feat: add job run logs retrieval to DbtCloudHook and enhance logging in DbtCloudRunJobOperator #46946
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…in DbtCloudRunJobOperator - Implemented `get_job_run_logs` method in `DbtCloudHook` to retrieve logs for specific dbt Cloud job runs. - Updated `execute_complete` method in `DbtCloudRunJobOperator` to log final job run logs. - Enhanced job run monitoring by streaming logs during job execution, improving visibility into job status. *Relates to apache#46923* Surfacing of DBT Cloud Logs to the logs of the DBTCloudRunJobOperator Signed-off-by: Gavin Burns <[email protected]>
…p logs - Modified `get_job_run_logs` method to fetch and aggregate logs from each step of a dbt Cloud job run, improving log detail and usability. - Updated `DbtCloudRunJobOperator` to ensure `account_id` is passed when retrieving logs, ensuring correct context for log retrieval. - Added unit tests to verify the new log aggregation functionality and ensure `account_id` is correctly utilized, enhancing test coverage. Signed-off-by: Gavin Burns <[email protected]>
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This pull request introduces several enhancements to the
dbtCloud provider in Airflow, focusing on improving the logging and monitoring of job runs. The most important changes include adding a new method to retrieve job run logs, modifying the execution process to stream logs in real-time, and updating theexecute_completemethod to log final job run logs.Enhancements to logging and monitoring:
providers/dbt/cloud/src/airflow/providers/dbt/cloud/hooks/dbt.py: Added theget_job_run_logsmethod to retrieve logs for a specific run of a dbt Cloud job.providers/dbt/cloud/src/airflow/providers/dbt/cloud/operators/dbt.py: Modified theexecutemethod to stream logs for job runs in real-time, providing better visibility into the job's progress.providers/dbt/cloud/src/airflow/providers/dbt/cloud/operators/dbt.py: Updated theexecute_completemethod to log the final logs for job runs, ensuring that the complete log history is captured.<!--Licensed to the Apache Software Foundation (ASF) under one
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Read the Pull Request Guidelines for more information.
In case of fundamental code changes, an Airflow Improvement Proposal (AIP) is needed.
In case of a new dependency, check compliance with the ASF 3rd Party License Policy.
In case of backwards incompatible changes please leave a note in a newsfragment file, named
{pr_number}.significant.rstor{issue_number}.significant.rst, in newsfragments.This pull request introduces new functionality to stream and log job run outputs for dbt Cloud jobs in Airflow, as well as some minor documentation improvements. The most important changes include adding a method to retrieve job run logs, modifying the execution flow to stream logs during job runs, and updating the
execute_completemethod to log final job run outputs.New functionality for logging and streaming:
providers/dbt/cloud/src/airflow/providers/dbt/cloud/hooks/dbt.py: Added a new methodget_job_run_logsto retrieve logs for a specific run of a dbt Cloud job.providers/dbt/cloud/src/airflow/providers/dbt/cloud/operators/dbt.py: Modified theexecutemethod to stream logs during the job run and check the job status in a loop until it reaches a terminal state.Documentation improvements:
providers/dbt/cloud/src/airflow/providers/dbt/cloud/operators/dbt.py: Added a docstring to theexecute_completemethod to provide details about its parameters and return value.These changes enhance the monitoring capabilities for dbt Cloud jobs by providing real-time log streaming and better visibility into job execution status.