2023-06-15 00:21:16 -05:00
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import uuid
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from datahub.emitter.mce_builder import make_data_job_urn, make_dataset_urn
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from datahub.emitter.mcp import MetadataChangeProposalWrapper
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from datahub.ingestion.graph.client import DataHubGraph, DataHubGraphConfig
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2023-10-10 16:08:34 +05:30
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from datahub.metadata.schema_classes import (DataJobInfoClass,
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DataJobInputOutputClass,
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EdgeClass)
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2023-06-15 00:21:16 -05:00
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from datahub.specific.datajob import DataJobPatchBuilder
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from tests.patch.common_patch_tests import (
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2023-10-10 16:08:34 +05:30
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helper_test_custom_properties_patch, helper_test_dataset_tags_patch,
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helper_test_entity_terms_patch, helper_test_ownership_patch)
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2023-06-15 00:21:16 -05:00
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def _make_test_datajob_urn(
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seedFlow: str = "SampleAirflowDag", seedTask: str = "SampleAirflowTask"
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):
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return make_data_job_urn(
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orchestrator="airflow",
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flow_id=f"{seedFlow}{uuid.uuid4()}",
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job_id=f"{seedTask}{uuid.uuid4()}",
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)
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# Common Aspect Patch Tests
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# Ownership
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def test_datajob_ownership_patch(wait_for_healthchecks):
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datajob_urn = _make_test_datajob_urn()
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helper_test_ownership_patch(datajob_urn, DataJobPatchBuilder)
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# Tags
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def test_datajob_tags_patch(wait_for_healthchecks):
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helper_test_dataset_tags_patch(_make_test_datajob_urn(), DataJobPatchBuilder)
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2023-06-15 00:21:16 -05:00
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# Terms
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def test_dataset_terms_patch(wait_for_healthchecks):
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helper_test_entity_terms_patch(_make_test_datajob_urn(), DataJobPatchBuilder)
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# Custom Properties
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def test_custom_properties_patch(wait_for_healthchecks):
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orig_datajob_info = DataJobInfoClass(name="test_name", type="TestJobType")
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helper_test_custom_properties_patch(
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test_entity_urn=_make_test_datajob_urn(),
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patch_builder_class=DataJobPatchBuilder,
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custom_properties_aspect_class=DataJobInfoClass,
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base_aspect=orig_datajob_info,
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)
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# Specific Aspect Patch Tests
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# Input/Output
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def test_datajob_inputoutput_dataset_patch(wait_for_healthchecks):
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datajob_urn = _make_test_datajob_urn()
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other_dataset_urn = make_dataset_urn(
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platform="hive", name=f"SampleHiveDataset2-{uuid.uuid4()}", env="PROD"
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)
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patch_dataset_urn = make_dataset_urn(
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platform="hive", name=f"SampleHiveDataset3-{uuid.uuid4()}", env="PROD"
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)
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inputoutput_lineage = DataJobInputOutputClass(
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inputDatasets=[],
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outputDatasets=[],
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inputDatasetEdges=[EdgeClass(destinationUrn=other_dataset_urn)],
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)
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dataset_input_lineage_to_add = EdgeClass(destinationUrn=patch_dataset_urn)
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mcpw = MetadataChangeProposalWrapper(
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entityUrn=datajob_urn, aspect=inputoutput_lineage
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)
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with DataHubGraph(DataHubGraphConfig()) as graph:
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graph.emit_mcp(mcpw)
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inputoutput_lineage_read: DataJobInputOutputClass = graph.get_aspect(
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entity_urn=datajob_urn,
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aspect_type=DataJobInputOutputClass,
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)
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assert (
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inputoutput_lineage_read.inputDatasetEdges[0].destinationUrn
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== other_dataset_urn
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)
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for patch_mcp in (
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DataJobPatchBuilder(datajob_urn)
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.add_input_dataset(dataset_input_lineage_to_add)
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.build()
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):
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graph.emit_mcp(patch_mcp)
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pass
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inputoutput_lineage_read = graph.get_aspect(
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entity_urn=datajob_urn,
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aspect_type=DataJobInputOutputClass,
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)
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assert len(inputoutput_lineage_read.inputDatasetEdges) == 2
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assert (
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inputoutput_lineage_read.inputDatasetEdges[0].destinationUrn
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== other_dataset_urn
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)
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assert (
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inputoutput_lineage_read.inputDatasetEdges[1].destinationUrn
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== patch_dataset_urn
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)
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for patch_mcp in (
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DataJobPatchBuilder(datajob_urn)
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.remove_input_dataset(patch_dataset_urn)
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.build()
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):
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graph.emit_mcp(patch_mcp)
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pass
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inputoutput_lineage_read = graph.get_aspect(
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entity_urn=datajob_urn,
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aspect_type=DataJobInputOutputClass,
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)
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assert len(inputoutput_lineage_read.inputDatasetEdges) == 1
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assert (
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inputoutput_lineage_read.inputDatasetEdges[0].destinationUrn
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== other_dataset_urn
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)
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