Merge branch 'master' into jk-fix-empty-schema-field

Author: jayasimhankv

docs/cli.md

@@ -735,7 +735,7 @@ Please see our [Integrations page](https://datahubproject.io/integrations) if yo
 | [bigquery](./generated/ingestion/sources/bigquery.md)                                          | `pip install 'acryl-datahub[bigquery]'`                    | BigQuery source                         |
 | [datahub-lineage-file](./generated/ingestion/sources/file-based-lineage.md)                    | _no additional dependencies_                               | Lineage File source                     |
 | [datahub-business-glossary](./generated/ingestion/sources/business-glossary.md)                | _no additional dependencies_                               | Business Glossary File source           |
-| [dbt](./generated/ingestion/sources/dbt.md)                                                    | _no additional dependencies_                               | dbt source                              |
+| [dbt](./generated/ingestion/sources/dbt.md)                                                    | `pip install 'acryl-datahub[dbt]'`                         | dbt source                              |
 | [dremio](./generated/ingestion/sources/dremio.md)                                              | `pip install 'acryl-datahub[dremio]'`                      | Dremio Source                           |
 | [druid](./generated/ingestion/sources/druid.md)                                                | `pip install 'acryl-datahub[druid]'`                       | Druid Source                            |
 | [feast](./generated/ingestion/sources/feast.md)                                                | `pip install 'acryl-datahub[feast]'`                       | Feast source (0.26.0)                   |

docs/managed-datahub/operator-guide/setting-up-remote-ingestion-executor.md

@@ -125,6 +125,50 @@ The Helm chart [datahub-executor-worker](https://executor-helm.acryl.io/index.ya
     --set image.tag=v0.3.1 \
     acryl datahub-executor-worker
   ```
+9. As of DataHub Cloud `v0.3.8.2` It is possible to pass secrets to ingestion recipes using Kubernetes Secret CRDs as shown below. This allows to update secrets at runtime without restarting Remote Executor process.
+  ```
+    # 1. Create K8s Secret object in remote executor namespace, e.g.
+    apiVersion: v1
+    kind: Secret
+    metadata:
+      name: datahub-secret-store
+    data:
+      REDSHIFT_PASSWORD: cmVkc2hpZnQtc2VjcmV0Cg==
+      SNOWFLAKE_PASSWORD: c25vd2ZsYWtlLXNlY3JldAo=
+    # 2. Add secret into your Remote Executor deployment:
+    extraVolumes:
+      - name: datahub-secret-store
+        secret:
+          secretName: datahub-secret-store
+    # 3. Mount it under /mnt/secrets directory
+    extraVolumeMounts:
+    - mountPath: /mnt/secrets
+      name: datahub-secret-store
+  ```
+You can then reference the mounted secrets directly in the ingestion recipe:
+```yaml
+source:
+    type: redshift
+    config:
+        host_port: '<redshift host:port>'
+        username: connector_test
+        table_lineage_mode: mixed
+        include_table_lineage: true
+        include_tables: true
+        include_views: true
+        profiling:
+            enabled: true
+            profile_table_level_only: false
+        stateful_ingestion:
+            enabled: true
+        password: '${REDSHIFT_PASSWORD}'
+``` 
+
+By default the executor will look for files mounted in `/mnt/secrets`, this is override-able by setting the env var: 
+`DATAHUB_EXECUTOR_FILE_SECRET_BASEDIR` to a different location (default: `/mnt/secrets`)
+
+These files are expected to be under 1MB in data by default. To increase this limit set a higher value using:
+`DATAHUB_EXECUTOR_FILE_SECRET_MAXLEN` (default: `1024768`, size in bytes)
 
 ## FAQ
 

docs/managed-datahub/release-notes/v_0_3_8.md

@@ -3,7 +3,7 @@
 
 Release Availability Date
 ---
-21-Jan-2025
+29-Jan-2025
 
 Recommended CLI/SDK
 ---

metadata-ingestion/setup.cfg

@@ -15,6 +15,9 @@ warn_unused_configs = yes
 disallow_untyped_defs = no
 
 # try to be a bit more strict in certain areas of the codebase
+[mypy-datahub]
+# Only for datahub's __init__.py - allow implicit reexport
+implicit_reexport = yes
 [mypy-datahub.*]
 ignore_missing_imports = no
 implicit_reexport = no
@@ -54,7 +57,7 @@ addopts = --cov=src --cov-report= --cov-config setup.cfg --strict-markers -p no:
 markers =
     slow: marks tests that are slow to run, including all docker-based tests (deselect with '-m not slow')
     integration: marks all integration tests, across all batches (deselect with '-m "not integration"')
-    integration_batch_0: mark tests to run in batch 0 of integration tests. This is done mainly for parallelisation in CI. Batch 0 is the default batch.
+    integration_batch_0: mark tests to run in batch 0 of integration tests. This is done mainly for parallelization in CI. Batch 0 is the default batch.
     integration_batch_1: mark tests to run in batch 1 of integration tests
     integration_batch_2: mark tests to run in batch 2 of integration tests
 testpaths =

metadata-ingestion/src/datahub/errors.py

@@ -0,0 +1,35 @@
+from datahub.configuration.common import MetaError
+
+# TODO: Move all other error types to this file.
+
+
+class SdkUsageError(MetaError):
+    pass
+
+
+class AlreadyExistsError(SdkUsageError):
+    pass
+
+
+class ItemNotFoundError(SdkUsageError):
+    pass
+
+
+class MultipleItemsFoundError(SdkUsageError):
+    pass
+
+
+class SchemaFieldKeyError(SdkUsageError, KeyError):
+    pass
+
+
+class IngestionAttributionWarning(Warning):
+    pass
+
+
+class MultipleSubtypesWarning(Warning):
+    pass
+
+
+class ExperimentalWarning(Warning):
+    pass

metadata-ingestion/src/datahub/ingestion/source/snowflake/snowflake_schema.py

@@ -6,6 +6,7 @@
 from typing import Callable, Dict, Iterable, List, MutableMapping, Optional
 
 from datahub.ingestion.api.report import SupportsAsObj
+from datahub.ingestion.source.common.subtypes import DatasetSubTypes
 from datahub.ingestion.source.snowflake.constants import SnowflakeObjectDomain
 from datahub.ingestion.source.snowflake.snowflake_connection import SnowflakeConnection
 from datahub.ingestion.source.snowflake.snowflake_query import (
@@ -100,6 +101,9 @@ class SnowflakeTable(BaseTable):
     def is_hybrid(self) -> bool:
         return self.type is not None and self.type == "HYBRID TABLE"
 
+    def get_subtype(self) -> DatasetSubTypes:
+        return DatasetSubTypes.TABLE
+
 
 @dataclass
 class SnowflakeView(BaseView):
@@ -109,6 +113,9 @@ class SnowflakeView(BaseView):
     column_tags: Dict[str, List[SnowflakeTag]] = field(default_factory=dict)
     is_secure: bool = False
 
+    def get_subtype(self) -> DatasetSubTypes:
+        return DatasetSubTypes.VIEW
+
 
 @dataclass
 class SnowflakeSchema:
@@ -154,6 +161,9 @@ class SnowflakeStream:
     column_tags: Dict[str, List[SnowflakeTag]] = field(default_factory=dict)
     last_altered: Optional[datetime] = None
 
+    def get_subtype(self) -> DatasetSubTypes:
+        return DatasetSubTypes.SNOWFLAKE_STREAM
+
 
 class _SnowflakeTagCache:
     def __init__(self) -> None:

metadata-ingestion/src/datahub/ingestion/source/snowflake/snowflake_schema_gen.py

@@ -21,7 +21,6 @@
 from datahub.ingestion.source.aws.s3_util import make_s3_urn_for_lineage
 from datahub.ingestion.source.common.subtypes import (
     DatasetContainerSubTypes,
-    DatasetSubTypes,
 )
 from datahub.ingestion.source.snowflake.constants import (
     GENERIC_PERMISSION_ERROR_KEY,
@@ -467,7 +466,13 @@ def _process_schema(
                 context=f"{db_name}.{schema_name}",
             )
 
-    def _process_tags(self, snowflake_schema, schema_name, db_name, domain):
+    def _process_tags(
+        self,
+        snowflake_schema: SnowflakeSchema,
+        schema_name: str,
+        db_name: str,
+        domain: str,
+    ) -> None:
         snowflake_schema.tags = self.tag_extractor.get_tags_on_object(
             schema_name=schema_name, db_name=db_name, domain=domain
         )
@@ -837,15 +842,7 @@ def gen_dataset_workunits(
         if dpi_aspect:
             yield dpi_aspect
 
-        subTypes = SubTypes(
-            typeNames=(
-                [DatasetSubTypes.SNOWFLAKE_STREAM]
-                if isinstance(table, SnowflakeStream)
-                else [DatasetSubTypes.VIEW]
-                if isinstance(table, SnowflakeView)
-                else [DatasetSubTypes.TABLE]
-            )
-        )
+        subTypes = SubTypes(typeNames=[table.get_subtype()])
 
         yield MetadataChangeProposalWrapper(
             entityUrn=dataset_urn, aspect=subTypes
@@ -932,9 +929,9 @@ def get_dataset_properties(
                         "OWNER_ROLE_TYPE": table.owner_role_type,
                         "TABLE_NAME": table.table_name,
                         "BASE_TABLES": table.base_tables,
-                        "STALE_AFTER": table.stale_after.isoformat()
-                        if table.stale_after
-                        else None,
+                        "STALE_AFTER": (
+                            table.stale_after.isoformat() if table.stale_after else None
+                        ),
                     }.items()
                     if v
                 }

metadata-ingestion/src/datahub/sdk/__init__.py

@@ -0,0 +1,33 @@
+import warnings
+
+import datahub.metadata.schema_classes as models
+from datahub.errors import ExperimentalWarning, SdkUsageError
+from datahub.ingestion.graph.config import DatahubClientConfig
+from datahub.metadata.urns import (
+    ChartUrn,
+    ContainerUrn,
+    CorpGroupUrn,
+    CorpUserUrn,
+    DashboardUrn,
+    DataPlatformInstanceUrn,
+    DataPlatformUrn,
+    DatasetUrn,
+    DomainUrn,
+    GlossaryTermUrn,
+    SchemaFieldUrn,
+    TagUrn,
+)
+from datahub.sdk.container import Container
+from datahub.sdk.dataset import Dataset
+from datahub.sdk.main_client import DataHubClient
+
+warnings.warn(
+    "The new datahub SDK (e.g. datahub.sdk.*) is experimental. "
+    "Our typical backwards-compatibility and stability guarantees do not apply to this code. "
+    "When it's promoted to stable, the import path will change "
+    "from `from datahub.sdk import ...` to `from datahub import ...`.",
+    ExperimentalWarning,
+    stacklevel=2,
+)
+del warnings
+del ExperimentalWarning

metadata-ingestion/src/datahub/sdk/_all_entities.py

@@ -0,0 +1,15 @@
+from typing import Dict, List, Type
+
+from datahub.sdk._entity import Entity
+from datahub.sdk.container import Container
+from datahub.sdk.dataset import Dataset
+
+# TODO: Is there a better way to declare this?
+ENTITY_CLASSES_LIST: List[Type[Entity]] = [
+    Container,
+    Dataset,
+]
+
+ENTITY_CLASSES: Dict[str, Type[Entity]] = {
+    cls.get_urn_type().ENTITY_TYPE: cls for cls in ENTITY_CLASSES_LIST
+}

metadata-ingestion/src/datahub/sdk/_attribution.py

@@ -0,0 +1,48 @@
+from __future__ import annotations
+
+import contextlib
+from typing import Iterator
+
+from datahub.utilities.str_enum import StrEnum
+
+
+class KnownAttribution(StrEnum):
+    INGESTION = "INGESTION"
+    INGESTION_ALTERNATE = "INGESTION_ALTERNATE"
+
+    UI = "UI"
+    SDK = "SDK"
+
+    PROPAGATION = "PROPAGATION"
+
+    def is_ingestion(self) -> bool:
+        return self in (
+            KnownAttribution.INGESTION,
+            KnownAttribution.INGESTION_ALTERNATE,
+        )
+
+
+_default_attribution = KnownAttribution.SDK
+
+
+def get_default_attribution() -> KnownAttribution:
+    return _default_attribution
+
+
+def set_default_attribution(attribution: KnownAttribution) -> None:
+    global _default_attribution
+    _default_attribution = attribution
+
+
+@contextlib.contextmanager
+def change_default_attribution(attribution: KnownAttribution) -> Iterator[None]:
+    old_attribution = get_default_attribution()
+    try:
+        set_default_attribution(attribution)
+        yield
+    finally:
+        set_default_attribution(old_attribution)
+
+
+def is_ingestion_attribution() -> bool:
+    return get_default_attribution().is_ingestion()