mirror of
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115 lines
3.6 KiB
Python
115 lines
3.6 KiB
Python
# Copyright 2025 Collate
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# Licensed under the Collate Community License, Version 1.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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# https://github.com/open-metadata/OpenMetadata/blob/main/ingestion/LICENSE
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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Main ingestion entrypoint to run OM workflows
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"""
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import os
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import yaml
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from metadata.generated.schema.entity.services.ingestionPipelines.ingestionPipeline import (
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PipelineType,
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)
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from metadata.generated.schema.metadataIngestion.workflow import LogLevels
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from metadata.utils.logger import set_loggers_level
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from metadata.workflow.data_quality import TestSuiteWorkflow
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from metadata.workflow.metadata import MetadataWorkflow
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from metadata.workflow.profiler import ProfilerWorkflow
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from metadata.workflow.usage import UsageWorkflow
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WORKFLOW_MAP = {
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PipelineType.metadata.value: MetadataWorkflow,
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PipelineType.usage.value: UsageWorkflow,
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PipelineType.lineage.value: MetadataWorkflow,
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PipelineType.profiler.value: ProfilerWorkflow,
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PipelineType.TestSuite.value: TestSuiteWorkflow,
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PipelineType.elasticSearchReindex.value: MetadataWorkflow,
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PipelineType.dbt.value: MetadataWorkflow,
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}
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def main():
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"""
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Ingestion entrypoint. Get the right Workflow class
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and execute the ingestion.
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This image is expected to be used and run in environments
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such as Airflow's KubernetesPodOperator:
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```
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config = '''
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source:
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type: ...
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serviceName: ...
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serviceConnection:
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...
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sourceConfig:
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...
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sink:
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...
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workflowConfig:
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...
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'''
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KubernetesPodOperator(
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task_id="ingest",
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name="ingest",
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cmds=["python", "main.py"],
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image="openmetadata/ingestion-base:0.13.2",
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namespace='default',
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env_vars={"config": config, "pipelineType": "metadata"},
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dag=dag,
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)
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```
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Note how we are expecting the env variables to be sent, with the `config` being the str
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representation of the ingestion YAML.
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We will also set the `pipelineRunId` value if it comes from the environment.
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"""
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# DockerOperator expects an env var called config
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config = os.getenv("config")
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if not config:
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raise RuntimeError(
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"Missing environment variable `config`. This is needed to configure the Workflow."
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)
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pipeline_type = os.getenv("pipelineType")
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if not pipeline_type:
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raise RuntimeError(
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"Missing environment variable `pipelineType`. This is needed to load the Workflow class."
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)
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pipeline_run_id = os.getenv("pipelineRunId")
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workflow_class = WORKFLOW_MAP.get(pipeline_type)
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if workflow_class is None:
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raise ValueError(f"Missing workflow_class loaded from {pipeline_type}")
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# Load the config string representation
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workflow_config = yaml.safe_load(config)
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if pipeline_run_id:
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workflow_config["pipelineRunId"] = pipeline_run_id
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logger_level = workflow_config.get("workflowConfig", {}).get("loggerLevel")
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set_loggers_level(logger_level or LogLevels.INFO.value)
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workflow = workflow_class.create(workflow_config)
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workflow.execute()
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workflow.raise_from_status()
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workflow.print_status()
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workflow.stop()
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if __name__ == "__main__":
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main()
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