Spring Batch is a lightweight and comprehensive batch framework designed for developing robust batch applications needed for daily enterprise operations. It provides infrastructure that focuses on business logic, uses plain-old Java objects with dependency injection, is lightweight and can be easily embedded into existing applications while allowing reuse of existing libraries. Spring Batch handles large data volumes, automation, robustness, reliability, and performance requirements of batch processes through its core concepts of item readers, processors, writers, steps, jobs, job launching, repositories and other features.

1. Spring Batch

2. 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

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WHAT’S IN
STORE?
1. Introduction
 What is a Batch Process?
2. Architecture
 Interactions and services
 Core concepts
3. Demo
 Simple Read write
 JMS Read Write
4. Some points to ponder
5. Summary

4. INTRODUCTION

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BATCH PROCESS?
• Bulk process
• Long running process
• Mostly sequential
• Once, daily, monthly, yearly, ...

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REQUIREMENTS OF A BATCH PROCESS
Large data volume—Batch applications must be able to handle
large volumes of data to import, export, or compute.
Automation—Batch applications must run without user
interaction except for serious problem resolution.
Robustness—Batch applications must handle invalid data
without crashing or
aborting prematurely.
Reliability—Batch applications must keep track of what goes
wrong and when(logging, notification).
Performance—Batch applications must perform well to finish
processing in a dedicated time window or to avoid disturbing any
other applications running simultaneously.

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MEET

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HOW BATCH APPLICATIONS FIT IN TODAY’S
SOFTWARE ARCHITECTURES
• Every day, large and complex calculations take place to index billions of documents,
using cutting-edge algorithms like MapReduce.
• Even in our event- and notification-driven world, batch applications are still
relevant!
• 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.
• Conversions
Batch processing may also 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.

10. BASIC ARCHITECTURE

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BASIC ARCHITECTURE
ItemReader:
retrieve input data from datasource(file, database, queue, etc.)
ItemProcessor:
transform input data to output data
ItemWriter:
persist output data to data store

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BATCH APPLICATION INTERACTIONS AND SERVICES

13. DEMO 1

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CHUNK ORIENTED PROCESSING
interface ItemReader<T> {
T read();
}
interface ItemWriter<T> {
void write(List<? extends T> items);
}
• API (pseudo)

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ITEMREADERS & ITEMWRITERS
ItemReader:
• FlatFileItemReader
• JdbcCursorItemReader
• JdbcPagingItemReader
• HibernateCursorItemReader
• IbatisPagingItemReader
• JmsItemReader
• etc.
DataSource
•Flat File
•XML
•Database
•Message
•etc.
ItemWriter:
•FlatFileItemWriter
•HibernateItemWriter
•JdbcBatchItemWriter
•JpaItemWriter
•etc.

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STEP
STEP:
Chunk, Tasklet
STEP FLOW:
Sequential
Conditional

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JOB
- Group of steps
- Represent entire batch process

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JOB EXECUTION

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JOB LAUNCHER AND REPOSITORY
JobLauncher
• Simple API to run job
JobRepository
• Store job status/result
• Database, in-memory

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AND SOME MORE…
• Parameter passing
(JobParmeters, ExecutionContext) "step"
scope
• Chunk processing
o commit interval, repeat policy, skip policy
• Listeners
o ItemReadListener, ItemProcessListener, It
emWriteListener, StepExecutionListener,
ChunkListener, SkipListener
• Scaling
o multi-
thread, parallel, remote, partitioning
• Web admin

21. DEMO 2

22. SUMMARY
Spring Batch provides infrastructure
that focus on business logic
POJO programming with DI
Light weight
easily embedded to existing
application
reuse existing libraries

23. THANK YOU!