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46 lines
1.5 KiB
Python
46 lines
1.5 KiB
Python
from typing import List
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import datahub.emitter.mce_builder as builder
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from datahub.emitter.mcp import MetadataChangeProposalWrapper
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from datahub.emitter.rest_emitter import DatahubRestEmitter
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from datahub.metadata.com.linkedin.pegasus2avro.datajob import DataJobInputOutputClass
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# Construct the DataJobInputOutput aspect.
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input_datasets: List[str] = [
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builder.make_dataset_urn(platform="mysql", name="librarydb.member", env="PROD"),
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builder.make_dataset_urn(platform="mysql", name="librarydb.checkout", env="PROD"),
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]
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output_datasets: List[str] = [
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builder.make_dataset_urn(
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platform="kafka", name="debezium.topics.librarydb.member_checkout", env="PROD"
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)
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]
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input_data_jobs: List[str] = [
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builder.make_data_job_urn(
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orchestrator="airflow", flow_id="flow1", job_id="job0", cluster="PROD"
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)
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]
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datajob_input_output = DataJobInputOutputClass(
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inputDatasets=input_datasets,
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outputDatasets=output_datasets,
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inputDatajobs=input_data_jobs,
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)
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# Construct a MetadataChangeProposalWrapper object.
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# NOTE: This will overwrite all of the existing lineage information associated with this job.
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datajob_input_output_mcp = MetadataChangeProposalWrapper(
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entityUrn=builder.make_data_job_urn(
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orchestrator="airflow", flow_id="flow1", job_id="job1", cluster="PROD"
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),
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aspect=datajob_input_output,
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)
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# Create an emitter to the GMS REST API.
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emitter = DatahubRestEmitter("http://localhost:8080")
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# Emit metadata!
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emitter.emit_mcp(datajob_input_output_mcp)
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