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Batch processing is the execution of a series of programs ("jobs") on a computer without manual intervention.
Jobs are set up so they can be run to completion without human interaction. All input parameters are predefined throughscripts, command-line arguments, control files, or job control language. This is in contrast to "online" or interactive programs which prompt the user for such input. A program takes a set of data files as input, processes the data, and produces a set of output data files. This operating environment is termed as "batch processing" because the input data are collected into batches or sets of records and each batch is processed as a unit. The output is another batch that can be reused for computation.
Benefits
Batch processing has these benefits:
• It can shift the time of job processing to when the computing resources are less busy.
• It avoids idling the computing resources with minute-by-minute manual intervention and supervision.
• By keeping high overall rate of utilization, it amortizes the computer, especially an expensive one.
• It allows the system to use different priorities for interactive and non-interactive work.
• Rather than running one program multiple times to process one transaction each time, batch processes will run the program only once for many transactions, reducing system overhead
Modern systems
Batch applications are still critical in most organizations in large part because many common business processes are amenable to batch processing. While online systems can also function when manual intervention is not desired, they are not typically optimized to perform high-volume, repetitive tasks. Therefore, even new systems usually contain one or more batch applications for updating information at the end of the day, generating reports, printing documents, and other non-interactive tasks that must complete reliably within certain business deadlines.
Modern batch applications make use of modern batch frameworks such as Jem The Bee, Spring Batch or implementations ofJSR 352[1] written for Java, and other frameworks for other programming languages, to provide the fault tolerance and scalability required for high-volume processing. In order to ensure high-speed processing, batch applications are often integrated with grid computing solutions to partition a batch job over a large number of processors, although there are significant programming challenges in doing so. High volume batch processing places particularly heavy demands on system and application architectures as well. Architectures that feature strong input/output performance and vertical scalability, including modern mainframe computers, tend to provide better batch performance than alternatives.
Scripting languages became popular as they evolved along with batch processing.
Common batch processing usage
Databases
Batch processing is also used for efficient bulk database updates and automated transaction processing, as contrasted to interactive online transaction processing (OLTP) applications. The extract, transform, load (ETL) step in populating data warehouses is inherently a batch process in most implementations.
Images
Batch processing is often used to perform various operations with digital images such as resize, convert, watermark, or otherwise edit image files.
Conversions
Batch processing may also be used for converting computer files from one format to another. For example, a batch job may convert proprietary and legacy files to common standard formats for end-user queries and display.