mirror of
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119 lines
3.7 KiB
Python
119 lines
3.7 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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Entrypoint to send exit handler information when a pipeline fails
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"""
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import logging
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import os
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from datetime import datetime
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import yaml
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from metadata.generated.schema.entity.services.ingestionPipelines.ingestionPipeline import (
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PipelineState,
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PipelineStatus,
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)
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from metadata.generated.schema.metadataIngestion.workflow import (
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OpenMetadataWorkflowConfig,
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)
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from metadata.ingestion.ometa.ometa_api import OpenMetadata
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SUCCESS_STATES = {"Succeeded"}
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def main():
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"""
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Exit Handler entrypoint
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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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The goal of this script is to be executed as a failure callback/exit handler
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when a Workflow processing fails. There are situations where the failure
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cannot be directly controlled in the Workflow class.
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We don't want to initialize the full workflow as it might be failing
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on the `__init__` call as well. We'll manually prepare the status sending
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logic.
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In this callback we just care about:
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- instantiating the ometa client
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- getting the IngestionPipeline FQN
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- if exists, update with `Failed` status
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"""
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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_run_id = os.getenv("pipelineRunId")
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raw_pipeline_status = os.getenv("pipelineStatus")
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raw_workflow_config = yaml.safe_load(config)
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raw_workflow_config["pipelineRunId"] = pipeline_run_id
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workflow_config = OpenMetadataWorkflowConfig.model_validate(raw_workflow_config)
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metadata = OpenMetadata(
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config=workflow_config.workflowConfig.openMetadataServerConfig
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)
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if workflow_config.ingestionPipelineFQN and pipeline_run_id and raw_pipeline_status:
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logging.info(
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f"Sending status to Ingestion Pipeline {workflow_config.ingestionPipelineFQN}"
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)
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pipeline_status = metadata.get_pipeline_status(
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workflow_config.ingestionPipelineFQN,
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str(workflow_config.pipelineRunId.root),
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)
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# Maybe the workflow was not even initialized
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if not pipeline_status:
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pipeline_status = PipelineStatus(
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runId=str(workflow_config.pipelineRunId.root),
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startDate=datetime.now().timestamp() * 1000,
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timestamp=datetime.now().timestamp() * 1000,
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)
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pipeline_status.endDate = datetime.now().timestamp() * 1000
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pipeline_status.pipelineState = (
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PipelineState.failed
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if raw_pipeline_status not in SUCCESS_STATES
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else PipelineState.success
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)
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metadata.create_or_update_pipeline_status(
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workflow_config.ingestionPipelineFQN, pipeline_status
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)
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else:
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logging.info(
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"Missing ingestionPipelineFQN, pipelineRunId or pipelineStatus. We won't update the status."
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)
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if __name__ == "__main__":
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main()
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