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Spring Batch
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
3
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
INTRODUCTION
5
6
BATCH PROCESS?
• Bulk process
• Long running process
• Mostly sequential
• Once, daily, monthly, yearly, ...
7
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.
8
MEET
9
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.
BASIC ARCHITECTURE
11
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
12
BATCH APPLICATION INTERACTIONS AND SERVICES
DEMO 1
14
CHUNK ORIENTED PROCESSING
interface ItemReader<T> {
T read();
}
interface ItemWriter<T> {
void write(List<? extends T> items);
}
• API (pseudo)
15
ITEMREADERS & ITEMWRITERS
ItemReader:
• FlatFileItemReader
• JdbcCursorItemReader
• JdbcPagingItemReader
• HibernateCursorItemReader
• IbatisPagingItemReader
• JmsItemReader
• etc.
DataSource
•Flat File
•XML
•Database
•Message
•etc.
ItemWriter:
•FlatFileItemWriter
•HibernateItemWriter
•JdbcBatchItemWriter
•JpaItemWriter
•etc.
16
STEP
STEP:
Chunk, Tasklet
STEP FLOW:
Sequential
Conditional
17
JOB
- Group of steps
- Represent entire batch process
18
JOB EXECUTION
19
JOB LAUNCHER AND REPOSITORY
JobLauncher
• Simple API to run job
JobRepository
• Store job status/result
• Database, in-memory
20
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
DEMO 2
SUMMARY
Spring Batch provides infrastructure
that focus on business logic
POJO programming with DI
Light weight
easily embedded to existing
application
reuse existing libraries
THANK YOU!

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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
  • 3. 3 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
  • 5. 5
  • 6. 6 BATCH PROCESS? • Bulk process • Long running process • Mostly sequential • Once, daily, monthly, yearly, ...
  • 7. 7 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.
  • 9. 9 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.
  • 11. 11 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
  • 14. 14 CHUNK ORIENTED PROCESSING interface ItemReader<T> { T read(); } interface ItemWriter<T> { void write(List<? extends T> items); } • API (pseudo)
  • 15. 15 ITEMREADERS & ITEMWRITERS ItemReader: • FlatFileItemReader • JdbcCursorItemReader • JdbcPagingItemReader • HibernateCursorItemReader • IbatisPagingItemReader • JmsItemReader • etc. DataSource •Flat File •XML •Database •Message •etc. ItemWriter: •FlatFileItemWriter •HibernateItemWriter •JdbcBatchItemWriter •JpaItemWriter •etc.
  • 17. 17 JOB - Group of steps - Represent entire batch process
  • 19. 19 JOB LAUNCHER AND REPOSITORY JobLauncher • Simple API to run job JobRepository • Store job status/result • Database, in-memory
  • 20. 20 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
  • 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

Notes de l'éditeur

  1. I adjusted this master text box to 2 column format. Instead of two text boxes. Might want to adjust the slide template name.