for column in columns:
- if not column.data_type or any(
- word in column.data_type.lower()
- for word in ["array", "struct", "geography", "json"]
- ):
- ignore_list.append(column.field_path)
- return ignore_list
-
- def _process_table(
- self,
- table: BigqueryTable,
- columns: List[BigqueryColumn],
- project_id: str,
- dataset_name: str,
- ) -> Iterable[MetadataWorkUnit]:
- table_identifier = BigqueryTableIdentifier(project_id, dataset_name, table.name)
-
- self.report.report_entity_scanned(table_identifier.raw_table_name())
-
- if not self.config.table_pattern.allowed(table_identifier.raw_table_name()):
- self.report.report_dropped(table_identifier.raw_table_name())
- return
-
- if self.store_table_refs:
- self.table_refs.add(
- str(BigQueryTableRef(table_identifier).get_sanitized_table_ref())
- )
- table.column_count = len(columns)
-
- # We only collect profile ignore list if profiling is enabled and profile_table_level_only is false
- if (
- self.config.is_profiling_enabled()
- and not self.config.profiling.profile_table_level_only
- ):
- table.columns_ignore_from_profiling = self.generate_profile_ignore_list(
- columns
- )
-
- if not table.column_count:
- logger.warning(
- f"Table doesn't have any column or unable to get columns for table: {table_identifier}"
- )
-
- # If table has time partitioning, set the data type of the partitioning field
- if table.partition_info:
- table.partition_info.column = next(
- (
- column
- for column in columns
- if column.name == table.partition_info.field
- ),
- None,
- )
- yield from self.gen_table_dataset_workunits(
- table, columns, project_id, dataset_name
- )
-
- def _process_view(
- self,
- view: BigqueryView,
- columns: List[BigqueryColumn],
- project_id: str,
- dataset_name: str,
- ) -> Iterable[MetadataWorkUnit]:
- table_identifier = BigqueryTableIdentifier(project_id, dataset_name, view.name)
-
- self.report.report_entity_scanned(table_identifier.raw_table_name(), "view")
-
- if not self.config.view_pattern.allowed(table_identifier.raw_table_name()):
- self.report.report_dropped(table_identifier.raw_table_name())
- return
-
- if self.store_table_refs:
- table_ref = str(
- BigQueryTableRef(table_identifier).get_sanitized_table_ref()
- )
- self.table_refs.add(table_ref)
- if self.config.lineage_parse_view_ddl and view.view_definition:
- self.view_refs_by_project[project_id].add(table_ref)
- self.view_definitions[table_ref] = view.view_definition
-
- view.column_count = len(columns)
- if not view.column_count:
- logger.warning(
- f"View doesn't have any column or unable to get columns for table: {table_identifier}"
- )
-
- yield from self.gen_view_dataset_workunits(
- table=view,
- columns=columns,
- project_id=project_id,
- dataset_name=dataset_name,
- )
-
- def _process_snapshot(
- self,
- snapshot: BigqueryTableSnapshot,
- columns: List[BigqueryColumn],
- project_id: str,
- dataset_name: str,
- ) -> Iterable[MetadataWorkUnit]:
- table_identifier = BigqueryTableIdentifier(
- project_id, dataset_name, snapshot.name
- )
-
- self.report.snapshots_scanned += 1
-
- if not self.config.table_snapshot_pattern.allowed(
- table_identifier.raw_table_name()
- ):
- self.report.report_dropped(table_identifier.raw_table_name())
- return
-
- snapshot.columns = columns
- snapshot.column_count = len(columns)
- if not snapshot.column_count:
- logger.warning(
- f"Snapshot doesn't have any column or unable to get columns for table: {table_identifier}"
- )
-
- if self.store_table_refs:
- table_ref = str(
- BigQueryTableRef(table_identifier).get_sanitized_table_ref()
- )
- self.table_refs.add(table_ref)
- if snapshot.base_table_identifier:
- self.snapshot_refs_by_project[project_id].add(table_ref)
- self.snapshots_by_ref[table_ref] = snapshot
-
- yield from self.gen_snapshot_dataset_workunits(
- table=snapshot,
- columns=columns,
- project_id=project_id,
- dataset_name=dataset_name,
- )
-
- def gen_table_dataset_workunits(
- self,
- table: BigqueryTable,
- columns: List[BigqueryColumn],
- project_id: str,
- dataset_name: str,
- ) -> Iterable[MetadataWorkUnit]:
- custom_properties: Dict[str, str] = {}
- if table.expires:
- custom_properties["expiration_date"] = str(table.expires)
-
- if table.partition_info:
- custom_properties["partition_info"] = str(table.partition_info)
-
- if table.size_in_bytes:
- custom_properties["size_in_bytes"] = str(table.size_in_bytes)
-
- if table.active_billable_bytes:
- custom_properties["billable_bytes_active"] = str(
- table.active_billable_bytes
- )
-
- if table.long_term_billable_bytes:
- custom_properties["billable_bytes_long_term"] = str(
- table.long_term_billable_bytes
- )
-
- if table.max_partition_id:
- custom_properties["number_of_partitions"] = str(table.num_partitions)
- custom_properties["max_partition_id"] = str(table.max_partition_id)
- custom_properties["is_partitioned"] = str(True)
-
- sub_types: List[str] = [DatasetSubTypes.TABLE]
- if table.max_shard_id:
- custom_properties["max_shard_id"] = str(table.max_shard_id)
- custom_properties["is_sharded"] = str(True)
- sub_types = ["sharded table"] + sub_types
-
- tags_to_add = None
- if table.labels and self.config.capture_table_label_as_tag:
- tags_to_add = []
- tags_to_add.extend(
- [
- make_tag_urn(f"""{k}:{v}""")
- for k, v in table.labels.items()
- if is_tag_allowed(self.config.capture_table_label_as_tag, k)
- ]
- )
-
- yield from self.gen_dataset_workunits(
- table=table,
- columns=columns,
- project_id=project_id,
- dataset_name=dataset_name,
- sub_types=sub_types,
- tags_to_add=tags_to_add,
- custom_properties=custom_properties,
- )
-
- def gen_view_dataset_workunits(
- self,
- table: BigqueryView,
- columns: List[BigqueryColumn],
- project_id: str,
- dataset_name: str,
- ) -> Iterable[MetadataWorkUnit]:
- tags_to_add = None
- if table.labels and self.config.capture_view_label_as_tag:
- tags_to_add = [
- make_tag_urn(f"{k}:{v}")
- for k, v in table.labels.items()
- if is_tag_allowed(self.config.capture_view_label_as_tag, k)
- ]
- yield from self.gen_dataset_workunits(
- table=table,
- columns=columns,
- project_id=project_id,
- dataset_name=dataset_name,
- tags_to_add=tags_to_add,
- sub_types=[DatasetSubTypes.VIEW],
- )
-
- view = cast(BigqueryView, table)
- view_definition_string = view.view_definition
- view_properties_aspect = ViewProperties(
- materialized=view.materialized,
- viewLanguage="SQL",
- viewLogic=view_definition_string or "",
- )
- yield MetadataChangeProposalWrapper(
- entityUrn=self.gen_dataset_urn(
- project_id=project_id, dataset_name=dataset_name, table=table.name
- ),
- aspect=view_properties_aspect,
- ).as_workunit()
-
- def gen_snapshot_dataset_workunits(
- self,
- table: BigqueryTableSnapshot,
- columns: List[BigqueryColumn],
- project_id: str,
- dataset_name: str,
- ) -> Iterable[MetadataWorkUnit]:
- custom_properties: Dict[str, str] = {}
- if table.ddl:
- custom_properties["snapshot_ddl"] = table.ddl
- if table.snapshot_time:
- custom_properties["snapshot_time"] = str(table.snapshot_time)
- if table.size_in_bytes:
- custom_properties["size_in_bytes"] = str(table.size_in_bytes)
- if table.rows_count:
- custom_properties["rows_count"] = str(table.rows_count)
- yield from self.gen_dataset_workunits(
- table=table,
- columns=columns,
- project_id=project_id,
- dataset_name=dataset_name,
- sub_types=[DatasetSubTypes.BIGQUERY_TABLE_SNAPSHOT],
- custom_properties=custom_properties,
- )
-
- def gen_dataset_workunits(
- self,
- table: Union[BigqueryTable, BigqueryView, BigqueryTableSnapshot],
- columns: List[BigqueryColumn],
- project_id: str,
- dataset_name: str,
- sub_types: List[str],
- tags_to_add: Optional[List[str]] = None,
- custom_properties: Optional[Dict[str, str]] = None,
- ) -> Iterable[MetadataWorkUnit]:
- dataset_urn = self.gen_dataset_urn(
- project_id=project_id, dataset_name=dataset_name, table=table.name
- )
-
- status = Status(removed=False)
- yield MetadataChangeProposalWrapper(
- entityUrn=dataset_urn, aspect=status
- ).as_workunit()
-
- datahub_dataset_name = BigqueryTableIdentifier(
- project_id, dataset_name, table.name
- )
-
- yield self.gen_schema_metadata(
- dataset_urn, table, columns, datahub_dataset_name
- )
-
- dataset_properties = DatasetProperties(
- name=datahub_dataset_name.get_table_display_name(),
- description=(
- unquote_and_decode_unicode_escape_seq(table.comment)
- if table.comment
- else ""
- ),
- qualifiedName=str(datahub_dataset_name),
- created=(
- TimeStamp(time=int(table.created.timestamp() * 1000))
- if table.created is not None
- else None
- ),
- lastModified=(
- TimeStamp(time=int(table.last_altered.timestamp() * 1000))
- if table.last_altered is not None
- else None
- ),
- externalUrl=(
- BQ_EXTERNAL_TABLE_URL_TEMPLATE.format(
- project=project_id, dataset=dataset_name, table=table.name
- )
- if self.config.include_external_url
- else None
- ),
- )
- if custom_properties:
- dataset_properties.customProperties.update(custom_properties)
-
- yield MetadataChangeProposalWrapper(
- entityUrn=dataset_urn, aspect=dataset_properties
- ).as_workunit()
-
- if tags_to_add:
- yield self.gen_tags_aspect_workunit(dataset_urn, tags_to_add)
-
- yield from add_table_to_schema_container(
- dataset_urn=dataset_urn,
- parent_container_key=self.gen_dataset_key(project_id, dataset_name),
- )
- yield self.get_dataplatform_instance_aspect(
- dataset_urn=dataset_urn, project_id=project_id
- )
-
- subTypes = SubTypes(typeNames=sub_types)
- yield MetadataChangeProposalWrapper(
- entityUrn=dataset_urn, aspect=subTypes
- ).as_workunit()
-
- if self.domain_registry:
- yield from get_domain_wu(
- dataset_name=str(datahub_dataset_name),
- entity_urn=dataset_urn,
- domain_registry=self.domain_registry,
- domain_config=self.config.domain,
- )
-
- def gen_tags_aspect_workunit(
- self, dataset_urn: str, tags_to_add: List[str]
- ) -> MetadataWorkUnit:
- tags = GlobalTagsClass(
- tags=[TagAssociationClass(tag_to_add) for tag_to_add in tags_to_add]
- )
- return MetadataChangeProposalWrapper(
- entityUrn=dataset_urn, aspect=tags
- ).as_workunit()
-
def gen_dataset_urn(
self, project_id: str, dataset_name: str, table: str, use_raw_name: bool = False
) -> str:
@@ -1235,241 +315,9 @@ def gen_dataset_urn_from_raw_ref(self, ref: BigQueryTableRef) -> str:
use_raw_name=True,
)
- def gen_dataset_urn_from_ref(self, ref: BigQueryTableRef) -> str:
- return self.gen_dataset_urn(
- ref.table_identifier.project_id,
- ref.table_identifier.dataset,
- ref.table_identifier.table,
- )
-
- def gen_schema_fields(self, columns: List[BigqueryColumn]) -> List[SchemaField]:
- schema_fields: List[SchemaField] = []
-
- # Below line affects HiveColumnToAvroConverter._STRUCT_TYPE_SEPARATOR in global scope
- # TODO: Refractor this such that
- # converter = HiveColumnToAvroConverter(struct_type_separator=" ");
- # converter.get_schema_fields_for_hive_column(...)
- original_struct_type_separator = (
- HiveColumnToAvroConverter._STRUCT_TYPE_SEPARATOR
- )
- HiveColumnToAvroConverter._STRUCT_TYPE_SEPARATOR = " "
- _COMPLEX_TYPE = re.compile("^(struct|array)")
- last_id = -1
- for col in columns:
- # if col.data_type is empty that means this column is part of a complex type
- if col.data_type is None or _COMPLEX_TYPE.match(col.data_type.lower()):
- # If the we have seen the ordinal position that most probably means we already processed this complex type
- if last_id != col.ordinal_position:
- schema_fields.extend(
- get_schema_fields_for_hive_column(
- col.name, col.data_type.lower(), description=col.comment
- )
- )
-
- # We have to add complex type comments to the correct level
- if col.comment:
- for idx, field in enumerate(schema_fields):
- # Remove all the [version=2.0].[type=struct]. tags to get the field path
- if (
- re.sub(
- r"\[.*?\]\.",
- "",
- field.fieldPath.lower(),
- 0,
- re.MULTILINE,
- )
- == col.field_path.lower()
- ):
- field.description = col.comment
- schema_fields[idx] = field
- break
- else:
- tags = []
- if col.is_partition_column:
- tags.append(
- TagAssociationClass(make_tag_urn(Constants.TAG_PARTITION_KEY))
- )
-
- if col.cluster_column_position is not None:
- tags.append(
- TagAssociationClass(
- make_tag_urn(
- f"{CLUSTERING_COLUMN_TAG}_{col.cluster_column_position}"
- )
- )
- )
-
- if col.policy_tags:
- for policy_tag in col.policy_tags:
- tags.append(TagAssociationClass(make_tag_urn(policy_tag)))
- field = SchemaField(
- fieldPath=col.name,
- type=SchemaFieldDataType(
- self.BIGQUERY_FIELD_TYPE_MAPPINGS.get(col.data_type, NullType)()
- ),
- nativeDataType=col.data_type,
- description=col.comment,
- nullable=col.is_nullable,
- globalTags=GlobalTagsClass(tags=tags),
- )
- schema_fields.append(field)
- last_id = col.ordinal_position
- HiveColumnToAvroConverter._STRUCT_TYPE_SEPARATOR = (
- original_struct_type_separator
- )
- return schema_fields
-
- def gen_schema_metadata(
- self,
- dataset_urn: str,
- table: Union[BigqueryTable, BigqueryView, BigqueryTableSnapshot],
- columns: List[BigqueryColumn],
- dataset_name: BigqueryTableIdentifier,
- ) -> MetadataWorkUnit:
- schema_metadata = SchemaMetadata(
- schemaName=str(dataset_name),
- platform=make_data_platform_urn(self.platform),
- version=0,
- hash="",
- platformSchema=MySqlDDL(tableSchema=""),
- # fields=[],
- fields=self.gen_schema_fields(columns),
- )
-
- if self.config.lineage_parse_view_ddl or self.config.lineage_use_sql_parser:
- self.sql_parser_schema_resolver.add_schema_metadata(
- dataset_urn, schema_metadata
- )
-
- return MetadataChangeProposalWrapper(
- entityUrn=dataset_urn, aspect=schema_metadata
- ).as_workunit()
-
def get_report(self) -> BigQueryV2Report:
return self.report
- def get_tables_for_dataset(
- self,
- project_id: str,
- dataset_name: str,
- ) -> Iterable[BigqueryTable]:
- # In bigquery there is no way to query all tables in a Project id
- with PerfTimer() as timer:
- # Partitions view throw exception if we try to query partition info for too many tables
- # so we have to limit the number of tables we query partition info.
- # The conn.list_tables returns table infos that information_schema doesn't contain and this
- # way we can merge that info with the queried one.
- # https://cloud.google.com/bigquery/docs/information-schema-partitions
- max_batch_size: int = (
- self.config.number_of_datasets_process_in_batch
- if not self.config.is_profiling_enabled()
- else self.config.number_of_datasets_process_in_batch_if_profiling_enabled
- )
-
- # We get the list of tables in the dataset to get core table properties and to be able to process the tables in batches
- # We collect only the latest shards from sharded tables (tables with _YYYYMMDD suffix) and ignore temporary tables
- table_items = self.get_core_table_details(
- dataset_name, project_id, self.config.temp_table_dataset_prefix
- )
-
- items_to_get: Dict[str, TableListItem] = {}
- for table_item in table_items.keys():
- items_to_get[table_item] = table_items[table_item]
- if len(items_to_get) % max_batch_size == 0:
- yield from self.bigquery_data_dictionary.get_tables_for_dataset(
- project_id,
- dataset_name,
- items_to_get,
- with_data_read_permission=self.config.have_table_data_read_permission,
- )
- items_to_get.clear()
-
- if items_to_get:
- yield from self.bigquery_data_dictionary.get_tables_for_dataset(
- project_id,
- dataset_name,
- items_to_get,
- with_data_read_permission=self.config.have_table_data_read_permission,
- )
-
- self.report.metadata_extraction_sec[f"{project_id}.{dataset_name}"] = round(
- timer.elapsed_seconds(), 2
- )
-
- def get_core_table_details(
- self, dataset_name: str, project_id: str, temp_table_dataset_prefix: str
- ) -> Dict[str, TableListItem]:
- table_items: Dict[str, TableListItem] = {}
- # Dict to store sharded table and the last seen max shard id
- sharded_tables: Dict[str, TableListItem] = {}
-
- for table in self.bigquery_data_dictionary.list_tables(
- dataset_name, project_id
- ):
- table_identifier = BigqueryTableIdentifier(
- project_id=project_id,
- dataset=dataset_name,
- table=table.table_id,
- )
-
- if table.table_type == "VIEW":
- if (
- not self.config.include_views
- or not self.config.view_pattern.allowed(
- table_identifier.raw_table_name()
- )
- ):
- self.report.report_dropped(table_identifier.raw_table_name())
- continue
- else:
- if not self.config.table_pattern.allowed(
- table_identifier.raw_table_name()
- ):
- self.report.report_dropped(table_identifier.raw_table_name())
- continue
-
- _, shard = BigqueryTableIdentifier.get_table_and_shard(
- table_identifier.table
- )
- table_name = table_identifier.get_table_name().split(".")[-1]
-
- # Sharded tables look like: table_20220120
- # For sharded tables we only process the latest shard and ignore the rest
- # to find the latest shard we iterate over the list of tables and store the maximum shard id
- # We only have one special case where the table name is a date `20220110`
- # in this case we merge all these tables under dataset name as table name.
- # For example some_dataset.20220110 will be turned to some_dataset.some_dataset
- # It seems like there are some bigquery user who uses this non-standard way of sharding the tables.
- if shard:
- if table_name not in sharded_tables:
- sharded_tables[table_name] = table
- continue
-
- stored_table_identifier = BigqueryTableIdentifier(
- project_id=project_id,
- dataset=dataset_name,
- table=sharded_tables[table_name].table_id,
- )
- _, stored_shard = BigqueryTableIdentifier.get_table_and_shard(
- stored_table_identifier.table
- )
- # When table is none, we use dataset_name as table_name
- assert stored_shard
- if stored_shard < shard:
- sharded_tables[table_name] = table
- continue
- elif str(table_identifier).startswith(temp_table_dataset_prefix):
- logger.debug(f"Dropping temporary table {table_identifier.table}")
- self.report.report_dropped(table_identifier.raw_table_name())
- continue
-
- table_items[table.table_id] = table
-
- # Adding maximum shards to the list of tables
- table_items.update({value.table_id: value for value in sharded_tables.values()})
-
- return table_items
-
def add_config_to_report(self):
self.report.include_table_lineage = self.config.include_table_lineage
self.report.use_date_sharded_audit_log_tables = (
diff --git a/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery_audit_log_api.py b/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery_audit_log_api.py
index 75e116773df96..7d2f8ee0e1fd8 100644
--- a/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery_audit_log_api.py
+++ b/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery_audit_log_api.py
@@ -66,6 +66,7 @@ def get_exported_bigquery_audit_metadata(
rate_limiter = RateLimiter(max_calls=self.requests_per_min, period=60)
with self.report.get_exported_log_entries as current_timer:
+ self.report.num_get_exported_log_entries_api_requests += 1
for dataset in bigquery_audit_metadata_datasets:
logger.info(
f"Start loading log entries from BigQueryAuditMetadata in {dataset}"
@@ -115,6 +116,7 @@ def get_bigquery_log_entries_via_gcp_logging(
)
with self.report.list_log_entries as current_timer:
+ self.report.num_list_log_entries_api_requests += 1
list_entries = client.list_entries(
filter_=filter,
page_size=log_page_size,
diff --git a/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery_config.py b/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery_config.py
index 578c9dddbd2e4..fe961dbd780f6 100644
--- a/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery_config.py
+++ b/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery_config.py
@@ -24,6 +24,10 @@
logger = logging.getLogger(__name__)
+DEFAULT_BQ_SCHEMA_PARALLELISM = int(
+ os.getenv("DATAHUB_BIGQUERY_SCHEMA_PARALLELISM", 20)
+)
+
class BigQueryUsageConfig(BaseUsageConfig):
_query_log_delay_removed = pydantic_removed_field("query_log_delay")
@@ -175,12 +179,12 @@ class BigQueryV2Config(
number_of_datasets_process_in_batch: int = Field(
hidden_from_docs=True,
- default=500,
+ default=10000,
description="Number of table queried in batch when getting metadata. This is a low level config property which should be touched with care.",
)
number_of_datasets_process_in_batch_if_profiling_enabled: int = Field(
- default=200,
+ default=1000,
description="Number of partitioned table queried in batch when getting metadata. This is a low level config property which should be touched with care. This restriction is needed because we query partitions system view which throws error if we try to touch too many tables.",
)
@@ -313,6 +317,12 @@ def have_table_data_read_permission(self) -> bool:
hidden_from_schema=True,
)
+ max_threads_dataset_parallelism: int = Field(
+ default=DEFAULT_BQ_SCHEMA_PARALLELISM,
+ description="Number of worker threads to use to parallelize BigQuery Dataset Metadata Extraction."
+ " Set to 1 to disable.",
+ )
+
@root_validator(skip_on_failure=True)
def profile_default_settings(cls, values: Dict) -> Dict:
# Extra default SQLAlchemy option for better connection pooling and threading.
diff --git a/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery_report.py b/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery_report.py
index 8a1bf9e5f3d1d..4cfcc3922ddc3 100644
--- a/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery_report.py
+++ b/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery_report.py
@@ -20,20 +20,32 @@
@dataclass
class BigQuerySchemaApiPerfReport(Report):
- num_list_projects: int = 0
+ num_listed_projects: int = 0
num_list_projects_retry_request: int = 0
+ num_list_projects_api_requests: int = 0
+ num_list_datasets_api_requests: int = 0
+ num_get_columns_for_dataset_api_requests: int = 0
+ num_get_tables_for_dataset_api_requests: int = 0
+ num_list_tables_api_requests: int = 0
+ num_get_views_for_dataset_api_requests: int = 0
+ num_get_snapshots_for_dataset_api_requests: int = 0
+
list_projects: PerfTimer = field(default_factory=PerfTimer)
list_datasets: PerfTimer = field(default_factory=PerfTimer)
- get_columns_for_dataset: PerfTimer = field(default_factory=PerfTimer)
- get_tables_for_dataset: PerfTimer = field(default_factory=PerfTimer)
- list_tables: PerfTimer = field(default_factory=PerfTimer)
- get_views_for_dataset: PerfTimer = field(default_factory=PerfTimer)
- get_snapshots_for_dataset: PerfTimer = field(default_factory=PerfTimer)
+
+ get_columns_for_dataset_sec: float = 0
+ get_tables_for_dataset_sec: float = 0
+ list_tables_sec: float = 0
+ get_views_for_dataset_sec: float = 0
+ get_snapshots_for_dataset_sec: float = 0
@dataclass
class BigQueryAuditLogApiPerfReport(Report):
+ num_get_exported_log_entries_api_requests: int = 0
get_exported_log_entries: PerfTimer = field(default_factory=PerfTimer)
+
+ num_list_log_entries_api_requests: int = 0
list_log_entries: PerfTimer = field(default_factory=PerfTimer)
@@ -85,7 +97,6 @@ class BigQueryV2Report(
num_usage_parsed_log_entries: TopKDict[str, int] = field(
default_factory=int_top_k_dict
)
- usage_error_count: Dict[str, int] = field(default_factory=int_top_k_dict)
num_usage_resources_dropped: int = 0
num_usage_operations_dropped: int = 0
diff --git a/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery_schema.py b/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery_schema.py
index fe9bbc134a147..7bb9becfc9a0d 100644
--- a/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery_schema.py
+++ b/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery_schema.py
@@ -24,6 +24,7 @@
BigqueryTableType,
)
from datahub.ingestion.source.sql.sql_generic import BaseColumn, BaseTable, BaseView
+from datahub.utilities.perf_timer import PerfTimer
from datahub.utilities.ratelimiter import RateLimiter
logger: logging.Logger = logging.getLogger(__name__)
@@ -163,33 +164,31 @@ def _should_retry(exc: BaseException) -> bool:
return True
with self.report.list_projects:
- try:
- # Bigquery API has limit in calling project.list request i.e. 2 request per second.
- # https://cloud.google.com/bigquery/quotas#api_request_quotas
- # Whenever this limit reached an exception occur with msg
- # 'Quota exceeded: Your user exceeded quota for concurrent project.lists requests.'
- # Hence, added the api request retry of 15 min.
- # We already tried adding rate_limit externally, proving max_result and page_size
- # to restrict the request calls inside list_project but issue still occured.
- projects_iterator = self.bq_client.list_projects(
- retry=retry.Retry(
- predicate=_should_retry, initial=10, maximum=180, timeout=900
- )
+ self.report.num_list_projects_api_requests += 1
+ # Bigquery API has limit in calling project.list request i.e. 2 request per second.
+ # https://cloud.google.com/bigquery/quotas#api_request_quotas
+ # Whenever this limit reached an exception occur with msg
+ # 'Quota exceeded: Your user exceeded quota for concurrent project.lists requests.'
+ # Hence, added the api request retry of 15 min.
+ # We already tried adding rate_limit externally, proving max_result and page_size
+ # to restrict the request calls inside list_project but issue still occured.
+ projects_iterator = self.bq_client.list_projects(
+ retry=retry.Retry(
+ predicate=_should_retry, initial=10, maximum=180, timeout=900
)
- projects: List[BigqueryProject] = [
- BigqueryProject(id=p.project_id, name=p.friendly_name)
- for p in projects_iterator
- ]
- self.report.num_list_projects = len(projects)
- return projects
- except Exception as e:
- logger.error(f"Error getting projects. {e}", exc_info=True)
- return []
+ )
+ projects: List[BigqueryProject] = [
+ BigqueryProject(id=p.project_id, name=p.friendly_name)
+ for p in projects_iterator
+ ]
+ self.report.num_listed_projects = len(projects)
+ return projects
def get_datasets_for_project_id(
self, project_id: str, maxResults: Optional[int] = None
) -> List[BigqueryDataset]:
with self.report.list_datasets:
+ self.report.num_list_datasets_api_requests += 1
datasets = self.bq_client.list_datasets(project_id, max_results=maxResults)
return [
BigqueryDataset(name=d.dataset_id, labels=d.labels) for d in datasets
@@ -222,50 +221,42 @@ def get_datasets_for_project_id_with_information_schema(
def list_tables(
self, dataset_name: str, project_id: str
) -> Iterator[TableListItem]:
- with self.report.list_tables as current_timer:
+ with PerfTimer() as current_timer:
for table in self.bq_client.list_tables(f"{project_id}.{dataset_name}"):
with current_timer.pause():
yield table
+ self.report.num_list_tables_api_requests += 1
+ self.report.list_tables_sec += current_timer.elapsed_seconds()
def get_tables_for_dataset(
self,
project_id: str,
dataset_name: str,
tables: Dict[str, TableListItem],
+ report: BigQueryV2Report,
with_data_read_permission: bool = False,
- report: Optional[BigQueryV2Report] = None,
) -> Iterator[BigqueryTable]:
- with self.report.get_tables_for_dataset as current_timer:
+ with PerfTimer() as current_timer:
filter_clause: str = ", ".join(f"'{table}'" for table in tables.keys())
if with_data_read_permission:
- # Tables are ordered by name and table suffix to make sure we always process the latest sharded table
- # and skip the others. Sharded tables are tables with suffix _20220102
- cur = self.get_query_result(
- BigqueryQuery.tables_for_dataset.format(
- project_id=project_id,
- dataset_name=dataset_name,
- table_filter=(
- f" and t.table_name in ({filter_clause})"
- if filter_clause
- else ""
- ),
- ),
- )
+ query_template = BigqueryQuery.tables_for_dataset
else:
- # Tables are ordered by name and table suffix to make sure we always process the latest sharded table
- # and skip the others. Sharded tables are tables with suffix _20220102
- cur = self.get_query_result(
- BigqueryQuery.tables_for_dataset_without_partition_data.format(
- project_id=project_id,
- dataset_name=dataset_name,
- table_filter=(
- f" and t.table_name in ({filter_clause})"
- if filter_clause
- else ""
- ),
+ query_template = BigqueryQuery.tables_for_dataset_without_partition_data
+
+ # Tables are ordered by name and table suffix to make sure we always process the latest sharded table
+ # and skip the others. Sharded tables are tables with suffix _20220102
+ cur = self.get_query_result(
+ query_template.format(
+ project_id=project_id,
+ dataset_name=dataset_name,
+ table_filter=(
+ f" and t.table_name in ({filter_clause})"
+ if filter_clause
+ else ""
),
- )
+ ),
+ )
for table in cur:
try:
@@ -275,15 +266,14 @@ def get_tables_for_dataset(
)
except Exception as e:
table_name = f"{project_id}.{dataset_name}.{table.table_name}"
- logger.warning(
- f"Error while processing table {table_name}",
- exc_info=True,
+ report.warning(
+ title="Failed to process table",
+ message="Error encountered while processing table",
+ context=table_name,
+ exc=e,
)
- if report:
- report.report_warning(
- "metadata-extraction",
- f"Failed to get table {table_name}: {e}",
- )
+ self.report.num_get_tables_for_dataset_api_requests += 1
+ self.report.get_tables_for_dataset_sec += current_timer.elapsed_seconds()
@staticmethod
def _make_bigquery_table(
@@ -332,7 +322,7 @@ def get_views_for_dataset(
has_data_read: bool,
report: BigQueryV2Report,
) -> Iterator[BigqueryView]:
- with self.report.get_views_for_dataset as current_timer:
+ with PerfTimer() as current_timer:
if has_data_read:
# If profiling is enabled
cur = self.get_query_result(
@@ -353,14 +343,14 @@ def get_views_for_dataset(
yield BigQuerySchemaApi._make_bigquery_view(table)
except Exception as e:
view_name = f"{project_id}.{dataset_name}.{table.table_name}"
- logger.warning(
- f"Error while processing view {view_name}",
- exc_info=True,
- )
- report.report_warning(
- "metadata-extraction",
- f"Failed to get view {view_name}: {e}",
+ report.warning(
+ title="Failed to process view",
+ message="Error encountered while processing view",
+ context=view_name,
+ exc=e,
)
+ self.report.num_get_views_for_dataset_api_requests += 1
+ self.report.get_views_for_dataset_sec += current_timer.elapsed_seconds()
@staticmethod
def _make_bigquery_view(view: bigquery.Row) -> BigqueryView:
@@ -416,22 +406,18 @@ def get_policy_tags_for_column(
)
yield policy_tag.display_name
except Exception as e:
- logger.warning(
- f"Unexpected error when retrieving policy tag {policy_tag_name} for column {column_name} in table {table_name}: {e}",
- exc_info=True,
- )
- report.report_warning(
- "metadata-extraction",
- f"Failed to retrieve policy tag {policy_tag_name} for column {column_name} in table {table_name} due to unexpected error: {e}",
+ report.warning(
+ title="Failed to retrieve policy tag",
+ message="Unexpected error when retrieving policy tag for column",
+ context=f"policy tag {policy_tag_name} for column {column_name} in table {table_ref}",
+ exc=e,
)
except Exception as e:
- logger.error(
- f"Unexpected error retrieving schema for table {table_name} in dataset {dataset_name}, project {project_id}: {e}",
- exc_info=True,
- )
- report.report_warning(
- "metadata-extraction",
- f"Failed to retrieve schema for table {table_name} in dataset {dataset_name}, project {project_id} due to unexpected error: {e}",
+ report.warning(
+ title="Failed to retrieve policy tag for table",
+ message="Unexpected error retrieving policy tag for table",
+ context=table_ref,
+ exc=e,
)
def get_columns_for_dataset(
@@ -445,7 +431,7 @@ def get_columns_for_dataset(
rate_limiter: Optional[RateLimiter] = None,
) -> Optional[Dict[str, List[BigqueryColumn]]]:
columns: Dict[str, List[BigqueryColumn]] = defaultdict(list)
- with self.report.get_columns_for_dataset:
+ with PerfTimer() as timer:
try:
cur = self.get_query_result(
(
@@ -461,89 +447,57 @@ def get_columns_for_dataset(
),
)
except Exception as e:
- logger.warning(f"Columns for dataset query failed with exception: {e}")
- # Error - Information schema query returned too much data.
- # Please repeat query with more selective predicates.
+ report.warning(
+ title="Failed to retrieve columns for dataset",
+ message="Query to get columns for dataset failed with exception",
+ context=f"{project_id}.{dataset_name}",
+ exc=e,
+ )
return None
last_seen_table: str = ""
for column in cur:
- if (
- column_limit
- and column.table_name in columns
- and len(columns[column.table_name]) >= column_limit
- ):
- if last_seen_table != column.table_name:
- logger.warning(
- f"{project_id}.{dataset_name}.{column.table_name} contains more than {column_limit} columns, only processing {column_limit} columns"
- )
- last_seen_table = column.table_name
- else:
- columns[column.table_name].append(
- BigqueryColumn(
- name=column.column_name,
- ordinal_position=column.ordinal_position,
- field_path=column.field_path,
- is_nullable=column.is_nullable == "YES",
- data_type=column.data_type,
- comment=column.comment,
- is_partition_column=column.is_partitioning_column == "YES",
- cluster_column_position=column.clustering_ordinal_position,
- policy_tags=(
- list(
- self.get_policy_tags_for_column(
- project_id,
- dataset_name,
- column.table_name,
- column.column_name,
- report,
- rate_limiter,
+ with timer.pause():
+ if (
+ column_limit
+ and column.table_name in columns
+ and len(columns[column.table_name]) >= column_limit
+ ):
+ if last_seen_table != column.table_name:
+ logger.warning(
+ f"{project_id}.{dataset_name}.{column.table_name} contains more than {column_limit} columns, only processing {column_limit} columns"
+ )
+ last_seen_table = column.table_name
+ else:
+ columns[column.table_name].append(
+ BigqueryColumn(
+ name=column.column_name,
+ ordinal_position=column.ordinal_position,
+ field_path=column.field_path,
+ is_nullable=column.is_nullable == "YES",
+ data_type=column.data_type,
+ comment=column.comment,
+ is_partition_column=column.is_partitioning_column
+ == "YES",
+ cluster_column_position=column.clustering_ordinal_position,
+ policy_tags=(
+ list(
+ self.get_policy_tags_for_column(
+ project_id,
+ dataset_name,
+ column.table_name,
+ column.column_name,
+ report,
+ rate_limiter,
+ )
)
- )
- if extract_policy_tags_from_catalog
- else []
- ),
+ if extract_policy_tags_from_catalog
+ else []
+ ),
+ )
)
- )
-
- return columns
-
- # This is not used anywhere
- def get_columns_for_table(
- self,
- table_identifier: BigqueryTableIdentifier,
- column_limit: Optional[int],
- ) -> List[BigqueryColumn]:
- cur = self.get_query_result(
- BigqueryQuery.columns_for_table.format(table_identifier=table_identifier),
- )
-
- columns: List[BigqueryColumn] = []
- last_seen_table: str = ""
- for column in cur:
- if (
- column_limit
- and column.table_name in columns
- and len(columns[column.table_name]) >= column_limit
- ):
- if last_seen_table != column.table_name:
- logger.warning(
- f"{table_identifier.project_id}.{table_identifier.dataset}.{column.table_name} contains more than {column_limit} columns, only processing {column_limit} columns"
- )
- else:
- columns.append(
- BigqueryColumn(
- name=column.column_name,
- ordinal_position=column.ordinal_position,
- is_nullable=column.is_nullable == "YES",
- field_path=column.field_path,
- data_type=column.data_type,
- comment=column.comment,
- is_partition_column=column.is_partitioning_column == "YES",
- cluster_column_position=column.clustering_ordinal_position,
- )
- )
- last_seen_table = column.table_name
+ self.report.num_get_columns_for_dataset_api_requests += 1
+ self.report.get_columns_for_dataset_sec += timer.elapsed_seconds()
return columns
@@ -554,7 +508,7 @@ def get_snapshots_for_dataset(
has_data_read: bool,
report: BigQueryV2Report,
) -> Iterator[BigqueryTableSnapshot]:
- with self.report.get_snapshots_for_dataset as current_timer:
+ with PerfTimer() as current_timer:
if has_data_read:
# If profiling is enabled
cur = self.get_query_result(
@@ -575,14 +529,14 @@ def get_snapshots_for_dataset(
yield BigQuerySchemaApi._make_bigquery_table_snapshot(table)
except Exception as e:
snapshot_name = f"{project_id}.{dataset_name}.{table.table_name}"
- logger.warning(
- f"Error while processing view {snapshot_name}",
- exc_info=True,
- )
report.report_warning(
- "metadata-extraction",
- f"Failed to get view {snapshot_name}: {e}",
+ title="Failed to process snapshot",
+ message="Error encountered while processing snapshot",
+ context=snapshot_name,
+ exc=e,
)
+ self.report.num_get_snapshots_for_dataset_api_requests += 1
+ self.report.get_snapshots_for_dataset_sec += current_timer.elapsed_seconds()
@staticmethod
def _make_bigquery_table_snapshot(snapshot: bigquery.Row) -> BigqueryTableSnapshot:
diff --git a/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery_schema_gen.py b/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery_schema_gen.py
new file mode 100644
index 0000000000000..3ffcb225db1c2
--- /dev/null
+++ b/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery_schema_gen.py
@@ -0,0 +1,1090 @@
+import logging
+import re
+from collections import defaultdict
+from typing import Callable, Dict, Iterable, List, Optional, Set, Type, Union, cast
+
+from google.cloud.bigquery.table import TableListItem
+
+from datahub.configuration.pattern_utils import is_schema_allowed, is_tag_allowed
+from datahub.emitter.mce_builder import (
+ make_data_platform_urn,
+ make_dataplatform_instance_urn,
+ make_tag_urn,
+)
+from datahub.emitter.mcp import MetadataChangeProposalWrapper
+from datahub.emitter.mcp_builder import BigQueryDatasetKey, ContainerKey, ProjectIdKey
+from datahub.ingestion.api.workunit import MetadataWorkUnit
+from datahub.ingestion.glossary.classification_mixin import (
+ SAMPLE_SIZE_MULTIPLIER,
+ ClassificationHandler,
+ classification_workunit_processor,
+)
+from datahub.ingestion.source.bigquery_v2.bigquery_audit import (
+ BigqueryTableIdentifier,
+ BigQueryTableRef,
+)
+from datahub.ingestion.source.bigquery_v2.bigquery_config import BigQueryV2Config
+from datahub.ingestion.source.bigquery_v2.bigquery_data_reader import BigQueryDataReader
+from datahub.ingestion.source.bigquery_v2.bigquery_helper import (
+ unquote_and_decode_unicode_escape_seq,
+)
+from datahub.ingestion.source.bigquery_v2.bigquery_report import BigQueryV2Report
+from datahub.ingestion.source.bigquery_v2.bigquery_schema import (
+ BigqueryColumn,
+ BigqueryDataset,
+ BigqueryProject,
+ BigQuerySchemaApi,
+ BigqueryTable,
+ BigqueryTableSnapshot,
+ BigqueryView,
+)
+from datahub.ingestion.source.bigquery_v2.common import (
+ BQ_EXTERNAL_DATASET_URL_TEMPLATE,
+ BQ_EXTERNAL_TABLE_URL_TEMPLATE,
+)
+from datahub.ingestion.source.bigquery_v2.profiler import BigqueryProfiler
+from datahub.ingestion.source.common.subtypes import (
+ DatasetContainerSubTypes,
+ DatasetSubTypes,
+)
+from datahub.ingestion.source.sql.sql_utils import (
+ add_table_to_schema_container,
+ gen_database_container,
+ gen_schema_container,
+ get_domain_wu,
+)
+from datahub.ingestion.source_report.ingestion_stage import (
+ METADATA_EXTRACTION,
+ PROFILING,
+)
+from datahub.metadata.com.linkedin.pegasus2avro.common import (
+ Status,
+ SubTypes,
+ TimeStamp,
+)
+from datahub.metadata.com.linkedin.pegasus2avro.dataset import (
+ DatasetProperties,
+ ViewProperties,
+)
+from datahub.metadata.com.linkedin.pegasus2avro.schema import (
+ ArrayType,
+ BooleanType,
+ BytesType,
+ DateType,
+ MySqlDDL,
+ NullType,
+ NumberType,
+ RecordType,
+ SchemaField,
+ SchemaFieldDataType,
+ SchemaMetadata,
+ StringType,
+ TimeType,
+)
+from datahub.metadata.schema_classes import (
+ DataPlatformInstanceClass,
+ GlobalTagsClass,
+ TagAssociationClass,
+)
+from datahub.sql_parsing.schema_resolver import SchemaResolver
+from datahub.utilities.file_backed_collections import FileBackedDict
+from datahub.utilities.hive_schema_to_avro import (
+ HiveColumnToAvroConverter,
+ get_schema_fields_for_hive_column,
+)
+from datahub.utilities.mapping import Constants
+from datahub.utilities.perf_timer import PerfTimer
+from datahub.utilities.ratelimiter import RateLimiter
+from datahub.utilities.registries.domain_registry import DomainRegistry
+from datahub.utilities.threaded_iterator_executor import ThreadedIteratorExecutor
+
+logger: logging.Logger = logging.getLogger(__name__)
+# Handle table snapshots
+# See https://cloud.google.com/bigquery/docs/table-snapshots-intro.
+SNAPSHOT_TABLE_REGEX = re.compile(r"^(.+)@(\d{13})$")
+CLUSTERING_COLUMN_TAG = "CLUSTERING_COLUMN"
+
+
+class BigQuerySchemaGenerator:
+ # https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types
+ # Note: We use the hive schema parser to parse nested BigQuery types. We also have
+ # some extra type mappings in that file.
+ BIGQUERY_FIELD_TYPE_MAPPINGS: Dict[
+ str,
+ Type[
+ Union[
+ ArrayType,
+ BytesType,
+ BooleanType,
+ NumberType,
+ RecordType,
+ StringType,
+ TimeType,
+ DateType,
+ NullType,
+ ]
+ ],
+ ] = {
+ "BYTES": BytesType,
+ "BOOL": BooleanType,
+ "INT": NumberType,
+ "INT64": NumberType,
+ "SMALLINT": NumberType,
+ "INTEGER": NumberType,
+ "BIGINT": NumberType,
+ "TINYINT": NumberType,
+ "BYTEINT": NumberType,
+ "STRING": StringType,
+ "TIME": TimeType,
+ "TIMESTAMP": TimeType,
+ "DATE": DateType,
+ "DATETIME": TimeType,
+ "GEOGRAPHY": NullType,
+ "JSON": RecordType,
+ "INTERVAL": NullType,
+ "ARRAY": ArrayType,
+ "STRUCT": RecordType,
+ }
+
+ def __init__(
+ self,
+ config: BigQueryV2Config,
+ report: BigQueryV2Report,
+ bigquery_data_dictionary: BigQuerySchemaApi,
+ domain_registry: Optional[DomainRegistry],
+ sql_parser_schema_resolver: SchemaResolver,
+ profiler: BigqueryProfiler,
+ dataset_urn_builder: Callable[[str, str, str], str],
+ ):
+ self.config = config
+ self.report = report
+ self.bigquery_data_dictionary = bigquery_data_dictionary
+ self.domain_registry = domain_registry
+ self.sql_parser_schema_resolver = sql_parser_schema_resolver
+ self.profiler = profiler
+ self.gen_dataset_urn = dataset_urn_builder
+ self.platform: str = "bigquery"
+
+ self.classification_handler = ClassificationHandler(self.config, self.report)
+ self.data_reader: Optional[BigQueryDataReader] = None
+ if self.classification_handler.is_classification_enabled():
+ self.data_reader = BigQueryDataReader.create(
+ self.config.get_bigquery_client()
+ )
+
+ # Global store of table identifiers for lineage filtering
+ self.table_refs: Set[str] = set()
+
+ # Maps project -> view_ref, so we can find all views in a project
+ self.view_refs_by_project: Dict[str, Set[str]] = defaultdict(set)
+ # Maps project -> snapshot_ref, so we can find all snapshots in a project
+ self.snapshot_refs_by_project: Dict[str, Set[str]] = defaultdict(set)
+ # Maps view ref -> actual sql
+ self.view_definitions: FileBackedDict[str] = FileBackedDict()
+ # Maps snapshot ref -> Snapshot
+ self.snapshots_by_ref: FileBackedDict[BigqueryTableSnapshot] = FileBackedDict()
+
+ @property
+ def store_table_refs(self):
+ return self.config.include_table_lineage or self.config.include_usage_statistics
+
+ def get_project_workunits(
+ self, project: BigqueryProject
+ ) -> Iterable[MetadataWorkUnit]:
+ self.report.set_ingestion_stage(project.id, METADATA_EXTRACTION)
+ logger.info(f"Processing project: {project.id}")
+ yield from self._process_project(project)
+
+ def get_dataplatform_instance_aspect(
+ self, dataset_urn: str, project_id: str
+ ) -> MetadataWorkUnit:
+ aspect = DataPlatformInstanceClass(
+ platform=make_data_platform_urn(self.platform),
+ instance=(
+ make_dataplatform_instance_urn(self.platform, project_id)
+ if self.config.include_data_platform_instance
+ else None
+ ),
+ )
+ return MetadataChangeProposalWrapper(
+ entityUrn=dataset_urn, aspect=aspect
+ ).as_workunit()
+
+ def gen_dataset_key(self, db_name: str, schema: str) -> ContainerKey:
+ return BigQueryDatasetKey(
+ project_id=db_name,
+ dataset_id=schema,
+ platform=self.platform,
+ env=self.config.env,
+ backcompat_env_as_instance=True,
+ )
+
+ def gen_project_id_key(self, database: str) -> ContainerKey:
+ return ProjectIdKey(
+ project_id=database,
+ platform=self.platform,
+ env=self.config.env,
+ backcompat_env_as_instance=True,
+ )
+
+ def gen_project_id_containers(self, database: str) -> Iterable[MetadataWorkUnit]:
+ database_container_key = self.gen_project_id_key(database)
+
+ yield from gen_database_container(
+ database=database,
+ name=database,
+ sub_types=[DatasetContainerSubTypes.BIGQUERY_PROJECT],
+ domain_registry=self.domain_registry,
+ domain_config=self.config.domain,
+ database_container_key=database_container_key,
+ )
+
+ def gen_dataset_containers(
+ self, dataset: str, project_id: str, tags: Optional[Dict[str, str]] = None
+ ) -> Iterable[MetadataWorkUnit]:
+ schema_container_key = self.gen_dataset_key(project_id, dataset)
+
+ tags_joined: Optional[List[str]] = None
+ if tags and self.config.capture_dataset_label_as_tag:
+ tags_joined = [
+ f"{k}:{v}"
+ for k, v in tags.items()
+ if is_tag_allowed(self.config.capture_dataset_label_as_tag, k)
+ ]
+
+ database_container_key = self.gen_project_id_key(database=project_id)
+
+ yield from gen_schema_container(
+ database=project_id,
+ schema=dataset,
+ sub_types=[DatasetContainerSubTypes.BIGQUERY_DATASET],
+ domain_registry=self.domain_registry,
+ domain_config=self.config.domain,
+ schema_container_key=schema_container_key,
+ database_container_key=database_container_key,
+ external_url=(
+ BQ_EXTERNAL_DATASET_URL_TEMPLATE.format(
+ project=project_id, dataset=dataset
+ )
+ if self.config.include_external_url
+ else None
+ ),
+ tags=tags_joined,
+ )
+
+ def _process_project(
+ self, bigquery_project: BigqueryProject
+ ) -> Iterable[MetadataWorkUnit]:
+ db_tables: Dict[str, List[BigqueryTable]] = {}
+
+ project_id = bigquery_project.id
+ try:
+ bigquery_project.datasets = (
+ self.bigquery_data_dictionary.get_datasets_for_project_id(project_id)
+ )
+ except Exception as e:
+
+ if (
+ self.config.project_id or self.config.project_ids
+ ) and "not enabled BigQuery." in str(e):
+ action_mesage = (
+ "The project has not enabled BigQuery API. "
+ "Did you mistype project id in recipe ?"
+ )
+ else:
+ action_mesage = (
+ "Does your service account have `bigquery.datasets.get` permission ? "
+ "Assign predefined role `roles/bigquery.metadataViewer` to your service account."
+ )
+
+ self.report.failure(
+ title="Unable to get datasets for project",
+ message=action_mesage,
+ context=project_id,
+ exc=e,
+ )
+ return None
+
+ if len(bigquery_project.datasets) == 0:
+ action_message = (
+ "Either there are no datasets in this project or missing `bigquery.datasets.get` permission. "
+ "You can assign predefined roles/bigquery.metadataViewer role to your service account."
+ )
+ if self.config.exclude_empty_projects:
+ self.report.report_dropped(project_id)
+ logger.info(
+ f"Excluded project '{project_id}' since no datasets were found. {action_message}"
+ )
+ else:
+ yield from self.gen_project_id_containers(project_id)
+ self.report.warning(
+ title="No datasets found in project",
+ message=action_message,
+ context=project_id,
+ )
+ return
+
+ yield from self.gen_project_id_containers(project_id)
+
+ self.report.num_project_datasets_to_scan[project_id] = len(
+ bigquery_project.datasets
+ )
+ yield from self._process_project_datasets(bigquery_project, db_tables)
+
+ if self.config.is_profiling_enabled():
+ logger.info(f"Starting profiling project {project_id}")
+ self.report.set_ingestion_stage(project_id, PROFILING)
+ yield from self.profiler.get_workunits(
+ project_id=project_id,
+ tables=db_tables,
+ )
+
+ def _process_project_datasets(
+ self,
+ bigquery_project: BigqueryProject,
+ db_tables: Dict[str, List[BigqueryTable]],
+ ) -> Iterable[MetadataWorkUnit]:
+
+ db_views: Dict[str, List[BigqueryView]] = {}
+ db_snapshots: Dict[str, List[BigqueryTableSnapshot]] = {}
+ project_id = bigquery_project.id
+
+ def _process_schema_worker(
+ bigquery_dataset: BigqueryDataset,
+ ) -> Iterable[MetadataWorkUnit]:
+ if not is_schema_allowed(
+ self.config.dataset_pattern,
+ bigquery_dataset.name,
+ project_id,
+ self.config.match_fully_qualified_names,
+ ):
+ self.report.report_dropped(f"{bigquery_dataset.name}.*")
+ return
+ try:
+ # db_tables, db_views, and db_snapshots are populated in the this method
+ for wu in self._process_schema(
+ project_id, bigquery_dataset, db_tables, db_views, db_snapshots
+ ):
+ yield wu
+ except Exception as e:
+ if self.config.is_profiling_enabled():
+ action_mesage = "Does your service account has bigquery.tables.list, bigquery.routines.get, bigquery.routines.list permission, bigquery.tables.getData permission?"
+ else:
+ action_mesage = "Does your service account has bigquery.tables.list, bigquery.routines.get, bigquery.routines.list permission?"
+
+ self.report.failure(
+ title="Unable to get tables for dataset",
+ message=action_mesage,
+ context=f"{project_id}.{bigquery_dataset.name}",
+ exc=e,
+ )
+
+ for wu in ThreadedIteratorExecutor.process(
+ worker_func=_process_schema_worker,
+ args_list=[(bq_dataset,) for bq_dataset in bigquery_project.datasets],
+ max_workers=self.config.max_threads_dataset_parallelism,
+ ):
+ yield wu
+
+ def _process_schema(
+ self,
+ project_id: str,
+ bigquery_dataset: BigqueryDataset,
+ db_tables: Dict[str, List[BigqueryTable]],
+ db_views: Dict[str, List[BigqueryView]],
+ db_snapshots: Dict[str, List[BigqueryTableSnapshot]],
+ ) -> Iterable[MetadataWorkUnit]:
+ dataset_name = bigquery_dataset.name
+
+ yield from self.gen_dataset_containers(
+ dataset_name, project_id, bigquery_dataset.labels
+ )
+
+ columns = None
+
+ rate_limiter: Optional[RateLimiter] = None
+ if self.config.rate_limit:
+ rate_limiter = RateLimiter(
+ max_calls=self.config.requests_per_min, period=60
+ )
+
+ if (
+ self.config.include_tables
+ or self.config.include_views
+ or self.config.include_table_snapshots
+ ):
+ columns = self.bigquery_data_dictionary.get_columns_for_dataset(
+ project_id=project_id,
+ dataset_name=dataset_name,
+ column_limit=self.config.column_limit,
+ run_optimized_column_query=self.config.run_optimized_column_query,
+ extract_policy_tags_from_catalog=self.config.extract_policy_tags_from_catalog,
+ report=self.report,
+ rate_limiter=rate_limiter,
+ )
+
+ if self.config.include_tables:
+ db_tables[dataset_name] = list(
+ self.get_tables_for_dataset(project_id, dataset_name)
+ )
+
+ for table in db_tables[dataset_name]:
+ table_columns = columns.get(table.name, []) if columns else []
+ table_wu_generator = self._process_table(
+ table=table,
+ columns=table_columns,
+ project_id=project_id,
+ dataset_name=dataset_name,
+ )
+ yield from classification_workunit_processor(
+ table_wu_generator,
+ self.classification_handler,
+ self.data_reader,
+ [project_id, dataset_name, table.name],
+ data_reader_kwargs=dict(
+ sample_size_percent=(
+ self.config.classification.sample_size
+ * SAMPLE_SIZE_MULTIPLIER
+ / table.rows_count
+ if table.rows_count
+ else None
+ )
+ ),
+ )
+ elif self.store_table_refs:
+ # Need table_refs to calculate lineage and usage
+ for table_item in self.bigquery_data_dictionary.list_tables(
+ dataset_name, project_id
+ ):
+ identifier = BigqueryTableIdentifier(
+ project_id=project_id,
+ dataset=dataset_name,
+ table=table_item.table_id,
+ )
+ if not self.config.table_pattern.allowed(identifier.raw_table_name()):
+ self.report.report_dropped(identifier.raw_table_name())
+ continue
+ try:
+ self.table_refs.add(
+ str(BigQueryTableRef(identifier).get_sanitized_table_ref())
+ )
+ except Exception as e:
+ logger.warning(
+ f"Could not create table ref for {table_item.path}: {e}"
+ )
+
+ if self.config.include_views:
+ db_views[dataset_name] = list(
+ self.bigquery_data_dictionary.get_views_for_dataset(
+ project_id,
+ dataset_name,
+ self.config.is_profiling_enabled(),
+ self.report,
+ )
+ )
+
+ for view in db_views[dataset_name]:
+ view_columns = columns.get(view.name, []) if columns else []
+ yield from self._process_view(
+ view=view,
+ columns=view_columns,
+ project_id=project_id,
+ dataset_name=dataset_name,
+ )
+
+ if self.config.include_table_snapshots:
+ db_snapshots[dataset_name] = list(
+ self.bigquery_data_dictionary.get_snapshots_for_dataset(
+ project_id,
+ dataset_name,
+ self.config.is_profiling_enabled(),
+ self.report,
+ )
+ )
+
+ for snapshot in db_snapshots[dataset_name]:
+ snapshot_columns = columns.get(snapshot.name, []) if columns else []
+ yield from self._process_snapshot(
+ snapshot=snapshot,
+ columns=snapshot_columns,
+ project_id=project_id,
+ dataset_name=dataset_name,
+ )
+
+ # This method is used to generate the ignore list for datatypes the profiler doesn't support we have to do it here
+ # because the profiler doesn't have access to columns
+ def generate_profile_ignore_list(self, columns: List[BigqueryColumn]) -> List[str]:
+ ignore_list: List[str] = []
+ for column in columns:
+ if not column.data_type or any(
+ word in column.data_type.lower()
+ for word in ["array", "struct", "geography", "json"]
+ ):
+ ignore_list.append(column.field_path)
+ return ignore_list
+
+ def _process_table(
+ self,
+ table: BigqueryTable,
+ columns: List[BigqueryColumn],
+ project_id: str,
+ dataset_name: str,
+ ) -> Iterable[MetadataWorkUnit]:
+ table_identifier = BigqueryTableIdentifier(project_id, dataset_name, table.name)
+
+ self.report.report_entity_scanned(table_identifier.raw_table_name())
+
+ if not self.config.table_pattern.allowed(table_identifier.raw_table_name()):
+ self.report.report_dropped(table_identifier.raw_table_name())
+ return
+
+ if self.store_table_refs:
+ self.table_refs.add(
+ str(BigQueryTableRef(table_identifier).get_sanitized_table_ref())
+ )
+ table.column_count = len(columns)
+
+ # We only collect profile ignore list if profiling is enabled and profile_table_level_only is false
+ if (
+ self.config.is_profiling_enabled()
+ and not self.config.profiling.profile_table_level_only
+ ):
+ table.columns_ignore_from_profiling = self.generate_profile_ignore_list(
+ columns
+ )
+
+ if not table.column_count:
+ logger.warning(
+ f"Table doesn't have any column or unable to get columns for table: {table_identifier}"
+ )
+
+ # If table has time partitioning, set the data type of the partitioning field
+ if table.partition_info:
+ table.partition_info.column = next(
+ (
+ column
+ for column in columns
+ if column.name == table.partition_info.field
+ ),
+ None,
+ )
+ yield from self.gen_table_dataset_workunits(
+ table, columns, project_id, dataset_name
+ )
+
+ def _process_view(
+ self,
+ view: BigqueryView,
+ columns: List[BigqueryColumn],
+ project_id: str,
+ dataset_name: str,
+ ) -> Iterable[MetadataWorkUnit]:
+ table_identifier = BigqueryTableIdentifier(project_id, dataset_name, view.name)
+
+ self.report.report_entity_scanned(table_identifier.raw_table_name(), "view")
+
+ if not self.config.view_pattern.allowed(table_identifier.raw_table_name()):
+ self.report.report_dropped(table_identifier.raw_table_name())
+ return
+
+ if self.store_table_refs:
+ table_ref = str(
+ BigQueryTableRef(table_identifier).get_sanitized_table_ref()
+ )
+ self.table_refs.add(table_ref)
+ if self.config.lineage_parse_view_ddl and view.view_definition:
+ self.view_refs_by_project[project_id].add(table_ref)
+ self.view_definitions[table_ref] = view.view_definition
+
+ view.column_count = len(columns)
+ if not view.column_count:
+ logger.warning(
+ f"View doesn't have any column or unable to get columns for view: {table_identifier}"
+ )
+
+ yield from self.gen_view_dataset_workunits(
+ table=view,
+ columns=columns,
+ project_id=project_id,
+ dataset_name=dataset_name,
+ )
+
+ def _process_snapshot(
+ self,
+ snapshot: BigqueryTableSnapshot,
+ columns: List[BigqueryColumn],
+ project_id: str,
+ dataset_name: str,
+ ) -> Iterable[MetadataWorkUnit]:
+ table_identifier = BigqueryTableIdentifier(
+ project_id, dataset_name, snapshot.name
+ )
+
+ self.report.snapshots_scanned += 1
+
+ if not self.config.table_snapshot_pattern.allowed(
+ table_identifier.raw_table_name()
+ ):
+ self.report.report_dropped(table_identifier.raw_table_name())
+ return
+
+ snapshot.columns = columns
+ snapshot.column_count = len(columns)
+ if not snapshot.column_count:
+ logger.warning(
+ f"Snapshot doesn't have any column or unable to get columns for snapshot: {table_identifier}"
+ )
+
+ if self.store_table_refs:
+ table_ref = str(
+ BigQueryTableRef(table_identifier).get_sanitized_table_ref()
+ )
+ self.table_refs.add(table_ref)
+ if snapshot.base_table_identifier:
+ self.snapshot_refs_by_project[project_id].add(table_ref)
+ self.snapshots_by_ref[table_ref] = snapshot
+
+ yield from self.gen_snapshot_dataset_workunits(
+ table=snapshot,
+ columns=columns,
+ project_id=project_id,
+ dataset_name=dataset_name,
+ )
+
+ def gen_table_dataset_workunits(
+ self,
+ table: BigqueryTable,
+ columns: List[BigqueryColumn],
+ project_id: str,
+ dataset_name: str,
+ ) -> Iterable[MetadataWorkUnit]:
+ custom_properties: Dict[str, str] = {}
+ if table.expires:
+ custom_properties["expiration_date"] = str(table.expires)
+
+ if table.partition_info:
+ custom_properties["partition_info"] = str(table.partition_info)
+
+ if table.size_in_bytes:
+ custom_properties["size_in_bytes"] = str(table.size_in_bytes)
+
+ if table.active_billable_bytes:
+ custom_properties["billable_bytes_active"] = str(
+ table.active_billable_bytes
+ )
+
+ if table.long_term_billable_bytes:
+ custom_properties["billable_bytes_long_term"] = str(
+ table.long_term_billable_bytes
+ )
+
+ if table.max_partition_id:
+ custom_properties["number_of_partitions"] = str(table.num_partitions)
+ custom_properties["max_partition_id"] = str(table.max_partition_id)
+ custom_properties["is_partitioned"] = str(True)
+
+ sub_types: List[str] = [DatasetSubTypes.TABLE]
+ if table.max_shard_id:
+ custom_properties["max_shard_id"] = str(table.max_shard_id)
+ custom_properties["is_sharded"] = str(True)
+ sub_types = ["sharded table"] + sub_types
+
+ tags_to_add = None
+ if table.labels and self.config.capture_table_label_as_tag:
+ tags_to_add = []
+ tags_to_add.extend(
+ [
+ make_tag_urn(f"""{k}:{v}""")
+ for k, v in table.labels.items()
+ if is_tag_allowed(self.config.capture_table_label_as_tag, k)
+ ]
+ )
+
+ yield from self.gen_dataset_workunits(
+ table=table,
+ columns=columns,
+ project_id=project_id,
+ dataset_name=dataset_name,
+ sub_types=sub_types,
+ tags_to_add=tags_to_add,
+ custom_properties=custom_properties,
+ )
+
+ def gen_view_dataset_workunits(
+ self,
+ table: BigqueryView,
+ columns: List[BigqueryColumn],
+ project_id: str,
+ dataset_name: str,
+ ) -> Iterable[MetadataWorkUnit]:
+ tags_to_add = None
+ if table.labels and self.config.capture_view_label_as_tag:
+ tags_to_add = [
+ make_tag_urn(f"{k}:{v}")
+ for k, v in table.labels.items()
+ if is_tag_allowed(self.config.capture_view_label_as_tag, k)
+ ]
+ yield from self.gen_dataset_workunits(
+ table=table,
+ columns=columns,
+ project_id=project_id,
+ dataset_name=dataset_name,
+ tags_to_add=tags_to_add,
+ sub_types=[DatasetSubTypes.VIEW],
+ )
+
+ view = cast(BigqueryView, table)
+ view_definition_string = view.view_definition
+ view_properties_aspect = ViewProperties(
+ materialized=view.materialized,
+ viewLanguage="SQL",
+ viewLogic=view_definition_string or "",
+ )
+ yield MetadataChangeProposalWrapper(
+ entityUrn=self.gen_dataset_urn(project_id, dataset_name, table.name),
+ aspect=view_properties_aspect,
+ ).as_workunit()
+
+ def gen_snapshot_dataset_workunits(
+ self,
+ table: BigqueryTableSnapshot,
+ columns: List[BigqueryColumn],
+ project_id: str,
+ dataset_name: str,
+ ) -> Iterable[MetadataWorkUnit]:
+ custom_properties: Dict[str, str] = {}
+ if table.ddl:
+ custom_properties["snapshot_ddl"] = table.ddl
+ if table.snapshot_time:
+ custom_properties["snapshot_time"] = str(table.snapshot_time)
+ if table.size_in_bytes:
+ custom_properties["size_in_bytes"] = str(table.size_in_bytes)
+ if table.rows_count:
+ custom_properties["rows_count"] = str(table.rows_count)
+ yield from self.gen_dataset_workunits(
+ table=table,
+ columns=columns,
+ project_id=project_id,
+ dataset_name=dataset_name,
+ sub_types=[DatasetSubTypes.BIGQUERY_TABLE_SNAPSHOT],
+ custom_properties=custom_properties,
+ )
+
+ def gen_dataset_workunits(
+ self,
+ table: Union[BigqueryTable, BigqueryView, BigqueryTableSnapshot],
+ columns: List[BigqueryColumn],
+ project_id: str,
+ dataset_name: str,
+ sub_types: List[str],
+ tags_to_add: Optional[List[str]] = None,
+ custom_properties: Optional[Dict[str, str]] = None,
+ ) -> Iterable[MetadataWorkUnit]:
+ dataset_urn = self.gen_dataset_urn(project_id, dataset_name, table.name)
+
+ status = Status(removed=False)
+ yield MetadataChangeProposalWrapper(
+ entityUrn=dataset_urn, aspect=status
+ ).as_workunit()
+
+ datahub_dataset_name = BigqueryTableIdentifier(
+ project_id, dataset_name, table.name
+ )
+
+ yield self.gen_schema_metadata(
+ dataset_urn, table, columns, datahub_dataset_name
+ )
+
+ dataset_properties = DatasetProperties(
+ name=datahub_dataset_name.get_table_display_name(),
+ description=(
+ unquote_and_decode_unicode_escape_seq(table.comment)
+ if table.comment
+ else ""
+ ),
+ qualifiedName=str(datahub_dataset_name),
+ created=(
+ TimeStamp(time=int(table.created.timestamp() * 1000))
+ if table.created is not None
+ else None
+ ),
+ lastModified=(
+ TimeStamp(time=int(table.last_altered.timestamp() * 1000))
+ if table.last_altered is not None
+ else None
+ ),
+ externalUrl=(
+ BQ_EXTERNAL_TABLE_URL_TEMPLATE.format(
+ project=project_id, dataset=dataset_name, table=table.name
+ )
+ if self.config.include_external_url
+ else None
+ ),
+ )
+ if custom_properties:
+ dataset_properties.customProperties.update(custom_properties)
+
+ yield MetadataChangeProposalWrapper(
+ entityUrn=dataset_urn, aspect=dataset_properties
+ ).as_workunit()
+
+ if tags_to_add:
+ yield self.gen_tags_aspect_workunit(dataset_urn, tags_to_add)
+
+ yield from add_table_to_schema_container(
+ dataset_urn=dataset_urn,
+ parent_container_key=self.gen_dataset_key(project_id, dataset_name),
+ )
+ yield self.get_dataplatform_instance_aspect(
+ dataset_urn=dataset_urn, project_id=project_id
+ )
+
+ subTypes = SubTypes(typeNames=sub_types)
+ yield MetadataChangeProposalWrapper(
+ entityUrn=dataset_urn, aspect=subTypes
+ ).as_workunit()
+
+ if self.domain_registry:
+ yield from get_domain_wu(
+ dataset_name=str(datahub_dataset_name),
+ entity_urn=dataset_urn,
+ domain_registry=self.domain_registry,
+ domain_config=self.config.domain,
+ )
+
+ def gen_tags_aspect_workunit(
+ self, dataset_urn: str, tags_to_add: List[str]
+ ) -> MetadataWorkUnit:
+ tags = GlobalTagsClass(
+ tags=[TagAssociationClass(tag_to_add) for tag_to_add in tags_to_add]
+ )
+ return MetadataChangeProposalWrapper(
+ entityUrn=dataset_urn, aspect=tags
+ ).as_workunit()
+
+ def gen_schema_fields(self, columns: List[BigqueryColumn]) -> List[SchemaField]:
+ schema_fields: List[SchemaField] = []
+
+ # Below line affects HiveColumnToAvroConverter._STRUCT_TYPE_SEPARATOR in global scope
+ # TODO: Refractor this such that
+ # converter = HiveColumnToAvroConverter(struct_type_separator=" ");
+ # converter.get_schema_fields_for_hive_column(...)
+ original_struct_type_separator = (
+ HiveColumnToAvroConverter._STRUCT_TYPE_SEPARATOR
+ )
+ HiveColumnToAvroConverter._STRUCT_TYPE_SEPARATOR = " "
+ _COMPLEX_TYPE = re.compile("^(struct|array)")
+ last_id = -1
+ for col in columns:
+ # if col.data_type is empty that means this column is part of a complex type
+ if col.data_type is None or _COMPLEX_TYPE.match(col.data_type.lower()):
+ # If the we have seen the ordinal position that most probably means we already processed this complex type
+ if last_id != col.ordinal_position:
+ schema_fields.extend(
+ get_schema_fields_for_hive_column(
+ col.name, col.data_type.lower(), description=col.comment
+ )
+ )
+
+ # We have to add complex type comments to the correct level
+ if col.comment:
+ for idx, field in enumerate(schema_fields):
+ # Remove all the [version=2.0].[type=struct]. tags to get the field path
+ if (
+ re.sub(
+ r"\[.*?\]\.",
+ repl="",
+ string=field.fieldPath.lower(),
+ count=0,
+ flags=re.MULTILINE,
+ )
+ == col.field_path.lower()
+ ):
+ field.description = col.comment
+ schema_fields[idx] = field
+ break
+ else:
+ tags = []
+ if col.is_partition_column:
+ tags.append(
+ TagAssociationClass(make_tag_urn(Constants.TAG_PARTITION_KEY))
+ )
+
+ if col.cluster_column_position is not None:
+ tags.append(
+ TagAssociationClass(
+ make_tag_urn(
+ f"{CLUSTERING_COLUMN_TAG}_{col.cluster_column_position}"
+ )
+ )
+ )
+
+ if col.policy_tags:
+ for policy_tag in col.policy_tags:
+ tags.append(TagAssociationClass(make_tag_urn(policy_tag)))
+ field = SchemaField(
+ fieldPath=col.name,
+ type=SchemaFieldDataType(
+ self.BIGQUERY_FIELD_TYPE_MAPPINGS.get(col.data_type, NullType)()
+ ),
+ nativeDataType=col.data_type,
+ description=col.comment,
+ nullable=col.is_nullable,
+ globalTags=GlobalTagsClass(tags=tags),
+ )
+ schema_fields.append(field)
+ last_id = col.ordinal_position
+ HiveColumnToAvroConverter._STRUCT_TYPE_SEPARATOR = (
+ original_struct_type_separator
+ )
+ return schema_fields
+
+ def gen_schema_metadata(
+ self,
+ dataset_urn: str,
+ table: Union[BigqueryTable, BigqueryView, BigqueryTableSnapshot],
+ columns: List[BigqueryColumn],
+ dataset_name: BigqueryTableIdentifier,
+ ) -> MetadataWorkUnit:
+ schema_metadata = SchemaMetadata(
+ schemaName=str(dataset_name),
+ platform=make_data_platform_urn(self.platform),
+ version=0,
+ hash="",
+ platformSchema=MySqlDDL(tableSchema=""),
+ # fields=[],
+ fields=self.gen_schema_fields(columns),
+ )
+
+ if self.config.lineage_parse_view_ddl or self.config.lineage_use_sql_parser:
+ self.sql_parser_schema_resolver.add_schema_metadata(
+ dataset_urn, schema_metadata
+ )
+
+ return MetadataChangeProposalWrapper(
+ entityUrn=dataset_urn, aspect=schema_metadata
+ ).as_workunit()
+
+ def get_tables_for_dataset(
+ self,
+ project_id: str,
+ dataset_name: str,
+ ) -> Iterable[BigqueryTable]:
+ # In bigquery there is no way to query all tables in a Project id
+ with PerfTimer() as timer:
+ # Partitions view throw exception if we try to query partition info for too many tables
+ # so we have to limit the number of tables we query partition info.
+ # The conn.list_tables returns table infos that information_schema doesn't contain and this
+ # way we can merge that info with the queried one.
+ # https://cloud.google.com/bigquery/docs/information-schema-partitions
+ max_batch_size: int = (
+ self.config.number_of_datasets_process_in_batch
+ if not self.config.is_profiling_enabled()
+ else self.config.number_of_datasets_process_in_batch_if_profiling_enabled
+ )
+
+ # We get the list of tables in the dataset to get core table properties and to be able to process the tables in batches
+ # We collect only the latest shards from sharded tables (tables with _YYYYMMDD suffix) and ignore temporary tables
+ table_items = self.get_core_table_details(
+ dataset_name, project_id, self.config.temp_table_dataset_prefix
+ )
+
+ items_to_get: Dict[str, TableListItem] = {}
+ for table_item in table_items:
+ items_to_get[table_item] = table_items[table_item]
+ if len(items_to_get) % max_batch_size == 0:
+ yield from self.bigquery_data_dictionary.get_tables_for_dataset(
+ project_id,
+ dataset_name,
+ items_to_get,
+ with_data_read_permission=self.config.have_table_data_read_permission,
+ report=self.report,
+ )
+ items_to_get.clear()
+
+ if items_to_get:
+ yield from self.bigquery_data_dictionary.get_tables_for_dataset(
+ project_id,
+ dataset_name,
+ items_to_get,
+ with_data_read_permission=self.config.have_table_data_read_permission,
+ report=self.report,
+ )
+
+ self.report.metadata_extraction_sec[f"{project_id}.{dataset_name}"] = round(
+ timer.elapsed_seconds(), 2
+ )
+
+ def get_core_table_details(
+ self, dataset_name: str, project_id: str, temp_table_dataset_prefix: str
+ ) -> Dict[str, TableListItem]:
+ table_items: Dict[str, TableListItem] = {}
+ # Dict to store sharded table and the last seen max shard id
+ sharded_tables: Dict[str, TableListItem] = {}
+
+ for table in self.bigquery_data_dictionary.list_tables(
+ dataset_name, project_id
+ ):
+ table_identifier = BigqueryTableIdentifier(
+ project_id=project_id,
+ dataset=dataset_name,
+ table=table.table_id,
+ )
+
+ if table.table_type == "VIEW":
+ if (
+ not self.config.include_views
+ or not self.config.view_pattern.allowed(
+ table_identifier.raw_table_name()
+ )
+ ):
+ self.report.report_dropped(table_identifier.raw_table_name())
+ continue
+ else:
+ if not self.config.table_pattern.allowed(
+ table_identifier.raw_table_name()
+ ):
+ self.report.report_dropped(table_identifier.raw_table_name())
+ continue
+
+ _, shard = BigqueryTableIdentifier.get_table_and_shard(
+ table_identifier.table
+ )
+ table_name = table_identifier.get_table_name().split(".")[-1]
+
+ # Sharded tables look like: table_20220120
+ # For sharded tables we only process the latest shard and ignore the rest
+ # to find the latest shard we iterate over the list of tables and store the maximum shard id
+ # We only have one special case where the table name is a date `20220110`
+ # in this case we merge all these tables under dataset name as table name.
+ # For example some_dataset.20220110 will be turned to some_dataset.some_dataset
+ # It seems like there are some bigquery user who uses this non-standard way of sharding the tables.
+ if shard:
+ if table_name not in sharded_tables:
+ sharded_tables[table_name] = table
+ continue
+
+ stored_table_identifier = BigqueryTableIdentifier(
+ project_id=project_id,
+ dataset=dataset_name,
+ table=sharded_tables[table_name].table_id,
+ )
+ _, stored_shard = BigqueryTableIdentifier.get_table_and_shard(
+ stored_table_identifier.table
+ )
+ # When table is none, we use dataset_name as table_name
+ assert stored_shard
+ if stored_shard < shard:
+ sharded_tables[table_name] = table
+ continue
+ elif str(table_identifier).startswith(temp_table_dataset_prefix):
+ logger.debug(f"Dropping temporary table {table_identifier.table}")
+ self.report.report_dropped(table_identifier.raw_table_name())
+ continue
+
+ table_items[table.table_id] = table
+
+ # Adding maximum shards to the list of tables
+ table_items.update({value.table_id: value for value in sharded_tables.values()})
+
+ return table_items
diff --git a/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery_test_connection.py b/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery_test_connection.py
new file mode 100644
index 0000000000000..3aac78c154b2e
--- /dev/null
+++ b/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery_test_connection.py
@@ -0,0 +1,178 @@
+import logging
+from datetime import datetime, timedelta
+from typing import Dict, List, Union
+
+from google.cloud import bigquery
+
+from datahub.ingestion.api.source import (
+ CapabilityReport,
+ SourceCapability,
+ TestConnectionReport,
+)
+from datahub.ingestion.source.bigquery_v2.bigquery_config import BigQueryV2Config
+from datahub.ingestion.source.bigquery_v2.bigquery_report import BigQueryV2Report
+from datahub.ingestion.source.bigquery_v2.bigquery_schema import BigQuerySchemaApi
+from datahub.ingestion.source.bigquery_v2.lineage import BigqueryLineageExtractor
+from datahub.ingestion.source.bigquery_v2.usage import BigQueryUsageExtractor
+from datahub.sql_parsing.schema_resolver import SchemaResolver
+
+logger: logging.Logger = logging.getLogger(__name__)
+
+
+class BigQueryTestConnection:
+ @staticmethod
+ def test_connection(config_dict: dict) -> TestConnectionReport:
+ test_report = TestConnectionReport()
+ _report: Dict[Union[SourceCapability, str], CapabilityReport] = dict()
+
+ try:
+ connection_conf = BigQueryV2Config.parse_obj_allow_extras(config_dict)
+ client: bigquery.Client = connection_conf.get_bigquery_client()
+ assert client
+
+ test_report.basic_connectivity = BigQueryTestConnection.connectivity_test(
+ client
+ )
+
+ connection_conf.start_time = datetime.now()
+ connection_conf.end_time = datetime.now() + timedelta(minutes=1)
+
+ report: BigQueryV2Report = BigQueryV2Report()
+ project_ids: List[str] = []
+ projects = client.list_projects()
+
+ for project in projects:
+ if connection_conf.project_id_pattern.allowed(project.project_id):
+ project_ids.append(project.project_id)
+
+ metadata_read_capability = (
+ BigQueryTestConnection.metadata_read_capability_test(
+ project_ids, connection_conf
+ )
+ )
+ if SourceCapability.SCHEMA_METADATA not in _report:
+ _report[SourceCapability.SCHEMA_METADATA] = metadata_read_capability
+
+ if connection_conf.include_table_lineage:
+ lineage_capability = BigQueryTestConnection.lineage_capability_test(
+ connection_conf, project_ids, report
+ )
+ if SourceCapability.LINEAGE_COARSE not in _report:
+ _report[SourceCapability.LINEAGE_COARSE] = lineage_capability
+
+ if connection_conf.include_usage_statistics:
+ usage_capability = BigQueryTestConnection.usage_capability_test(
+ connection_conf, project_ids, report
+ )
+ if SourceCapability.USAGE_STATS not in _report:
+ _report[SourceCapability.USAGE_STATS] = usage_capability
+
+ test_report.capability_report = _report
+ return test_report
+
+ except Exception as e:
+ test_report.basic_connectivity = CapabilityReport(
+ capable=False, failure_reason=f"{e}"
+ )
+ return test_report
+
+ @staticmethod
+ def connectivity_test(client: bigquery.Client) -> CapabilityReport:
+ ret = client.query("select 1")
+ if ret.error_result:
+ return CapabilityReport(
+ capable=False, failure_reason=f"{ret.error_result['message']}"
+ )
+ else:
+ return CapabilityReport(capable=True)
+
+ @staticmethod
+ def metadata_read_capability_test(
+ project_ids: List[str], config: BigQueryV2Config
+ ) -> CapabilityReport:
+ for project_id in project_ids:
+ try:
+ logger.info(f"Metadata read capability test for project {project_id}")
+ client: bigquery.Client = config.get_bigquery_client()
+ assert client
+ bigquery_data_dictionary = BigQuerySchemaApi(
+ BigQueryV2Report().schema_api_perf, client
+ )
+ result = bigquery_data_dictionary.get_datasets_for_project_id(
+ project_id, 10
+ )
+ if len(result) == 0:
+ return CapabilityReport(
+ capable=False,
+ failure_reason=f"Dataset query returned empty dataset. It is either empty or no dataset in project {project_id}",
+ )
+ tables = bigquery_data_dictionary.get_tables_for_dataset(
+ project_id=project_id,
+ dataset_name=result[0].name,
+ tables={},
+ with_data_read_permission=config.have_table_data_read_permission,
+ report=BigQueryV2Report(),
+ )
+ if len(list(tables)) == 0:
+ return CapabilityReport(
+ capable=False,
+ failure_reason=f"Tables query did not return any table. It is either empty or no tables in project {project_id}.{result[0].name}",
+ )
+
+ except Exception as e:
+ return CapabilityReport(
+ capable=False,
+ failure_reason=f"Dataset query failed with error: {e}",
+ )
+
+ return CapabilityReport(capable=True)
+
+ @staticmethod
+ def lineage_capability_test(
+ connection_conf: BigQueryV2Config,
+ project_ids: List[str],
+ report: BigQueryV2Report,
+ ) -> CapabilityReport:
+ lineage_extractor = BigqueryLineageExtractor(
+ connection_conf, report, lambda ref: ""
+ )
+ for project_id in project_ids:
+ try:
+ logger.info(f"Lineage capability test for project {project_id}")
+ lineage_extractor.test_capability(project_id)
+ except Exception as e:
+ return CapabilityReport(
+ capable=False,
+ failure_reason=f"Lineage capability test failed with: {e}",
+ )
+
+ return CapabilityReport(capable=True)
+
+ @staticmethod
+ def usage_capability_test(
+ connection_conf: BigQueryV2Config,
+ project_ids: List[str],
+ report: BigQueryV2Report,
+ ) -> CapabilityReport:
+ usage_extractor = BigQueryUsageExtractor(
+ connection_conf,
+ report,
+ schema_resolver=SchemaResolver(platform="bigquery"),
+ dataset_urn_builder=lambda ref: "",
+ )
+ for project_id in project_ids:
+ try:
+ logger.info(f"Usage capability test for project {project_id}")
+ failures_before_test = len(report.failures)
+ usage_extractor.test_capability(project_id)
+ if failures_before_test != len(report.failures):
+ return CapabilityReport(
+ capable=False,
+ failure_reason="Usage capability test failed. Check the logs for further info",
+ )
+ except Exception as e:
+ return CapabilityReport(
+ capable=False,
+ failure_reason=f"Usage capability test failed with: {e} for project {project_id}",
+ )
+ return CapabilityReport(capable=True)
diff --git a/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/lineage.py b/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/lineage.py
index c41207ec67f62..496bd64d3b4fe 100644
--- a/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/lineage.py
+++ b/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/lineage.py
@@ -251,11 +251,6 @@ def get_time_window(self) -> Tuple[datetime, datetime]:
else:
return self.config.start_time, self.config.end_time
- def error(self, log: logging.Logger, key: str, reason: str) -> None:
- # TODO: Remove this method.
- # Note that this downgrades the error to a warning.
- self.report.warning(key, reason)
-
def _should_ingest_lineage(self) -> bool:
if (
self.redundant_run_skip_handler
@@ -265,9 +260,9 @@ def _should_ingest_lineage(self) -> bool:
)
):
# Skip this run
- self.report.report_warning(
- "lineage-extraction",
- "Skip this run as there was already a run for current ingestion window.",
+ self.report.warning(
+ title="Skipped redundant lineage extraction",
+ message="Skip this run as there was already a run for current ingestion window.",
)
return False
@@ -345,12 +340,12 @@ def generate_lineage(
events, sql_parser_schema_resolver
)
except Exception as e:
- if project_id:
- self.report.lineage_failed_extraction.append(project_id)
- self.error(
- logger,
- "lineage",
- f"{project_id}: {e}",
+ self.report.lineage_failed_extraction.append(project_id)
+ self.report.warning(
+ title="Failed to extract lineage",
+ message="Unexpected error encountered",
+ context=project_id,
+ exc=e,
)
lineage = {}
@@ -481,98 +476,88 @@ def lineage_via_catalog_lineage_api(
# Regions to search for BigQuery tables: projects/{project_id}/locations/{region}
enabled_regions: List[str] = ["US", "EU"]
- try:
- lineage_client: lineage_v1.LineageClient = lineage_v1.LineageClient()
+ lineage_client: lineage_v1.LineageClient = lineage_v1.LineageClient()
+
+ data_dictionary = BigQuerySchemaApi(
+ self.report.schema_api_perf, self.config.get_bigquery_client()
+ )
- data_dictionary = BigQuerySchemaApi(
- self.report.schema_api_perf, self.config.get_bigquery_client()
+ # Filtering datasets
+ datasets = list(data_dictionary.get_datasets_for_project_id(project_id))
+ project_tables = []
+ for dataset in datasets:
+ # Enables only tables where type is TABLE, VIEW or MATERIALIZED_VIEW (not EXTERNAL)
+ project_tables.extend(
+ [
+ table
+ for table in data_dictionary.list_tables(dataset.name, project_id)
+ if table.table_type in ["TABLE", "VIEW", "MATERIALIZED_VIEW"]
+ ]
)
- # Filtering datasets
- datasets = list(data_dictionary.get_datasets_for_project_id(project_id))
- project_tables = []
- for dataset in datasets:
- # Enables only tables where type is TABLE, VIEW or MATERIALIZED_VIEW (not EXTERNAL)
- project_tables.extend(
+ lineage_map: Dict[str, Set[LineageEdge]] = {}
+ curr_date = datetime.now()
+ for project_table in project_tables:
+ # Convert project table to .. format
+ table = f"{project_table.project}.{project_table.dataset_id}.{project_table.table_id}"
+
+ if not is_schema_allowed(
+ self.config.dataset_pattern,
+ schema_name=project_table.dataset_id,
+ db_name=project_table.project,
+ match_fully_qualified_schema_name=self.config.match_fully_qualified_names,
+ ) or not self.config.table_pattern.allowed(table):
+ self.report.num_skipped_lineage_entries_not_allowed[
+ project_table.project
+ ] += 1
+ continue
+
+ logger.info("Creating lineage map for table %s", table)
+ upstreams = set()
+ downstream_table = lineage_v1.EntityReference()
+ # fully_qualified_name in format: "bigquery:.."
+ downstream_table.fully_qualified_name = f"bigquery:{table}"
+ # Searches in different regions
+ for region in enabled_regions:
+ location_request = lineage_v1.SearchLinksRequest(
+ target=downstream_table,
+ parent=f"projects/{project_id}/locations/{region.lower()}",
+ )
+ response = lineage_client.search_links(request=location_request)
+ upstreams.update(
[
- table
- for table in data_dictionary.list_tables(
- dataset.name, project_id
+ str(lineage.source.fully_qualified_name).replace(
+ "bigquery:", ""
)
- if table.table_type in ["TABLE", "VIEW", "MATERIALIZED_VIEW"]
+ for lineage in response
]
)
- lineage_map: Dict[str, Set[LineageEdge]] = {}
- curr_date = datetime.now()
- for project_table in project_tables:
- # Convert project table to .. format
- table = f"{project_table.project}.{project_table.dataset_id}.{project_table.table_id}"
-
- if not is_schema_allowed(
- self.config.dataset_pattern,
- schema_name=project_table.dataset_id,
- db_name=project_table.project,
- match_fully_qualified_schema_name=self.config.match_fully_qualified_names,
- ) or not self.config.table_pattern.allowed(table):
- self.report.num_skipped_lineage_entries_not_allowed[
- project_table.project
- ] += 1
- continue
-
- logger.info("Creating lineage map for table %s", table)
- upstreams = set()
- downstream_table = lineage_v1.EntityReference()
- # fully_qualified_name in format: "bigquery:.."
- downstream_table.fully_qualified_name = f"bigquery:{table}"
- # Searches in different regions
- for region in enabled_regions:
- location_request = lineage_v1.SearchLinksRequest(
- target=downstream_table,
- parent=f"projects/{project_id}/locations/{region.lower()}",
- )
- response = lineage_client.search_links(request=location_request)
- upstreams.update(
- [
- str(lineage.source.fully_qualified_name).replace(
- "bigquery:", ""
- )
- for lineage in response
- ]
- )
-
- # Downstream table identifier
- destination_table_str = str(
- BigQueryTableRef(
- table_identifier=BigqueryTableIdentifier(*table.split("."))
- )
+ # Downstream table identifier
+ destination_table_str = str(
+ BigQueryTableRef(
+ table_identifier=BigqueryTableIdentifier(*table.split("."))
)
+ )
- # Only builds lineage map when the table has upstreams
- logger.debug("Found %d upstreams for table %s", len(upstreams), table)
- if upstreams:
- lineage_map[destination_table_str] = {
- LineageEdge(
- table=str(
- BigQueryTableRef(
- table_identifier=BigqueryTableIdentifier.from_string_name(
- source_table
- )
+ # Only builds lineage map when the table has upstreams
+ logger.debug("Found %d upstreams for table %s", len(upstreams), table)
+ if upstreams:
+ lineage_map[destination_table_str] = {
+ LineageEdge(
+ table=str(
+ BigQueryTableRef(
+ table_identifier=BigqueryTableIdentifier.from_string_name(
+ source_table
)
- ),
- column_mapping=frozenset(),
- auditStamp=curr_date,
- )
- for source_table in upstreams
- }
- return lineage_map
- except Exception as e:
- self.error(
- logger,
- "lineage-exported-catalog-lineage-api",
- f"Error: {e}",
- )
- raise e
+ )
+ ),
+ column_mapping=frozenset(),
+ auditStamp=curr_date,
+ )
+ for source_table in upstreams
+ }
+ return lineage_map
def _get_parsed_audit_log_events(self, project_id: str) -> Iterable[QueryEvent]:
# We adjust the filter values a bit, since we need to make sure that the join
diff --git a/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/profiler.py b/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/profiler.py
index 8c393d1e8a436..582c312f99098 100644
--- a/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/profiler.py
+++ b/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/profiler.py
@@ -227,8 +227,9 @@ def get_profile_request(
if partition is None and bq_table.partition_info:
self.report.report_warning(
- "profile skipped as partitioned table is empty or partition id or type was invalid",
- profile_request.pretty_name,
+ title="Profile skipped for partitioned table",
+ message="profile skipped as partitioned table is empty or partition id or type was invalid",
+ context=profile_request.pretty_name,
)
return None
if (
diff --git a/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/usage.py b/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/usage.py
index 1b95cbf505016..6824d630a2277 100644
--- a/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/usage.py
+++ b/metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/usage.py
@@ -358,9 +358,9 @@ def _should_ingest_usage(self) -> bool:
)
):
# Skip this run
- self.report.report_warning(
- "usage-extraction",
- "Skip this run as there was already a run for current ingestion window.",
+ self.report.warning(
+ title="Skipped redundant usage extraction",
+ message="Skip this run as there was already a run for current ingestion window.",
)
return False
@@ -410,8 +410,7 @@ def _get_workunits_internal(
)
usage_state.report_disk_usage(self.report)
except Exception as e:
- logger.error("Error processing usage", exc_info=True)
- self.report.report_warning("usage-ingestion", str(e))
+ self.report.warning(message="Error processing usage", exc=e)
self.report_status("usage-ingestion", False)
def generate_read_events_from_query(
@@ -477,10 +476,12 @@ def _ingest_events(
)
except Exception as e:
- logger.warning(
- f"Unable to store usage event {audit_event}", exc_info=True
+ self.report.warning(
+ message="Unable to store usage event",
+ context=f"{audit_event}",
+ exc=e,
)
- self._report_error("store-event", e)
+
logger.info(f"Total number of events aggregated = {num_aggregated}.")
if self.report.num_view_query_events > 0:
@@ -500,11 +501,11 @@ def _generate_operational_workunits(
yield operational_wu
self.report.num_operational_stats_workunits_emitted += 1
except Exception as e:
- logger.warning(
- f"Unable to generate operation workunit for event {audit_event}",
- exc_info=True,
+ self.report.warning(
+ message="Unable to generate operation workunit",
+ context=f"{audit_event}",
+ exc=e,
)
- self._report_error("operation-workunit", e)
def _generate_usage_workunits(
self, usage_state: BigQueryUsageState
@@ -541,11 +542,11 @@ def _generate_usage_workunits(
)
self.report.num_usage_workunits_emitted += 1
except Exception as e:
- logger.warning(
- f"Unable to generate usage workunit for bucket {entry.timestamp}, {entry.resource}",
- exc_info=True,
+ self.report.warning(
+ message="Unable to generate usage statistics workunit",
+ context=f"{entry.timestamp}, {entry.resource}",
+ exc=e,
)
- self._report_error("statistics-workunit", e)
def _get_usage_events(self, projects: Iterable[str]) -> Iterable[AuditEvent]:
if self.config.use_exported_bigquery_audit_metadata:
@@ -559,12 +560,12 @@ def _get_usage_events(self, projects: Iterable[str]) -> Iterable[AuditEvent]:
)
yield from self._get_parsed_bigquery_log_events(project_id)
except Exception as e:
- logger.error(
- f"Error getting usage events for project {project_id}",
- exc_info=True,
- )
self.report.usage_failed_extraction.append(project_id)
- self.report.report_warning(f"usage-extraction-{project_id}", str(e))
+ self.report.warning(
+ message="Failed to get some or all usage events for project",
+ context=project_id,
+ exc=e,
+ )
self.report_status(f"usage-extraction-{project_id}", False)
self.report.usage_extraction_sec[project_id] = round(
@@ -898,12 +899,10 @@ def _get_parsed_bigquery_log_events(
self.report.num_usage_parsed_log_entries[project_id] += 1
yield event
except Exception as e:
- logger.warning(
- f"Unable to parse log entry `{entry}` for project {project_id}",
- exc_info=True,
- )
- self._report_error(
- f"log-parse-{project_id}", e, group="usage-log-parse"
+ self.report.warning(
+ message="Unable to parse usage log entry",
+ context=f"`{entry}` for project {project_id}",
+ exc=e,
)
def _generate_filter(self, corrected_start_time, corrected_end_time):
@@ -946,13 +945,6 @@ def get_tables_from_query(
return parsed_table_refs
- def _report_error(
- self, label: str, e: Exception, group: Optional[str] = None
- ) -> None:
- """Report an error that does not constitute a major failure."""
- self.report.usage_error_count[label] += 1
- self.report.report_warning(group or f"usage-{label}", str(e))
-
def test_capability(self, project_id: str) -> None:
for entry in self._get_parsed_bigquery_log_events(project_id, limit=1):
logger.debug(f"Connection test got one {entry}")
diff --git a/metadata-ingestion/src/datahub/ingestion/source/snowflake/snowflake_schema_gen.py b/metadata-ingestion/src/datahub/ingestion/source/snowflake/snowflake_schema_gen.py
index dcc18635de32c..72f8f8ad793fd 100644
--- a/metadata-ingestion/src/datahub/ingestion/source/snowflake/snowflake_schema_gen.py
+++ b/metadata-ingestion/src/datahub/ingestion/source/snowflake/snowflake_schema_gen.py
@@ -1,7 +1,5 @@
-import concurrent.futures
import itertools
import logging
-import queue
from typing import Callable, Dict, Iterable, List, Optional, Union
from datahub.configuration.pattern_utils import is_schema_allowed
@@ -101,6 +99,7 @@
from datahub.metadata.com.linkedin.pegasus2avro.tag import TagProperties
from datahub.sql_parsing.sql_parsing_aggregator import SqlParsingAggregator
from datahub.utilities.registries.domain_registry import DomainRegistry
+from datahub.utilities.threaded_iterator_executor import ThreadedIteratorExecutor
logger = logging.getLogger(__name__)
@@ -318,41 +317,22 @@ def _process_db_schemas(
snowflake_db: SnowflakeDatabase,
db_tables: Dict[str, List[SnowflakeTable]],
) -> Iterable[MetadataWorkUnit]:
- q: "queue.Queue[MetadataWorkUnit]" = queue.Queue(maxsize=100)
-
- def _process_schema_worker(snowflake_schema: SnowflakeSchema) -> None:
+ def _process_schema_worker(
+ snowflake_schema: SnowflakeSchema,
+ ) -> Iterable[MetadataWorkUnit]:
for wu in self._process_schema(
snowflake_schema, snowflake_db.name, db_tables
):
- q.put(wu)
-
- with concurrent.futures.ThreadPoolExecutor(
- max_workers=SCHEMA_PARALLELISM
- ) as executor:
- futures = []
- for snowflake_schema in snowflake_db.schemas:
- f = executor.submit(_process_schema_worker, snowflake_schema)
- futures.append(f)
-
- # Read from the queue and yield the work units until all futures are done.
- while True:
- if not q.empty():
- while not q.empty():
- yield q.get_nowait()
- else:
- try:
- yield q.get(timeout=0.2)
- except queue.Empty:
- pass
-
- # Filter out the done futures.
- futures = [f for f in futures if not f.done()]
- if not futures:
- break
-
- # Yield the remaining work units. This theoretically should not happen, but adding it just in case.
- while not q.empty():
- yield q.get_nowait()
+ yield wu
+
+ for wu in ThreadedIteratorExecutor.process(
+ worker_func=_process_schema_worker,
+ args_list=[
+ (snowflake_schema,) for snowflake_schema in snowflake_db.schemas
+ ],
+ max_workers=SCHEMA_PARALLELISM,
+ ):
+ yield wu
def fetch_schemas_for_database(
self, snowflake_db: SnowflakeDatabase, db_name: str
diff --git a/metadata-ingestion/src/datahub/utilities/threaded_iterator_executor.py b/metadata-ingestion/src/datahub/utilities/threaded_iterator_executor.py
new file mode 100644
index 0000000000000..216fa155035d3
--- /dev/null
+++ b/metadata-ingestion/src/datahub/utilities/threaded_iterator_executor.py
@@ -0,0 +1,52 @@
+import concurrent.futures
+import contextlib
+import queue
+from typing import Any, Callable, Generator, Iterable, Tuple, TypeVar
+
+T = TypeVar("T")
+
+
+class ThreadedIteratorExecutor:
+ """
+ Executes worker functions of type `Callable[..., Iterable[T]]` in parallel threads,
+ yielding items of type `T` as they become available.
+ """
+
+ @classmethod
+ def process(
+ cls,
+ worker_func: Callable[..., Iterable[T]],
+ args_list: Iterable[Tuple[Any, ...]],
+ max_workers: int,
+ ) -> Generator[T, None, None]:
+
+ out_q: queue.Queue[T] = queue.Queue()
+
+ def _worker_wrapper(
+ worker_func: Callable[..., Iterable[T]], *args: Any
+ ) -> None:
+ for item in worker_func(*args):
+ out_q.put(item)
+
+ with concurrent.futures.ThreadPoolExecutor(max_workers=max_workers) as executor:
+ futures = []
+ for args in args_list:
+ future = executor.submit(_worker_wrapper, worker_func, *args)
+ futures.append(future)
+ # Read from the queue and yield the work units until all futures are done.
+ while True:
+ if not out_q.empty():
+ while not out_q.empty():
+ yield out_q.get_nowait()
+ else:
+ with contextlib.suppress(queue.Empty):
+ yield out_q.get(timeout=0.2)
+
+ # Filter out the done futures.
+ futures = [f for f in futures if not f.done()]
+ if not futures:
+ break
+
+ # Yield the remaining work units. This theoretically should not happen, but adding it just in case.
+ while not out_q.empty():
+ yield out_q.get_nowait()
diff --git a/metadata-ingestion/tests/integration/bigquery_v2/test_bigquery.py b/metadata-ingestion/tests/integration/bigquery_v2/test_bigquery.py
index a24b6174eb925..762c73d2a55c6 100644
--- a/metadata-ingestion/tests/integration/bigquery_v2/test_bigquery.py
+++ b/metadata-ingestion/tests/integration/bigquery_v2/test_bigquery.py
@@ -11,7 +11,6 @@
DynamicTypedClassifierConfig,
)
from datahub.ingestion.glossary.datahub_classifier import DataHubClassifierConfig
-from datahub.ingestion.source.bigquery_v2.bigquery import BigqueryV2Source
from datahub.ingestion.source.bigquery_v2.bigquery_data_reader import BigQueryDataReader
from datahub.ingestion.source.bigquery_v2.bigquery_schema import (
BigqueryColumn,
@@ -19,6 +18,9 @@
BigQuerySchemaApi,
BigqueryTable,
)
+from datahub.ingestion.source.bigquery_v2.bigquery_schema_gen import (
+ BigQuerySchemaGenerator,
+)
from tests.test_helpers import mce_helpers
from tests.test_helpers.state_helpers import run_and_get_pipeline
@@ -39,7 +41,7 @@ def random_email():
@freeze_time(FROZEN_TIME)
@patch.object(BigQuerySchemaApi, "get_tables_for_dataset")
-@patch.object(BigqueryV2Source, "get_core_table_details")
+@patch.object(BigQuerySchemaGenerator, "get_core_table_details")
@patch.object(BigQuerySchemaApi, "get_datasets_for_project_id")
@patch.object(BigQuerySchemaApi, "get_columns_for_dataset")
@patch.object(BigQueryDataReader, "get_sample_data_for_table")
diff --git a/metadata-ingestion/tests/unit/test_bigquery_source.py b/metadata-ingestion/tests/unit/test_bigquery_source.py
index b58f35c0deef5..ea32db0ef2757 100644
--- a/metadata-ingestion/tests/unit/test_bigquery_source.py
+++ b/metadata-ingestion/tests/unit/test_bigquery_source.py
@@ -32,6 +32,9 @@
BigqueryTableSnapshot,
BigqueryView,
)
+from datahub.ingestion.source.bigquery_v2.bigquery_schema_gen import (
+ BigQuerySchemaGenerator,
+)
from datahub.ingestion.source.bigquery_v2.lineage import (
LineageEdge,
LineageEdgeColumnMapping,
@@ -231,8 +234,9 @@ def test_get_dataplatform_instance_aspect_returns_project_id(get_bq_client_mock)
config = BigQueryV2Config.parse_obj({"include_data_platform_instance": True})
source = BigqueryV2Source(config=config, ctx=PipelineContext(run_id="test"))
+ schema_gen = source.bq_schema_extractor
- data_platform_instance = source.get_dataplatform_instance_aspect(
+ data_platform_instance = schema_gen.get_dataplatform_instance_aspect(
"urn:li:test", project_id
)
metadata = data_platform_instance.metadata
@@ -246,8 +250,9 @@ def test_get_dataplatform_instance_aspect_returns_project_id(get_bq_client_mock)
def test_get_dataplatform_instance_default_no_instance(get_bq_client_mock):
config = BigQueryV2Config.parse_obj({})
source = BigqueryV2Source(config=config, ctx=PipelineContext(run_id="test"))
+ schema_gen = source.bq_schema_extractor
- data_platform_instance = source.get_dataplatform_instance_aspect(
+ data_platform_instance = schema_gen.get_dataplatform_instance_aspect(
"urn:li:test", "project_id"
)
metadata = data_platform_instance.metadata
@@ -395,8 +400,9 @@ def test_gen_table_dataset_workunits(get_bq_client_mock, bigquery_table):
source: BigqueryV2Source = BigqueryV2Source(
config=config, ctx=PipelineContext(run_id="test")
)
+ schema_gen = source.bq_schema_extractor
- gen = source.gen_table_dataset_workunits(
+ gen = schema_gen.gen_table_dataset_workunits(
bigquery_table, [], project_id, dataset_name
)
mcp = cast(MetadataChangeProposalClass, next(iter(gen)).metadata)
@@ -710,9 +716,10 @@ def test_table_processing_logic(get_bq_client_mock, data_dictionary_mock):
data_dictionary_mock.get_tables_for_dataset.return_value = None
source = BigqueryV2Source(config=config, ctx=PipelineContext(run_id="test"))
+ schema_gen = source.bq_schema_extractor
_ = list(
- source.get_tables_for_dataset(
+ schema_gen.get_tables_for_dataset(
project_id="test-project", dataset_name="test-dataset"
)
)
@@ -784,9 +791,10 @@ def test_table_processing_logic_date_named_tables(
data_dictionary_mock.get_tables_for_dataset.return_value = None
source = BigqueryV2Source(config=config, ctx=PipelineContext(run_id="test"))
+ schema_gen = source.bq_schema_extractor
_ = list(
- source.get_tables_for_dataset(
+ schema_gen.get_tables_for_dataset(
project_id="test-project", dataset_name="test-dataset"
)
)
@@ -882,7 +890,9 @@ def test_get_views_for_dataset(
assert list(views) == [bigquery_view_1, bigquery_view_2]
-@patch.object(BigqueryV2Source, "gen_dataset_workunits", lambda *args, **kwargs: [])
+@patch.object(
+ BigQuerySchemaGenerator, "gen_dataset_workunits", lambda *args, **kwargs: []
+)
@patch.object(BigQueryV2Config, "get_bigquery_client")
def test_gen_view_dataset_workunits(
get_bq_client_mock, bigquery_view_1, bigquery_view_2
@@ -897,8 +907,9 @@ def test_gen_view_dataset_workunits(
source: BigqueryV2Source = BigqueryV2Source(
config=config, ctx=PipelineContext(run_id="test")
)
+ schema_gen = source.bq_schema_extractor
- gen = source.gen_view_dataset_workunits(
+ gen = schema_gen.gen_view_dataset_workunits(
bigquery_view_1, [], project_id, dataset_name
)
mcp = cast(MetadataChangeProposalClass, next(iter(gen)).metadata)
@@ -908,7 +919,7 @@ def test_gen_view_dataset_workunits(
viewLogic=bigquery_view_1.view_definition,
)
- gen = source.gen_view_dataset_workunits(
+ gen = schema_gen.gen_view_dataset_workunits(
bigquery_view_2, [], project_id, dataset_name
)
mcp = cast(MetadataChangeProposalClass, next(iter(gen)).metadata)
@@ -990,8 +1001,9 @@ def test_gen_snapshot_dataset_workunits(get_bq_client_mock, bigquery_snapshot):
source: BigqueryV2Source = BigqueryV2Source(
config=config, ctx=PipelineContext(run_id="test")
)
+ schema_gen = source.bq_schema_extractor
- gen = source.gen_snapshot_dataset_workunits(
+ gen = schema_gen.gen_snapshot_dataset_workunits(
bigquery_snapshot, [], project_id, dataset_name
)
mcp = cast(MetadataChangeProposalWrapper, list(gen)[2].metadata)
diff --git a/metadata-ingestion/tests/unit/utilities/test_threaded_iterator_executor.py b/metadata-ingestion/tests/unit/utilities/test_threaded_iterator_executor.py
new file mode 100644
index 0000000000000..35c44c7b4a847
--- /dev/null
+++ b/metadata-ingestion/tests/unit/utilities/test_threaded_iterator_executor.py
@@ -0,0 +1,14 @@
+from datahub.utilities.threaded_iterator_executor import ThreadedIteratorExecutor
+
+
+def test_threaded_iterator_executor():
+ def table_of(i):
+ for j in range(1, 11):
+ yield f"{i}x{j}={i*j}"
+
+ assert {
+ res
+ for res in ThreadedIteratorExecutor.process(
+ table_of, [(i,) for i in range(1, 30)], max_workers=2
+ )
+ } == {x for i in range(1, 30) for x in table_of(i)}
From bb24651264e3076115b1223637e9284f575d1d70 Mon Sep 17 00:00:00 2001
From: Harshal Sheth
Date: Tue, 16 Jul 2024 12:27:37 -0700
Subject: [PATCH 07/23] fix(airflow): add error handling around
render_template() (#10907)
---
.../src/datahub_airflow_plugin/datahub_listener.py | 9 +++++++--
1 file changed, 7 insertions(+), 2 deletions(-)
diff --git a/metadata-ingestion-modules/airflow-plugin/src/datahub_airflow_plugin/datahub_listener.py b/metadata-ingestion-modules/airflow-plugin/src/datahub_airflow_plugin/datahub_listener.py
index 6ef4f831522cb..c87f7f8fb1a8e 100644
--- a/metadata-ingestion-modules/airflow-plugin/src/datahub_airflow_plugin/datahub_listener.py
+++ b/metadata-ingestion-modules/airflow-plugin/src/datahub_airflow_plugin/datahub_listener.py
@@ -362,8 +362,13 @@ def on_task_instance_running(
# Render templates in a copy of the task instance.
# This is necessary to get the correct operator args in the extractors.
- task_instance = copy.deepcopy(task_instance)
- task_instance.render_templates()
+ try:
+ task_instance = copy.deepcopy(task_instance)
+ task_instance.render_templates()
+ except Exception as e:
+ logger.info(
+ f"Error rendering templates in DataHub listener. Jinja-templated variables will not be extracted correctly: {e}"
+ )
# The type ignore is to placate mypy on Airflow 2.1.x.
dagrun: "DagRun" = task_instance.dag_run # type: ignore[attr-defined]
From a8b07c5fe6dc55eebf44e63b35cd957709c56a26 Mon Sep 17 00:00:00 2001
From: Nadav Gross <33874964+nadavgross@users.noreply.github.com>
Date: Tue, 16 Jul 2024 22:28:14 +0300
Subject: [PATCH 08/23] feat(ingestion/sqlglot): add optional `default_dialect`
parameter to sqlglot lineage (#10830)
---
.../src/datahub/ingestion/graph/client.py | 2 ++
.../src/datahub/sql_parsing/sqlglot_lineage.py | 16 +++++++++++++---
2 files changed, 15 insertions(+), 3 deletions(-)
diff --git a/metadata-ingestion/src/datahub/ingestion/graph/client.py b/metadata-ingestion/src/datahub/ingestion/graph/client.py
index 7ba412b3e772c..1d6097da231f8 100644
--- a/metadata-ingestion/src/datahub/ingestion/graph/client.py
+++ b/metadata-ingestion/src/datahub/ingestion/graph/client.py
@@ -1241,6 +1241,7 @@ def parse_sql_lineage(
env: str = DEFAULT_ENV,
default_db: Optional[str] = None,
default_schema: Optional[str] = None,
+ default_dialect: Optional[str] = None,
) -> "SqlParsingResult":
from datahub.sql_parsing.sqlglot_lineage import sqlglot_lineage
@@ -1254,6 +1255,7 @@ def parse_sql_lineage(
schema_resolver=schema_resolver,
default_db=default_db,
default_schema=default_schema,
+ default_dialect=default_dialect,
)
def create_tag(self, tag_name: str) -> str:
diff --git a/metadata-ingestion/src/datahub/sql_parsing/sqlglot_lineage.py b/metadata-ingestion/src/datahub/sql_parsing/sqlglot_lineage.py
index 9c2a588a577cc..976ff8bcc9b3f 100644
--- a/metadata-ingestion/src/datahub/sql_parsing/sqlglot_lineage.py
+++ b/metadata-ingestion/src/datahub/sql_parsing/sqlglot_lineage.py
@@ -843,8 +843,14 @@ def _sqlglot_lineage_inner(
schema_resolver: SchemaResolverInterface,
default_db: Optional[str] = None,
default_schema: Optional[str] = None,
+ default_dialect: Optional[str] = None,
) -> SqlParsingResult:
- dialect = get_dialect(schema_resolver.platform)
+
+ if not default_dialect:
+ dialect = get_dialect(schema_resolver.platform)
+ else:
+ dialect = get_dialect(default_dialect)
+
if is_dialect_instance(dialect, "snowflake"):
# in snowflake, table identifiers must be uppercased to match sqlglot's behavior.
if default_db:
@@ -1003,6 +1009,7 @@ def sqlglot_lineage(
schema_resolver: SchemaResolverInterface,
default_db: Optional[str] = None,
default_schema: Optional[str] = None,
+ default_dialect: Optional[str] = None,
) -> SqlParsingResult:
"""Parse a SQL statement and generate lineage information.
@@ -1020,8 +1027,9 @@ def sqlglot_lineage(
can be brittle with respect to missing schema information and complex
SQL logic like UNNESTs.
- The SQL dialect is inferred from the schema_resolver's platform. The
- set of supported dialects is the same as sqlglot's. See their
+ The SQL dialect can be given as an argument called default_dialect or it can
+ be inferred from the schema_resolver's platform.
+ The set of supported dialects is the same as sqlglot's. See their
`documentation `_
for the full list.
@@ -1035,6 +1043,7 @@ def sqlglot_lineage(
schema_resolver: The schema resolver to use for resolving table schemas.
default_db: The default database to use for unqualified table names.
default_schema: The default schema to use for unqualified table names.
+ default_dialect: A default dialect to override the dialect provided by 'schema_resolver'.
Returns:
A SqlParsingResult object containing the parsed lineage information.
@@ -1059,6 +1068,7 @@ def sqlglot_lineage(
schema_resolver=schema_resolver,
default_db=default_db,
default_schema=default_schema,
+ default_dialect=default_dialect,
)
except Exception as e:
return SqlParsingResult.make_from_error(e)
From 1565fb01028efaaff5bfdef7e429f63eb0502b2d Mon Sep 17 00:00:00 2001
From: david-leifker <114954101+david-leifker@users.noreply.github.com>
Date: Tue, 16 Jul 2024 16:56:51 -0500
Subject: [PATCH 09/23] feat(mcp-mutator): new mcp mutator plugin (#10904)
---
.../linkedin/metadata/aspect/ReadItem.java | 6 +-
.../metadata/aspect/batch/AspectsBatch.java | 7 +
.../metadata/aspect/plugins/PluginSpec.java | 20 +-
.../aspect/plugins/hooks/MCLSideEffect.java | 2 +-
.../aspect/plugins/hooks/MCPSideEffect.java | 4 +-
.../aspect/plugins/hooks/MutationHook.java | 26 +-
.../validation/AspectPayloadValidator.java | 4 +-
metadata-io/build.gradle | 1 +
metadata-io/metadata-io-api/build.gradle | 7 +
.../entity/ebean/batch/AspectsBatchImpl.java | 26 +-
.../entity/ebean/batch/ProposedItem.java | 80 +++++
.../ebean/batch/AspectsBatchImplTest.java | 320 ++++++++++++++++++
.../test/resources/AspectsBatchImplTest.yaml | 19 ++
.../aspect/hooks/IgnoreUnknownMutator.java | 80 +++++
.../hooks/IgnoreUnknownMutatorTest.java | 143 ++++++++
.../kafka/MaeConsumerApplication.java | 1 +
.../MCLSpringCommonTestConfiguration.java | 3 +
.../kafka/MceConsumerApplication.java | 3 +-
.../src/main/resources/entity-registry.yml | 6 +
.../metadata/context/RequestContext.java | 1 +
.../src/main/resources/application.yaml | 2 +
.../ConfigEntityRegistryFactory.java | 5 +-
.../SpringStandardPluginConfiguration.java | 33 ++
.../metadata/aspect/SpringPluginFactory.java | 12 +-
.../linkedin/gms/CommonApplicationConfig.java | 1 +
25 files changed, 786 insertions(+), 26 deletions(-)
create mode 100644 metadata-io/metadata-io-api/src/main/java/com/linkedin/metadata/entity/ebean/batch/ProposedItem.java
create mode 100644 metadata-io/metadata-io-api/src/test/java/com/linkedin/metadata/entity/ebean/batch/AspectsBatchImplTest.java
create mode 100644 metadata-io/metadata-io-api/src/test/resources/AspectsBatchImplTest.yaml
create mode 100644 metadata-io/src/main/java/com/linkedin/metadata/aspect/hooks/IgnoreUnknownMutator.java
create mode 100644 metadata-io/src/test/java/com/linkedin/metadata/aspect/hooks/IgnoreUnknownMutatorTest.java
create mode 100644 metadata-service/factories/src/main/java/com/linkedin/gms/factory/plugins/SpringStandardPluginConfiguration.java
diff --git a/entity-registry/src/main/java/com/linkedin/metadata/aspect/ReadItem.java b/entity-registry/src/main/java/com/linkedin/metadata/aspect/ReadItem.java
index 342b5376d8a75..106596bf80ccf 100644
--- a/entity-registry/src/main/java/com/linkedin/metadata/aspect/ReadItem.java
+++ b/entity-registry/src/main/java/com/linkedin/metadata/aspect/ReadItem.java
@@ -5,6 +5,7 @@
import com.linkedin.data.template.RecordTemplate;
import com.linkedin.metadata.models.AspectSpec;
import com.linkedin.metadata.models.EntitySpec;
+import com.linkedin.mxe.GenericAspect;
import com.linkedin.mxe.SystemMetadata;
import java.lang.reflect.InvocationTargetException;
import javax.annotation.Nonnull;
@@ -26,6 +27,9 @@ public interface ReadItem {
*/
@Nonnull
default String getAspectName() {
+ if (getAspectSpec() == null) {
+ return GenericAspect.dataSchema().getName();
+ }
return getAspectSpec().getName();
}
@@ -72,6 +76,6 @@ static T getAspect(Class clazz, @Nullable RecordTemplate recordTemplate)
*
* @return aspect's specification
*/
- @Nonnull
+ @Nullable
AspectSpec getAspectSpec();
}
diff --git a/entity-registry/src/main/java/com/linkedin/metadata/aspect/batch/AspectsBatch.java b/entity-registry/src/main/java/com/linkedin/metadata/aspect/batch/AspectsBatch.java
index a302632e1936f..77820948b00cb 100644
--- a/entity-registry/src/main/java/com/linkedin/metadata/aspect/batch/AspectsBatch.java
+++ b/entity-registry/src/main/java/com/linkedin/metadata/aspect/batch/AspectsBatch.java
@@ -84,6 +84,13 @@ static void applyWriteMutationHooks(
}
}
+ default Stream applyProposalMutationHooks(
+ Collection proposedItems, @Nonnull RetrieverContext retrieverContext) {
+ return retrieverContext.getAspectRetriever().getEntityRegistry().getAllMutationHooks().stream()
+ .flatMap(
+ mutationHook -> mutationHook.applyProposalMutation(proposedItems, retrieverContext));
+ }
+
default ValidationExceptionCollection validateProposed(
Collection mcpItems) {
return validateProposed(mcpItems, getRetrieverContext());
diff --git a/entity-registry/src/main/java/com/linkedin/metadata/aspect/plugins/PluginSpec.java b/entity-registry/src/main/java/com/linkedin/metadata/aspect/plugins/PluginSpec.java
index 1adb1be81ecc1..f99dd18d3c9c1 100644
--- a/entity-registry/src/main/java/com/linkedin/metadata/aspect/plugins/PluginSpec.java
+++ b/entity-registry/src/main/java/com/linkedin/metadata/aspect/plugins/PluginSpec.java
@@ -3,7 +3,6 @@
import com.linkedin.common.urn.Urn;
import com.linkedin.events.metadata.ChangeType;
import com.linkedin.metadata.aspect.plugins.config.AspectPluginConfig;
-import com.linkedin.metadata.models.AspectSpec;
import com.linkedin.metadata.models.EntitySpec;
import javax.annotation.Nonnull;
import javax.annotation.Nullable;
@@ -25,20 +24,13 @@ public boolean enabled() {
}
public boolean shouldApply(
- @Nullable ChangeType changeType, @Nonnull Urn entityUrn, @Nonnull AspectSpec aspectSpec) {
- return shouldApply(changeType, entityUrn.getEntityType(), aspectSpec);
+ @Nullable ChangeType changeType, @Nonnull Urn entityUrn, @Nonnull String aspectName) {
+ return shouldApply(changeType, entityUrn.getEntityType(), aspectName);
}
public boolean shouldApply(
- @Nullable ChangeType changeType,
- @Nonnull EntitySpec entitySpec,
- @Nonnull AspectSpec aspectSpec) {
- return shouldApply(changeType, entitySpec.getName(), aspectSpec.getName());
- }
-
- public boolean shouldApply(
- @Nullable ChangeType changeType, @Nonnull String entityName, @Nonnull AspectSpec aspectSpec) {
- return shouldApply(changeType, entityName, aspectSpec.getName());
+ @Nullable ChangeType changeType, @Nonnull EntitySpec entitySpec, @Nonnull String aspectName) {
+ return shouldApply(changeType, entitySpec.getName(), aspectName);
}
public boolean shouldApply(
@@ -49,8 +41,8 @@ && isChangeTypeSupported(changeType)
}
protected boolean isEntityAspectSupported(
- @Nonnull EntitySpec entitySpec, @Nonnull AspectSpec aspectSpec) {
- return isEntityAspectSupported(entitySpec.getName(), aspectSpec.getName());
+ @Nonnull EntitySpec entitySpec, @Nonnull String aspectName) {
+ return isEntityAspectSupported(entitySpec.getName(), aspectName);
}
protected boolean isEntityAspectSupported(
diff --git a/entity-registry/src/main/java/com/linkedin/metadata/aspect/plugins/hooks/MCLSideEffect.java b/entity-registry/src/main/java/com/linkedin/metadata/aspect/plugins/hooks/MCLSideEffect.java
index 57016404648d5..853c2ef5f796c 100644
--- a/entity-registry/src/main/java/com/linkedin/metadata/aspect/plugins/hooks/MCLSideEffect.java
+++ b/entity-registry/src/main/java/com/linkedin/metadata/aspect/plugins/hooks/MCLSideEffect.java
@@ -24,7 +24,7 @@ public final Stream apply(
@Nonnull Collection batchItems, @Nonnull RetrieverContext retrieverContext) {
return applyMCLSideEffect(
batchItems.stream()
- .filter(item -> shouldApply(item.getChangeType(), item.getUrn(), item.getAspectSpec()))
+ .filter(item -> shouldApply(item.getChangeType(), item.getUrn(), item.getAspectName()))
.collect(Collectors.toList()),
retrieverContext);
}
diff --git a/entity-registry/src/main/java/com/linkedin/metadata/aspect/plugins/hooks/MCPSideEffect.java b/entity-registry/src/main/java/com/linkedin/metadata/aspect/plugins/hooks/MCPSideEffect.java
index 52920d8c6f396..ce49dd057bc3e 100644
--- a/entity-registry/src/main/java/com/linkedin/metadata/aspect/plugins/hooks/MCPSideEffect.java
+++ b/entity-registry/src/main/java/com/linkedin/metadata/aspect/plugins/hooks/MCPSideEffect.java
@@ -25,7 +25,7 @@ public final Stream apply(
Collection changeMCPS, @Nonnull RetrieverContext retrieverContext) {
return applyMCPSideEffect(
changeMCPS.stream()
- .filter(item -> shouldApply(item.getChangeType(), item.getUrn(), item.getAspectSpec()))
+ .filter(item -> shouldApply(item.getChangeType(), item.getUrn(), item.getAspectName()))
.collect(Collectors.toList()),
retrieverContext);
}
@@ -41,7 +41,7 @@ public final Stream postApply(
Collection mclItems, @Nonnull RetrieverContext retrieverContext) {
return postMCPSideEffect(
mclItems.stream()
- .filter(item -> shouldApply(item.getChangeType(), item.getUrn(), item.getAspectSpec()))
+ .filter(item -> shouldApply(item.getChangeType(), item.getUrn(), item.getAspectName()))
.collect(Collectors.toList()),
retrieverContext);
}
diff --git a/entity-registry/src/main/java/com/linkedin/metadata/aspect/plugins/hooks/MutationHook.java b/entity-registry/src/main/java/com/linkedin/metadata/aspect/plugins/hooks/MutationHook.java
index c067954912a03..b2fd997d49444 100644
--- a/entity-registry/src/main/java/com/linkedin/metadata/aspect/plugins/hooks/MutationHook.java
+++ b/entity-registry/src/main/java/com/linkedin/metadata/aspect/plugins/hooks/MutationHook.java
@@ -3,6 +3,7 @@
import com.linkedin.metadata.aspect.ReadItem;
import com.linkedin.metadata.aspect.RetrieverContext;
import com.linkedin.metadata.aspect.batch.ChangeMCP;
+import com.linkedin.metadata.aspect.batch.MCPItem;
import com.linkedin.metadata.aspect.plugins.PluginSpec;
import com.linkedin.util.Pair;
import java.util.Collection;
@@ -24,7 +25,7 @@ public final Stream> applyWriteMutation(
@Nonnull Collection changeMCPS, @Nonnull RetrieverContext retrieverContext) {
return writeMutation(
changeMCPS.stream()
- .filter(i -> shouldApply(i.getChangeType(), i.getEntitySpec(), i.getAspectSpec()))
+ .filter(i -> shouldApply(i.getChangeType(), i.getEntitySpec(), i.getAspectName()))
.collect(Collectors.toList()),
retrieverContext);
}
@@ -34,7 +35,23 @@ public final Stream> applyReadMutation(
@Nonnull Collection items, @Nonnull RetrieverContext retrieverContext) {
return readMutation(
items.stream()
- .filter(i -> isEntityAspectSupported(i.getEntitySpec(), i.getAspectSpec()))
+ .filter(i -> isEntityAspectSupported(i.getEntitySpec(), i.getAspectName()))
+ .collect(Collectors.toList()),
+ retrieverContext);
+ }
+
+ /**
+ * Apply Proposal mutations prior to validation
+ *
+ * @param mcpItems wrapper for MCP
+ * @param retrieverContext retriever context
+ * @return stream of mutated Proposal items
+ */
+ public final Stream applyProposalMutation(
+ @Nonnull Collection mcpItems, @Nonnull RetrieverContext retrieverContext) {
+ return proposalMutation(
+ mcpItems.stream()
+ .filter(i -> shouldApply(i.getChangeType(), i.getEntitySpec(), i.getAspectName()))
.collect(Collectors.toList()),
retrieverContext);
}
@@ -48,4 +65,9 @@ protected Stream> writeMutation(
@Nonnull Collection changeMCPS, @Nonnull RetrieverContext retrieverContext) {
return changeMCPS.stream().map(i -> Pair.of(i, false));
}
+
+ protected Stream proposalMutation(
+ @Nonnull Collection mcpItems, @Nonnull RetrieverContext retrieverContext) {
+ return Stream.empty();
+ }
}
diff --git a/entity-registry/src/main/java/com/linkedin/metadata/aspect/plugins/validation/AspectPayloadValidator.java b/entity-registry/src/main/java/com/linkedin/metadata/aspect/plugins/validation/AspectPayloadValidator.java
index b39c38c2768a7..4083329899fee 100644
--- a/entity-registry/src/main/java/com/linkedin/metadata/aspect/plugins/validation/AspectPayloadValidator.java
+++ b/entity-registry/src/main/java/com/linkedin/metadata/aspect/plugins/validation/AspectPayloadValidator.java
@@ -22,7 +22,7 @@ public final Stream validateProposed(
@Nonnull RetrieverContext retrieverContext) {
return validateProposedAspects(
mcpItems.stream()
- .filter(i -> shouldApply(i.getChangeType(), i.getUrn(), i.getAspectSpec()))
+ .filter(i -> shouldApply(i.getChangeType(), i.getUrn(), i.getAspectName()))
.collect(Collectors.toList()),
retrieverContext);
}
@@ -37,7 +37,7 @@ public final Stream validatePreCommit(
@Nonnull Collection changeMCPs, @Nonnull RetrieverContext retrieverContext) {
return validatePreCommitAspects(
changeMCPs.stream()
- .filter(i -> shouldApply(i.getChangeType(), i.getUrn(), i.getAspectSpec()))
+ .filter(i -> shouldApply(i.getChangeType(), i.getUrn(), i.getAspectName()))
.collect(Collectors.toList()),
retrieverContext);
}
diff --git a/metadata-io/build.gradle b/metadata-io/build.gradle
index 6666e33544688..ff29cb5fff47d 100644
--- a/metadata-io/build.gradle
+++ b/metadata-io/build.gradle
@@ -21,6 +21,7 @@ dependencies {
api project(':metadata-service:services')
api project(':metadata-operation-context')
+ implementation spec.product.pegasus.restliServer
implementation spec.product.pegasus.data
implementation spec.product.pegasus.generator
diff --git a/metadata-io/metadata-io-api/build.gradle b/metadata-io/metadata-io-api/build.gradle
index bd79e8cb3ddef..b8028fad07bb6 100644
--- a/metadata-io/metadata-io-api/build.gradle
+++ b/metadata-io/metadata-io-api/build.gradle
@@ -8,4 +8,11 @@ dependencies {
implementation project(':metadata-utils')
compileOnly externalDependency.lombok
annotationProcessor externalDependency.lombok
+
+ testImplementation(externalDependency.testng)
+ testImplementation(externalDependency.mockito)
+ testImplementation(testFixtures(project(":entity-registry")))
+ testImplementation project(':metadata-operation-context')
+ testImplementation externalDependency.lombok
+ testAnnotationProcessor externalDependency.lombok
}
diff --git a/metadata-io/metadata-io-api/src/main/java/com/linkedin/metadata/entity/ebean/batch/AspectsBatchImpl.java b/metadata-io/metadata-io-api/src/main/java/com/linkedin/metadata/entity/ebean/batch/AspectsBatchImpl.java
index 0914df744e413..a23f6ab175046 100644
--- a/metadata-io/metadata-io-api/src/main/java/com/linkedin/metadata/entity/ebean/batch/AspectsBatchImpl.java
+++ b/metadata-io/metadata-io-api/src/main/java/com/linkedin/metadata/entity/ebean/batch/AspectsBatchImpl.java
@@ -8,6 +8,7 @@
import com.linkedin.metadata.aspect.batch.AspectsBatch;
import com.linkedin.metadata.aspect.batch.BatchItem;
import com.linkedin.metadata.aspect.batch.ChangeMCP;
+import com.linkedin.metadata.aspect.batch.MCPItem;
import com.linkedin.metadata.aspect.plugins.validation.ValidationExceptionCollection;
import com.linkedin.mxe.MetadataChangeProposal;
import com.linkedin.util.Pair;
@@ -18,6 +19,7 @@
import java.util.Objects;
import java.util.Set;
import java.util.stream.Collectors;
+import java.util.stream.Stream;
import javax.annotation.Nonnull;
import lombok.Builder;
import lombok.Getter;
@@ -44,9 +46,20 @@ public class AspectsBatchImpl implements AspectsBatch {
public Pair
-To do so, simply follow the [Slack Integration Guide](docs/managed-datahub/saas-slack-setup.md) and contact your Acryl customer success team to enable the feature!
+To do so, simply follow the [Slack Integration Guide](docs/managed-datahub/slack/saas-slack-setup.md) and contact your Acryl customer success team to enable the feature!
diff --git a/docs/managed-datahub/managed-datahub-overview.md b/docs/managed-datahub/managed-datahub-overview.md
index 087238097dd9f..4efc96eaf17a7 100644
--- a/docs/managed-datahub/managed-datahub-overview.md
+++ b/docs/managed-datahub/managed-datahub-overview.md
@@ -56,7 +56,8 @@ know.
| Monitor Freshness SLAs | ❌ | ✅ |
| Monitor Table Schemas | ❌ | ✅ |
| Monitor Table Volume | ❌ | ✅ |
-| Validate Table Columns | ❌ | ✅ |
+| Monitor Table Column Integrity | ❌ | ✅ |
+| Monitor Table with Custom SQL | ❌ | ✅ |
| Receive Notifications via Email & Slack | ❌ | ✅ |
| Manage Data Incidents via Slack | ❌ | ✅ |
| View Data Health Dashboard | ❌ | ✅ |
@@ -115,7 +116,7 @@ Fill out
## Additional Integrations
-- [Slack Integration](docs/managed-datahub/saas-slack-setup.md)
+- [Slack Integration](docs/managed-datahub/slack/saas-slack-setup.md)
- [Remote Ingestion Executor](docs/managed-datahub/operator-guide/setting-up-remote-ingestion-executor.md)
- [AWS Privatelink](docs/managed-datahub/integrations/aws-privatelink.md)
- [AWS Eventbridge](docs/managed-datahub/operator-guide/setting-up-events-api-on-aws-eventbridge.md)
diff --git a/docs/managed-datahub/observe/assertions.md b/docs/managed-datahub/observe/assertions.md
index b74d524dff1bd..e63d051a0096b 100644
--- a/docs/managed-datahub/observe/assertions.md
+++ b/docs/managed-datahub/observe/assertions.md
@@ -38,7 +38,7 @@ If you opt for a 3rd party tool, it will be your responsibility to ensure the as
## Alerts
-Beyond the ability to see the results of the assertion checks (and history of the results) both on the physical asset’s page in the DataHub UI and as the result of DataHub API calls, you can also get notified via [slack messages](/docs/managed-datahub/saas-slack-setup.md) (DMs or to a team channel) based on your [subscription](https://youtu.be/VNNZpkjHG_I?t=79) to an assertion change event. In the future, we’ll also provide the ability to subscribe directly to contracts.
+Beyond the ability to see the results of the assertion checks (and history of the results) both on the physical asset’s page in the DataHub UI and as the result of DataHub API calls, you can also get notified via [Slack messages](/docs/managed-datahub/slack/saas-slack-setup.md) (DMs or to a team channel) based on your [subscription](https://youtu.be/VNNZpkjHG_I?t=79) to an assertion change event. In the future, we’ll also provide the ability to subscribe directly to contracts.
With Acryl Observe, you can get the Assertion Change event by getting API events via [AWS EventBridge](/docs/managed-datahub/operator-guide/setting-up-events-api-on-aws-eventbridge.md) (the availability and simplicity of setup of each solution dependent on your current Acryl setup – chat with your Acryl representative to learn more).
diff --git a/docs/managed-datahub/saas-slack-setup.md b/docs/managed-datahub/saas-slack-setup.md
deleted file mode 100644
index 1b98f3a30773a..0000000000000
--- a/docs/managed-datahub/saas-slack-setup.md
+++ /dev/null
@@ -1,113 +0,0 @@
-import FeatureAvailability from '@site/src/components/FeatureAvailability';
-
-# Configure Slack For Notifications
-
-
-
-## Install the DataHub Slack App into your Slack workspace
-
-The following steps should be performed by a Slack Workspace Admin.
-- Navigate to https://api.slack.com/apps/
-- Click Create New App
-- Use “From an app manifest” option
-- Select your workspace
-- Paste this Manifest in YAML. Suggest changing name and `display_name` to be `DataHub App YOUR_TEAM_NAME` but not required. This name will show up in your slack workspace
-```yml
-display_information:
- name: DataHub App
- description: An app to integrate DataHub with Slack
- background_color: "#000000"
-features:
- bot_user:
- display_name: DataHub App
- always_online: false
-oauth_config:
- scopes:
- bot:
- - channels:read
- - chat:write
- - commands
- - groups:read
- - im:read
- - mpim:read
- - team:read
- - users:read
- - users:read.email
-settings:
- org_deploy_enabled: false
- socket_mode_enabled: false
- token_rotation_enabled: false
-```
-
-Confirm you see the Basic Information Tab
-
-![](https://raw.githubusercontent.com/datahub-project/static-assets/main/imgs/integrations/slack/slack_basic_info.png)
-
-- Click **Install to Workspace**
-- It will show you permissions the Slack App is asking for, what they mean and a default channel in which you want to add the slack app
- - Note that the Slack App will only be able to post in channels that the app has been added to. This is made clear by slack’s Authentication screen also.
-- Select the channel you'd like notifications to go to and click **Allow**
-- Go to DataHub App page
- - You can find your workspace's list of apps at https://api.slack.com/apps/
-
-## Generating a Bot Token
-
-- Go to **OAuth & Permissions** Tab
-
-![](https://raw.githubusercontent.com/datahub-project/static-assets/main/imgs/integrations/slack/slack_oauth_and_permissions.png)
-
-Here you'll find a “Bot User OAuth Token” which DataHub will need to communicate with your slack through the bot.
-In the next steps, we'll show you how to configure the Slack Integration inside of Acryl DataHub.
-
-## Configuring Notifications
-
-> In order to set up the Slack integration, the user must have the `Manage Platform Settings` privilege.
-
-To enable the integration with slack
-- Navigate to **Settings > Integrations**
-- Click **Slack**
-- Enable the Integration
-- Enter the **Bot Token** obtained in the previous steps
-- Enter a **Default Slack Channel** - this is where all notifications will be routed unless
-- Click **Update** to save your settings
-
-
-
-To enable and disable specific types of notifications, or configure custom routing for notifications, start by navigating to **Settings > Notifications**.
-To enable or disable a specific notification type in Slack, simply click the check mark. By default, all notification types are enabled.
-To customize the channel where notifications are send, click the button to the right of the check box.
-
-
-
-If provided, a custom channel will be used to route notifications of the given type. If not provided, the default channel will be used.
-That's it! You should begin to receive notifications on Slack. Note that it may take up to 1 minute for notification settings to take effect after saving.
-
-## Sending Notifications
-
-For now we support sending notifications to
-- Slack Channel ID (e.g. `C029A3M079U`)
-- Slack Channel Name (e.g. `#troubleshoot`)
-- Specific Users (aka Direct Messages or DMs) via user ID
-
-By default, the Slack app will be able to send notifications to public channels. If you want to send notifications to private channels or DMs, you will need to invite the Slack app to those channels.
-
-## How to find Team ID and Channel ID in Slack
-
-- Go to the Slack channel for which you want to get channel ID
-- Check the URL e.g. for the troubleshoot channel in OSS DataHub slack
-
-![](https://raw.githubusercontent.com/datahub-project/static-assets/main/imgs/integrations/slack/slack_channel_url.png)
-
-- Notice `TUMKD5EGJ/C029A3M079U` in the URL
- - Team ID = `TUMKD5EGJ` from above
- - Channel ID = `C029A3M079U` from above
-
-## How to find User ID in Slack
-
-- Go to user DM
-- Click on their profile picture
-- Click on View Full Profile
-- Click on “More”
-- Click on “Copy member ID”
-
-![](https://raw.githubusercontent.com/datahub-project/static-assets/main/imgs/integrations/slack/slack_user_id.png)
\ No newline at end of file
diff --git a/docs/managed-datahub/slack/saas-slack-app.md b/docs/managed-datahub/slack/saas-slack-app.md
new file mode 100644
index 0000000000000..5e16fed901e72
--- /dev/null
+++ b/docs/managed-datahub/slack/saas-slack-app.md
@@ -0,0 +1,59 @@
+import FeatureAvailability from '@site/src/components/FeatureAvailability';
+
+# Slack App Features
+
+
+
+## Overview
+The DataHub Slack App brings several of DataHub's key capabilities directly into your Slack experience. These include:
+1. Searching for Data Assets
+2. Subscribing to notifications for Data Assets
+3. Managing Data Incidents
+
+*Our goal with the Slack app is to make data discovery easier and more accessible for you.*
+
+## Slack App Commands
+The command-based capabilities on the Slack App revolve around search.
+
+### Querying for Assets
+You can trigger a search by simplying typing `/acryl my favorite table`.
+
+
+
+
+Right within Slack, you'll be presented with results matching your query, and a handful of quick-actions for your convenience.
+
+
+
+
+By selecting **'More Details'** you can preview in-depth information about an asset without leaving Slack.
+
+
+
+
+### Subscribing to be notified about an Asset
+You can hit the **'Subscribe'** button on a specific search result to subscribe to it directly from within Slack.
+
+
+
+
+
+## Manage Data Incidents
+Some of the most commonly used features within our Slack app are the Incidents management capabilities.
+The DataHub UI offers a rich set of [Incident tracking and management](https://datahubproject.io/docs/incidents/incidents/) features.
+When a Slack member or channel receives notifications about an Incident, many of these features are made accessible right within the Slack app.
+
+When an incident is raised, you will recieve rich context about the incident in the Slack message itself. You will also be able to `Mark as Resolved`, update the `Priorty`, set a triage `Stage` and `View Details` - directly from the Slack message.
+
+
+
+
+If you choose to `Mark as Resolved` the message will update in-place, and you will be presented with the ability to `Reopen Incident` should you choose.
+
+
+
+
+
+## Coming Soon
+We're constantly working on rolling out new features for the Slack app, stay tuned!
+
diff --git a/docs/managed-datahub/slack/saas-slack-setup.md b/docs/managed-datahub/slack/saas-slack-setup.md
new file mode 100644
index 0000000000000..6db6a77c3a1f3
--- /dev/null
+++ b/docs/managed-datahub/slack/saas-slack-setup.md
@@ -0,0 +1,176 @@
+import FeatureAvailability from '@site/src/components/FeatureAvailability';
+
+# Configure Slack For Notifications
+
+
+
+## Install the DataHub Slack App into your Slack workspace
+
+
+### Video Walkthrough
+
+
+### Step-by-step guide
+The following steps should be performed by a Slack Workspace Admin.
+1. Navigate to [https://api.slack.com/reference/manifests#config-tokens](https://api.slack.com/reference/manifests#config-tokens)
+2. Under **Managing configuration tokens**, select **'Generate Token'**
+
+
+
+3. Select your workspace, then hit **'Generate'**
+
+
+
+4. Now you will see two tokens available for you to copy, an *Access Token* and a *Refresh Token*
+
+
+
+5. Navigate back to your DataHub [Slack Integration setup page](https://longtailcompanions.acryl.io/settings/integrations/slack), and paste the tokens into their respective boxes, and click **'Connect'**.
+
+
+
+6. You will be automatically re-directed to Slack to confirm DataHub Slack App's permissions and complete the installation process:
+
+
+
+7. Congrats 🎉 Slack is set up! Now try it out by going to the **Platform Notifications** page
+
+
+
+8. Enter your channel in, and click **'Send a test notification'**
+
+
+
+
+Now proceed to the [Subscriptions and Notifications page](https://datahubproject.io/docs/managed-datahub/subscription-and-notification) to see how you can subscribe to be notified about events on the platform, or visit the [Slack App page](saas-slack-app.md) to see how you can use DataHub's powerful capabilities directly within Slack.
+
+
+
+## Sending Notifications
+
+For now, we support sending notifications to
+- Slack Channel Name (e.g. `#troubleshoot`)
+- Slack Channel ID (e.g. `C029A3M079U`)
+- Specific Users (aka Direct Messages or DMs) via user ID
+
+By default, the Slack app will be able to send notifications to public channels. If you want to send notifications to private channels or DMs, you will need to invite the Slack app to those channels.
+
+## How to find Team ID and Channel ID in Slack
+:::note
+We recommend just using the Slack channel name for simplicity (e.g. `#troubleshoot`).
+:::
+
+**Via Slack App:**
+1. Go to the Slack channel for which you want to get a channel ID
+2. Click the channel name at the top
+
+
+
+3. At the bottom of the modal that pops up, you will see the Channel ID as well as a button to copy it
+
+
+
+
+**Via Web:**
+1. Go to the Slack channel for which you want to get a channel ID
+2. Check the URL e.g. for the troubleshoot channel in OSS DataHub Slack
+![](https://raw.githubusercontent.com/datahub-project/static-assets/main/imgs/integrations/slack/slack_channel_url.png)
+
+3. Notice `TUMKD5EGJ/C029A3M079U` in the URL
+ - Team ID = `TUMKD5EGJ` from above
+ - Channel ID = `C029A3M079U` from above
+
+## How to find User ID in Slack
+
+**Your User ID**
+1. Click your profile picture, then select **'Profile'**
+
+
+
+2. Now hit the **'...'** and select **'Copy member ID'**
+
+
+
+
+**Someone else's User ID**
+1. Click their profile picture in the Slack message
+
+
+
+2. Now hit the **'...'** and select **'Copy member ID'**
+
+
+
diff --git a/docs/managed-datahub/subscription-and-notification.md b/docs/managed-datahub/subscription-and-notification.md
index 81648d4298ec1..0e456fe415b2c 100644
--- a/docs/managed-datahub/subscription-and-notification.md
+++ b/docs/managed-datahub/subscription-and-notification.md
@@ -5,7 +5,10 @@ import FeatureAvailability from '@site/src/components/FeatureAvailability';
DataHub's Subscriptions and Notifications feature gives you real-time change alerts on data assets of your choice.
-With this feature, you can set up subscriptions to specific changes for an Entity – and DataHub will notify you when those changes happen. Currently, DataHub supports notifications on Slack, with support for Microsoft Teams and email subscriptions forthcoming.
+With this feature, you can set up subscriptions to specific changes for an Entity – and DataHub will notify you when those changes happen. Currently, DataHub supports notifications on Slack and Email, with support for Microsoft Teams forthcoming.
+
+Email will work out of box. For installing the DataHub Slack App, see:
+👉 [Configure Slack for Notifications](slack/saas-slack-setup.md)
@@ -16,7 +19,7 @@ As a user, you can subscribe to and receive notifications about changes such as
## Prerequisites
-Once you have [configured Slack within your DataHub instance](saas-slack-setup.md), you will be able to subscribe to any Entity in DataHub and begin recieving notifications via DM.
+Once you have [configured Slack within your DataHub instance](slack/saas-slack-setup.md), you will be able to subscribe to any Entity in DataHub and begin recieving notifications via DM.
To begin receiving personal notifications, go to Settings > "My Notifications". From here, toggle on Slack Notifications and input your Slack Member ID.
If you want to create and manage group-level Subscriptions for your team, you will need [the following privileges](../../docs/authorization/roles.md#role-privileges):
From 0b64de8f2bb3ea862f7a003024d77a03bd6d903f Mon Sep 17 00:00:00 2001
From: Ellie O'Neil <110510035+eboneil@users.noreply.github.com>
Date: Wed, 17 Jul 2024 14:58:25 -0700
Subject: [PATCH 22/23] fix(airflow): Add comma parsing of owners to DataJobs
(#10903)
---
.../client/airflow_generator.py | 16 +++++++++++-----
1 file changed, 11 insertions(+), 5 deletions(-)
diff --git a/metadata-ingestion-modules/airflow-plugin/src/datahub_airflow_plugin/client/airflow_generator.py b/metadata-ingestion-modules/airflow-plugin/src/datahub_airflow_plugin/client/airflow_generator.py
index 8aa154dc267b6..e9f93c0c1eab0 100644
--- a/metadata-ingestion-modules/airflow-plugin/src/datahub_airflow_plugin/client/airflow_generator.py
+++ b/metadata-ingestion-modules/airflow-plugin/src/datahub_airflow_plugin/client/airflow_generator.py
@@ -127,6 +127,10 @@ def _get_dependencies(
)
return upstream_tasks
+ @staticmethod
+ def _extract_owners(dag: "DAG") -> List[str]:
+ return [owner.strip() for owner in dag.owner.split(",")]
+
@staticmethod
def generate_dataflow(
config: DatahubLineageConfig,
@@ -175,7 +179,7 @@ def generate_dataflow(
data_flow.url = f"{base_url}/tree?dag_id={dag.dag_id}"
if config.capture_ownership_info and dag.owner:
- owners = [owner.strip() for owner in dag.owner.split(",")]
+ owners = AirflowGenerator._extract_owners(dag)
if config.capture_ownership_as_group:
data_flow.group_owners.update(owners)
else:
@@ -282,10 +286,12 @@ def generate_datajob(
datajob.url = f"{base_url}/taskinstance/list/?flt1_dag_id_equals={datajob.flow_urn.flow_id}&_flt_3_task_id={task.task_id}"
if capture_owner and dag.owner:
- if config and config.capture_ownership_as_group:
- datajob.group_owners.add(dag.owner)
- else:
- datajob.owners.add(dag.owner)
+ if config and config.capture_ownership_info:
+ owners = AirflowGenerator._extract_owners(dag)
+ if config.capture_ownership_as_group:
+ datajob.group_owners.update(owners)
+ else:
+ datajob.owners.update(owners)
if capture_tags and dag.tags:
datajob.tags.update(dag.tags)
From 452b94fb023356b7a3392c878a67aed9c6b722cf Mon Sep 17 00:00:00 2001
From: david-leifker <114954101+david-leifker@users.noreply.github.com>
Date: Wed, 17 Jul 2024 17:09:36 -0500
Subject: [PATCH 23/23] fix(entityservice): fix merging sideeffects (#10937)
---
.../metadata/aspect/batch/AspectsBatch.java | 17 +++++++----------
1 file changed, 7 insertions(+), 10 deletions(-)
diff --git a/entity-registry/src/main/java/com/linkedin/metadata/aspect/batch/AspectsBatch.java b/entity-registry/src/main/java/com/linkedin/metadata/aspect/batch/AspectsBatch.java
index 77820948b00cb..fc4ac90dfabad 100644
--- a/entity-registry/src/main/java/com/linkedin/metadata/aspect/batch/AspectsBatch.java
+++ b/entity-registry/src/main/java/com/linkedin/metadata/aspect/batch/AspectsBatch.java
@@ -9,6 +9,7 @@
import com.linkedin.util.Pair;
import java.util.ArrayList;
import java.util.Collection;
+import java.util.HashMap;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
@@ -198,16 +199,12 @@ default Map> getNewUrnAspectsMap(
static Map> merge(
@Nonnull Map> a, @Nonnull Map> b) {
- return Stream.concat(a.entrySet().stream(), b.entrySet().stream())
- .flatMap(
- entry ->
- entry.getValue().entrySet().stream()
- .map(innerEntry -> Pair.of(entry.getKey(), innerEntry)))
- .collect(
- Collectors.groupingBy(
- Pair::getKey,
- Collectors.mapping(
- Pair::getValue, Collectors.toMap(Map.Entry::getKey, Map.Entry::getValue))));
+ Map> mergedMap = new HashMap<>();
+ for (Map.Entry> entry :
+ Stream.concat(a.entrySet().stream(), b.entrySet().stream()).collect(Collectors.toList())) {
+ mergedMap.computeIfAbsent(entry.getKey(), k -> new HashMap<>()).putAll(entry.getValue());
+ }
+ return mergedMap;
}
default String toAbbreviatedString(int maxWidth) {