batchworkflow
Batchworkflow refers to the automated orchestration and execution of a collection of tasks grouped into batches. It is commonly used for processing data or tasks that do not require immediate interaction and is typically scheduled to run at regular intervals or when certain events occur, such as data availability.
Core concepts include tasks, inputs, outputs, and dependencies managed by an orchestration engine. The engine schedules
Execution models for batch workflows frequently use directed acyclic graphs (DAGs), where nodes represent tasks and
Architecture typically involves a central scheduler, a pool of workers, and storage for artifacts and logs.
Characteristics and benefits include predictable throughput, consolidated resource management, and easier reproducibility. Batch workflows are suited
Common use cases encompass extract, transform, load (ETL) pipelines, data warehousing, batch machine learning inference, report