-
Notifications
You must be signed in to change notification settings - Fork 3k
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
- Loading branch information
1 parent
9a60c1d
commit 55a77b0
Showing
7 changed files
with
440 additions
and
222 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Empty file.
293 changes: 293 additions & 0 deletions
293
smoke-test/tests/data_process_instance/test_data_process_instance.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,293 @@ | ||
| import logging | ||
| import os | ||
| import tempfile | ||
| from random import randint | ||
|
|
||
| import pytest | ||
| from datahub.emitter.mcp import MetadataChangeProposalWrapper | ||
| from datahub.ingestion.api.common import PipelineContext, RecordEnvelope | ||
| from datahub.ingestion.api.sink import NoopWriteCallback | ||
| from datahub.ingestion.sink.file import FileSink, FileSinkConfig | ||
| from datahub.metadata.schema_classes import ( | ||
| AuditStampClass, | ||
| ContainerClass, | ||
| ContainerPropertiesClass, | ||
| DataPlatformInstanceClass, | ||
| DataPlatformInstancePropertiesClass, | ||
| DataProcessInstanceKeyClass, | ||
| DataProcessInstancePropertiesClass, | ||
| DataProcessInstanceRunEventClass, | ||
| MLHyperParamClass, | ||
| MLMetricClass, | ||
| MLTrainingRunPropertiesClass, | ||
| SubTypesClass, | ||
| TimeWindowSizeClass, | ||
| ) | ||
|
|
||
| from tests.utils import ( | ||
| delete_urns_from_file, | ||
| ingest_file_via_rest, | ||
| wait_for_writes_to_sync, | ||
| ) | ||
|
|
||
| logger = logging.getLogger(__name__) | ||
|
|
||
| # Generate unique DPI ID | ||
| dpi_id = f"test-pipeline-run-{randint(1000, 9999)}" | ||
| dpi_urn = f"urn:li:dataProcessInstance:{dpi_id}" | ||
|
|
||
|
|
||
| class FileEmitter: | ||
| def __init__(self, filename: str) -> None: | ||
| self.sink: FileSink = FileSink( | ||
| ctx=PipelineContext(run_id="create_test_data"), | ||
| config=FileSinkConfig(filename=filename), | ||
| ) | ||
|
|
||
| def emit(self, event): | ||
| self.sink.write_record_async( | ||
| record_envelope=RecordEnvelope(record=event, metadata={}), | ||
| write_callback=NoopWriteCallback(), | ||
| ) | ||
|
|
||
| def close(self): | ||
| self.sink.close() | ||
|
|
||
|
|
||
| def create_test_data(filename: str): | ||
| mcps = [ | ||
| # Key aspect | ||
| MetadataChangeProposalWrapper( | ||
| entityType="dataProcessInstance", | ||
| entityUrn=dpi_urn, | ||
| aspectName="dataProcessInstanceKey", | ||
| aspect=DataProcessInstanceKeyClass(id=dpi_id), | ||
| ), | ||
| # Properties aspect | ||
| MetadataChangeProposalWrapper( | ||
| entityType="dataProcessInstance", | ||
| entityUrn=dpi_urn, | ||
| aspectName="dataProcessInstanceProperties", | ||
| aspect=DataProcessInstancePropertiesClass( | ||
| name="Test Pipeline Run", | ||
| type="BATCH_SCHEDULED", | ||
| created=AuditStampClass( | ||
| time=1640692800000, actor="urn:li:corpuser:datahub" | ||
| ), | ||
| ), | ||
| ), | ||
| # Run Event aspect | ||
| MetadataChangeProposalWrapper( | ||
| entityType="dataProcessInstance", | ||
| entityUrn=dpi_urn, | ||
| aspectName="dataProcessInstanceRunEvent", | ||
| aspect=DataProcessInstanceRunEventClass( | ||
| timestampMillis=1704067200000, | ||
| eventGranularity=TimeWindowSizeClass(unit="WEEK", multiple=1), | ||
| status="COMPLETE", | ||
| ), | ||
| ), | ||
| # Platform Instance aspect | ||
| MetadataChangeProposalWrapper( | ||
| entityType="dataProcessInstance", | ||
| entityUrn=dpi_urn, | ||
| aspectName="dataPlatformInstance", | ||
| aspect=DataPlatformInstanceClass( | ||
| platform="urn:li:dataPlatform:airflow", | ||
| instance="urn:li:dataPlatformInstance:(urn:li:dataPlatform:airflow,1234567890)", | ||
| ), | ||
| ), | ||
| MetadataChangeProposalWrapper( | ||
| entityType="dataPlatformInstance", | ||
| entityUrn="urn:li:dataPlatformInstance:(urn:li:dataPlatform:airflow,1234567890)", | ||
| aspectName="dataPlatformInstanceProperties", | ||
| aspect=DataPlatformInstancePropertiesClass( | ||
| name="my process instance", | ||
| ), | ||
| ), | ||
| # SubTypes aspect | ||
| MetadataChangeProposalWrapper( | ||
| entityType="dataProcessInstance", | ||
| entityUrn=dpi_urn, | ||
| aspectName="subTypes", | ||
| aspect=SubTypesClass(typeNames=["TEST", "BATCH_JOB"]), | ||
| ), | ||
| # Container aspect | ||
| MetadataChangeProposalWrapper( | ||
| entityType="dataProcessInstance", | ||
| entityUrn=dpi_urn, | ||
| aspectName="container", | ||
| aspect=ContainerClass(container="urn:li:container:testGroup1"), | ||
| ), | ||
| MetadataChangeProposalWrapper( | ||
| entityType="container", | ||
| entityUrn="urn:li:container:testGroup1", | ||
| aspectName="containerProperties", | ||
| aspect=ContainerPropertiesClass(name="testGroup1"), | ||
| ), | ||
| # ML Training Run Properties aspect | ||
| MetadataChangeProposalWrapper( | ||
| entityType="dataProcessInstance", | ||
| entityUrn=dpi_urn, | ||
| aspectName="mlTrainingRunProperties", | ||
| aspect=MLTrainingRunPropertiesClass( | ||
| id="test-training-run-123", | ||
| trainingMetrics=[ | ||
| MLMetricClass( | ||
| name="accuracy", | ||
| description="accuracy of the model", | ||
| value="0.95", | ||
| ), | ||
| MLMetricClass( | ||
| name="loss", | ||
| description="accuracy loss of the model", | ||
| value="0.05", | ||
| ), | ||
| ], | ||
| hyperParams=[ | ||
| MLHyperParamClass( | ||
| name="learningRate", | ||
| description="rate of learning", | ||
| value="0.001", | ||
| ), | ||
| MLHyperParamClass( | ||
| name="batchSize", description="size of the batch", value="32" | ||
| ), | ||
| ], | ||
| outputUrls=["s3://my-bucket/ml/output"], | ||
| ), | ||
| ), | ||
| ] | ||
|
|
||
| file_emitter = FileEmitter(filename) | ||
| for mcp in mcps: | ||
| file_emitter.emit(mcp) | ||
| file_emitter.close() | ||
|
|
||
|
|
||
| @pytest.fixture(scope="module", autouse=False) | ||
| def ingest_cleanup_data(auth_session, graph_client, request): | ||
| new_file, filename = tempfile.mkstemp(suffix=".json") | ||
| try: | ||
| create_test_data(filename) | ||
| print("ingesting data process instance test data") | ||
| ingest_file_via_rest(auth_session, filename) | ||
| wait_for_writes_to_sync() | ||
| yield | ||
| print("removing data process instance test data") | ||
| delete_urns_from_file(graph_client, filename) | ||
| wait_for_writes_to_sync() | ||
| finally: | ||
| os.remove(filename) | ||
|
|
||
|
|
||
| @pytest.mark.integration | ||
| def test_search_dpi(auth_session, ingest_cleanup_data): | ||
| """Test DPI search and validation of returned fields using GraphQL.""" | ||
|
|
||
| json = { | ||
| "query": """query scrollAcrossEntities($input: ScrollAcrossEntitiesInput!) { | ||
| scrollAcrossEntities(input: $input) { | ||
| nextScrollId | ||
| count | ||
| total | ||
| searchResults { | ||
| entity { | ||
| ... on DataProcessInstance { | ||
| urn | ||
| properties { | ||
| name | ||
| externalUrl | ||
| } | ||
| dataPlatformInstance { | ||
| platform { | ||
| urn | ||
| name | ||
| } | ||
| } | ||
| subTypes { | ||
| typeNames | ||
| } | ||
| container { | ||
| urn | ||
| } | ||
| platform { | ||
| urn | ||
| name | ||
| properties { | ||
| type | ||
| } | ||
| } | ||
| mlTrainingRunProperties { | ||
| id | ||
| trainingMetrics { | ||
| name | ||
| value | ||
| } | ||
| hyperParams { | ||
| name | ||
| value | ||
| } | ||
| outputUrls | ||
| } | ||
| } | ||
| } | ||
| } | ||
| } | ||
| }""", | ||
| "variables": { | ||
| "input": {"types": ["DATA_PROCESS_INSTANCE"], "query": dpi_id, "count": 10} | ||
| }, | ||
| } | ||
|
|
||
| response = auth_session.post( | ||
| f"{auth_session.frontend_url()}/api/v2/graphql", json=json | ||
| ) | ||
| response.raise_for_status() | ||
| res_data = response.json() | ||
|
|
||
| # Basic response structure validation | ||
| assert res_data, "Response should not be empty" | ||
| assert "data" in res_data, "Response should contain 'data' field" | ||
| print("RESPONSE DATA:" + str(res_data)) | ||
| assert ( | ||
| "scrollAcrossEntities" in res_data["data"] | ||
| ), "Response should contain 'scrollAcrossEntities' field" | ||
|
|
||
| search_results = res_data["data"]["scrollAcrossEntities"] | ||
| assert ( | ||
| "searchResults" in search_results | ||
| ), "Response should contain 'searchResults' field" | ||
|
|
||
| results = search_results["searchResults"] | ||
| assert len(results) > 0, "Should find at least one result" | ||
|
|
||
| # Find our test entity | ||
| test_entity = None | ||
| for result in results: | ||
| if result["entity"]["urn"] == dpi_urn: | ||
| test_entity = result["entity"] | ||
| break | ||
|
|
||
| assert test_entity is not None, f"Should find test entity with URN {dpi_urn}" | ||
|
|
||
| # Validate fields | ||
| props = test_entity["properties"] | ||
| assert props["name"] == "Test Pipeline Run" | ||
|
|
||
| platform_instance = test_entity["dataPlatformInstance"] | ||
| assert platform_instance["platform"]["urn"] == "urn:li:dataPlatform:airflow" | ||
|
|
||
| sub_types = test_entity["subTypes"] | ||
| assert set(sub_types["typeNames"]) == {"TEST", "BATCH_JOB"} | ||
|
|
||
| container = test_entity["container"] | ||
| assert container["urn"] == "urn:li:container:testGroup1" | ||
|
|
||
| ml_props = test_entity["mlTrainingRunProperties"] | ||
| assert ml_props["id"] == "test-training-run-123" | ||
| assert ml_props["trainingMetrics"][0] == {"name": "accuracy", "value": "0.95"} | ||
| assert ml_props["trainingMetrics"][1] == {"name": "loss", "value": "0.05"} | ||
| assert ml_props["hyperParams"][0] == {"name": "learningRate", "value": "0.001"} | ||
| assert ml_props["hyperParams"][1] == {"name": "batchSize", "value": "32"} | ||
| assert ml_props["outputUrls"][0] == "s3://my-bucket/ml/output" |
Oops, something went wrong.