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Many applications within the enterprise domain require bulk processing to perform business operations in mission critical environments. These business operations include automated, complex processing of large volumes of information that is most efficiently processed without user interaction. These operations typically include time based events (e.g. month-end calculations, notices or correspondence), periodic application of complex business rules processed repetitively across very large data sets (e.g. insurance benefit determination or rate adjustments), or the integration of information that is received from internal and external systems that typically requires formatting, validation and processing in a transactional manner into the system of record. Batch processing is used to process billions of transactions every day for enterprises.
Spring Batch is a lightweight, comprehensive batch framework designed to enable the development of robust batch applications vital for the daily operations of enterprise systems. Spring Batch builds upon the productivity, POJO-based development approach, and general ease of use capabilities people have come to know from the Spring Framework, while making it easy for developers to access and leverage more advanced enterprise services when necessary.
Spring Batch provides reusable functions that are essential in processing large volumes of records, including logging/tracing, transaction management, job processing statistics, job restart, skip, and resource management. It also provides more advanced technical services and features that will enable extremely high-volume and high performance batch jobs through optimization and partitioning techniques. Simple as well as complex, high-volume batch jobs can leverage the framework in a highly scalable manner to process significant volumes of information.
High Level Architecture:-
In above figure, the top of the hierarchy is the batch application itself. This is whatever batch processing application you want to write. It depends on the Spring Batch core module, which primarily provides a runtime environment for your batch jobs. Both the batch app and the core module in turn depend upon an infrastructure module that provides classes useful for both building and running batch apps.
As we see in above figure a hypothetical three-step job, though obviously a job can have arbitrarily many steps. The steps are typically sequential, though as of Spring Batch 2.0 it’s possible to define conditional flows (e.g., execute step 2 if step 1 succeeds; otherwise execute step 3). Within any given step, the basic process is as follows: read a bunch of “items” (e.g., database rows, XML elements, lines in a flat file—whatever), process them, and write them out somewhere to make it convenient for subsequent steps to work with the result.
Overview of the Spring Batch Core- The Spring Batch Core Domain consists of an API for launching, monitoring and managing batch jobs.
The figure above shows the central parts of the core domain and its main touch points with the batch application developer (Job and Step). To launch a job there is a JobLauncher interface that can be used to simplify the launching for dumb clients like JMX or a command line.
A Job is composed of a list of Steps, each of which is executed in turn by the Job. The Step is a central strategy in the Spring Batch Core. Implementations of Step are responsible for sharing the work out, but in ways that the configuration doesn’t need to be aware of. For instance, the same or very similar Step configuration might be used in a simple in-process sequential executor, or in a multi-threaded implementation, or one that delegates to remote calls to a distributed system.
A Job can be re-used to create multiple job instances and this is reflected in the figure above showing an extended picture of the core domain. When a Job is launched it first checks to see if a job with the same JobParameters was already executed. We expect one of the following outcomes, depending on the Job:
- If the job was not previously launched then it can be created and executed. A new JobInstance is created and stored in a repository (usually a database). A new JobExecution is also created to track the progress of this particular execution.
- If the job was previously launched and failed the Job is responsible for indicating whether it believes it is restartable (is a restart legal and expected). There is a flag for this purpose on the Job. If the there was a previous failure – maybe the operator has fixed some bad input and wants to run it again – then we might want to restart the previous job.
- If the job was previously launched with the same JobParameters and completed successfully, then it is an error to restart it. An ad-hoc request needs to be distinguished from previous runs by adding a unique job parameter. In either case a new JobExecution is created and stored to monitor this execution of the JobInstance.
Spring Batch Launch Environment-
The application style is organized into four logical tiers, which include Run, Job, Application, and Data tiers. The primary goal for organizing an application according to the tiers is to embed what is known as “separation of concerns” within the system. Effective separation of concerns results in reducing the impact of change to the system.
- Run Tier: The Run Tier is concerned with the scheduling and launching of the application. A vendor product is typically used in this tier to allow time-based and interdependent scheduling of batch jobs as well as providing parallel processing capabilities.
- Job Tier: The Job Tier is responsible for the overall execution of a batch job. It sequentially executes batch steps, ensuring that all steps are in the correct state and all appropriate policies are enforced.
- Application Tier: The Application Tier contains components required to execute the program. It contains specific modules that address the required batch functionality and enforces policies around a module execution (e.g., commit intervals, capture of statistics, etc.)
- Data Tier: The Data Tier provides the integration with the physical data sources that might include databases, files, or queues. Note: In some cases the Job tier can be completely missing and in other cases one job script can start several batch job instances.
Contents for Spring Batch 2.0
- What’s New in Spring Batch 2.X.X
- The Domain Language of Batch
- ItemReaders and ItemWriters in Spring Batch 2.0
- Configuring and Running a Job in Spring Batch 2.0
- Configuring a Step in Spring Batch 2.0
- Spring Batch Glossary
- Scaling and Parallel Processing in Spring Batch 2.0
- RepeatTemplate in Spring Batch 2.0
- Hello World With Spring Batch 2.0.x
- Spring Batch ItemReader and ItemWriter Example
- Spring Batch Example MySQL Database To XML
- Spring Batch Example XML File To CSV File
- Spring Batch Example CSV File To MySQL Database
- Spring Batch Example XML File To MongoDB
- Spring Batch Example MultiResourceItemReader
- Spring Batch TaskScheduler Example