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Etl Jobs

APIs related to ETL/ELT Spark and Python jobs, shared job libraries, job executions, scripts, resource access, and job lineage.

📄️ Repair and Clean Metadata for Executions

Performs a cleanup or report of metadata associated with Jobs, Schedules, Data Pipelines, Users, Datasets, Access Parity, and Datasources to ensure accurate and efficient data management. For jobs, schedules, and data-pipelines, triggers a state machine cleanup (no request body fields required). For users, datasets, access-parity, and datasources, use Mode to choose report (dry-run) or repair. For Jobs cleanup, it also removes dangling ENIs (network interfaces) in available state within the application VPC and Glue subnets that are left behind by Glue jobs.