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58 lines
2.0 KiB
Python
58 lines
2.0 KiB
Python
import logging
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from typing import Optional
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from datahub.emitter.mce_builder import make_dataset_urn, make_term_urn
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from datahub.emitter.mcp import MetadataChangeProposalWrapper
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# read-modify-write requires access to the DataHubGraph (RestEmitter is not enough)
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from datahub.ingestion.graph.client import DatahubClientConfig, DataHubGraph
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# Imports for metadata model classes
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from datahub.metadata.schema_classes import (
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AuditStampClass,
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GlossaryTermAssociationClass,
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GlossaryTermsClass,
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)
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log = logging.getLogger(__name__)
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logging.basicConfig(level=logging.INFO)
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# First we get the current terms
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gms_endpoint = "http://localhost:8080"
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graph = DataHubGraph(DatahubClientConfig(server=gms_endpoint))
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dataset_urn = make_dataset_urn(platform="hive", name="realestate_db.sales", env="PROD")
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current_terms: Optional[GlossaryTermsClass] = graph.get_aspect(
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entity_urn=dataset_urn, aspect_type=GlossaryTermsClass
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)
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term_to_add = make_term_urn("Classification.HighlyConfidential")
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term_association_to_add = GlossaryTermAssociationClass(urn=term_to_add)
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# an audit stamp that basically says we have no idea when these terms were added to this dataset
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# change the time value to (time.time() * 1000) if you want to specify the current time of running this code as the time
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unknown_audit_stamp = AuditStampClass(time=0, actor="urn:li:corpuser:ingestion")
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need_write = False
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if current_terms:
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if term_to_add not in [x.urn for x in current_terms.terms]:
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# terms exist, but this term is not present in the current terms
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current_terms.terms.append(term_association_to_add)
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need_write = True
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else:
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# create a brand new terms aspect
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current_terms = GlossaryTermsClass(
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terms=[term_association_to_add],
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auditStamp=unknown_audit_stamp,
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)
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need_write = True
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if need_write:
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event: MetadataChangeProposalWrapper = MetadataChangeProposalWrapper(
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entityUrn=dataset_urn,
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aspect=current_terms,
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)
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graph.emit(event)
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else:
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log.info(f"Term {term_to_add} already exists, omitting write")
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