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Computerized batch processing is a method of running software programs called jobs in batches automatically. While users are required to submit the jobs, no other ...
A job scheduler is a computer application for controlling unattended background program execution of jobs. [1] This is commonly called batch scheduling, as execution of non-interactive jobs is often called batch processing, though traditional job and batch are distinguished and contrasted; see that page for details.
Batch processing is execution of a series of programs (jobs) on a computer without manual intervention. Several transactions, called a batch are collected and processed at the same time. The results of each transaction are not immediately available when the transaction is being entered; [1] there is a time delay.
Spring Batch is an open source framework for batch processing. It is a lightweight, comprehensive solution designed to enable the development of robust batch applications, [1] which are often found in modern enterprise systems. Spring Batch builds upon the POJO-based development approach of the Spring Framework. [2]
Apache Flink is an open-source, unified stream-processing and batch-processing framework developed by the Apache Software Foundation. The core of Apache Flink is a distributed streaming data-flow engine written in Java and Scala. [3] [4] Flink executes arbitrary dataflow programs in a data-parallel and pipelined (hence task parallel) manner. [5]
During batch processing, several different programs were loaded in the computer memory, and the first one began to run. When the first program reached an instruction waiting for a peripheral, the context of this program was stored away, and the second program in memory was given a chance to run.
In system software, a job queue (a.k.a. batch queue, input queue), is a data structure maintained by job scheduler software containing jobs to run. [1] Users submit their programs that they want executed, "jobs", to the queue for batch processing. The scheduler software maintains the queue as the pool of jobs available for it to run.
These programs might take hours to run. As computers grew in speed, run times dropped, and soon the time taken to start up the next program became a concern. Newer batch processing software and methodologies, including batch operating systems such as IBSYS (1960), decreased these "dead periods" by queuing up programs ready to run. [4]