SpringTutorials
    Back to Spring Batch
    Section 1

    Introduction to Spring Batch

    What is batch processing and why use Spring Batch for enterprise applications

    What is Batch Processing?

    Batch processing is the execution of a series of jobs without manual intervention. Unlike real-time processing where data is processed immediately, batch processing collects data over time and processes it all at once.

    Real-time Processing
    • • Immediate response required
    • • User is waiting for result
    • • Single transaction at a time
    • • Example: API request/response
    Batch Processing
    • • Scheduled execution
    • • No user waiting
    • • Millions of records at once
    • • Example: Nightly report generation

    Common Batch Processing Use Cases:

    Data migration
    Report generation
    ETL processes
    Billing calculations
    Data synchronization
    Log processing

    Why Spring Batch?

    Spring Batch is the de-facto standard for batch processing in Java. It's a lightweight, comprehensive framework designed for enterprise-grade batch applications.

    Chunk-Oriented Processing

    Process data in manageable chunks with automatic transaction management and commit intervals.

    Restartability & Recovery

    Resume failed jobs from where they left off with built-in state persistence.

    Skip & Retry Logic

    Define policies for handling errors - skip bad records or retry transient failures.

    Parallel Processing

    Multi-threaded steps, partitioning, and remote chunking for high-throughput jobs.

    Spring Integration

    Seamlessly integrates with Spring Boot, Spring Data, and the entire Spring ecosystem.

    Getting Started with Spring Batch

    Add the Spring Batch starter dependency to your Spring Boot project:

    pom.xml
    <dependencies><!-- Spring Batch Starter --><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-batch</artifactId></dependency><!-- Database for Job Repository --><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-data-jpa</artifactId></dependency><dependency><groupId>com.h2database</groupId><artifactId>h2</artifactId><scope>runtime</scope></dependency></dependencies>
    application.properties
    # Initialize Spring Batch schemaspring.batch.jdbc.initialize-schema=always# H2 Console (for development)spring.h2.console.enabled=truespring.datasource.url=jdbc:h2:mem:batchdb# Prevent auto-start of jobs (optional)spring.batch.job.enabled=false

    💡 Note

    Spring Batch requires a database to store job metadata (JobRepository). H2 is great for development, but use a persistent database like PostgreSQL or MySQL in production.

    Spring Batch Architecture

    Spring Batch follows a layered architecture with three main components:

    1. Application Layer

    Your business logic - Jobs, Steps, Readers, Processors, Writers that you define.

    2. Batch Core

    Spring Batch runtime - JobLauncher, Job, Step implementations and execution handling.

    3. Batch Infrastructure

    Readers, Writers, retry/skip policies, and the JobRepository for persistence.

    Core Components
    ┌─────────────────────────────────────────────────┐
│                     JOB                         │
│  ┌─────────────────────────────────────────┐    │
│  │               STEP 1                     │    │
│  │  ┌─────────┐ ┌──────────┐ ┌──────────┐  │    │
│  │  │ Reader  │→│Processor │→│  Writer  │  │    │
│  │  └─────────┘ └──────────┘ └──────────┘  │    │
│  └─────────────────────────────────────────┘    │
│                      ↓                          │
│  ┌─────────────────────────────────────────┐    │
│  │               STEP 2                     │    │
│  │  ┌─────────┐ ┌──────────┐ ┌──────────┐  │    │
│  │  │ Reader  │→│Processor │→│  Writer  │  │    │
│  │  └─────────┘ └──────────┘ └──────────┘  │    │
│  └─────────────────────────────────────────┘    │
└─────────────────────────────────────────────────┘

    💬 Comments & Discussion