batchjobs

BatchJobs refer to the execution of non-interactive tasks submitted to a batch processing system. A batch job is typically a script or a defined set of commands that runs without user interaction, often scheduled or triggered when resources become available. Batch systems manage the queuing, scheduling, and execution of these jobs and provide mechanisms for collecting logs, outputs, and status information.

In a typical batch architecture, a user submits a job description to a scheduler or batch interface. The scheduler places the job in a queue, resolves resource requirements (such as CPU, memory, and wall time), and assigns it to an appropriate compute resource or node. Job definitions usually specify input and output data locations, environment settings, dependencies on other jobs, error handling, and accounting information. Output is directed to logs or data stores for audit and analysis.

Key lifecycle stages include submission, validation, queuing, scheduling, execution, monitoring, completion, and archival. Features commonly found in batch systems include priority management, job dependencies, retry and checkpointing mechanisms, resource fairness, and usage accounting. Batch processing is designed for throughput and reproducibility, enabling large-scale workloads to run without manual intervention.

Typical use cases encompass data processing pipelines, ETL tasks, simulations, rendering in film production, and scientific workloads that require reliable, repeatable execution of many tasks. The concept has evolved from mainframe job control languages to modern distributed and cloud-based batch services, which integrate with workflow tools and cloud orchestration to improve scalability and resilience. See also queueing systems, workflow management, and job scheduling.