Master Spring Batch: Core Concepts, Architecture, and Best Practices

Spring Batch Overview

Spring Batch is a lightweight, comprehensive data‑processing framework provided by Spring, designed for enterprise batch jobs that run without user interaction. Typical scenarios include time‑based events (e.g., month‑end calculations), large‑scale repetitive processing (e.g., insurance calculations), and integration of data from internal or external systems.

Key Features

Spring Batch offers reusable capabilities essential for high‑volume processing, such as record tracking, transaction management, job statistics, restartability, skip logic, and resource management. It also provides advanced services like optimization and partitioning to achieve high throughput.

Typical Architecture

A batch application generally follows three steps: read a large number of records from a database, file, or queue; process the data; and write the transformed data back. The following diagram illustrates this flow.

The overall Spring Batch architecture is shown below.

Job and Step Model

A Job consists of multiple Steps, each defining its own ItemReader (to read data), ItemProcessor (to apply business logic), and ItemWriter (to write data). Jobs are stored in a JobRepository and launched via a JobLauncher.

Core Concepts

Job

public interface Job {
    String getName();
    boolean isRestartable();
    void execute(JobExecution execution);
    JobParametersIncrementer getJobParametersIncrementer();
    JobParametersValidator getJobParametersValidator();
}

JobInstance

public interface JobInstance {
    long getInstanceId();
    String getJobName();
}

JobParameters

JobParameters identify a specific execution of a Job (e.g., a date stamp for a daily “EndOfDay” job).

JobExecution

public interface JobExecution {
    long getExecutionId();
    String getJobName();
    BatchStatus getBatchStatus();
    Date getStartTime();
    Date getEndTime();
    String getExitStatus();
    Date getCreateTime();
    Date getLastUpdatedTime();
    Properties getJobParameters();
}

Step and StepExecution

A Step represents a distinct phase of a Job. Each execution of a Step is captured by a StepExecution, which stores statistics, timestamps, and an ExecutionContext (a key‑value map).

ItemReader / ItemProcessor / ItemWriter

Spring Batch provides many ready‑made implementations (e.g., JdbcPagingItemReader, JdbcCursorItemReader) and allows custom implementations.

@Bean
public JdbcPagingItemReader itemReader(DataSource dataSource, PagingQueryProvider queryProvider) {
    Map<String, Object> params = new HashMap<>();
    params.put("status", "NEW");
    return new JdbcPagingItemReaderBuilder<CustomerCredit>()
        .name("creditReader")
        .dataSource(dataSource)
        .queryProvider(queryProvider)
        .parameterValues(params)
        .rowMapper(customerCreditMapper())
        .pageSize(1000)
        .build();
}

Chunk Processing

Spring Batch can group items into chunks; after a configured chunk size is reached, the transaction is committed.

Skip and Failure Handling

Skip policies let you define how many exceptions a step may ignore ( skipLimit), which exceptions to skip ( skip), and which to treat as fatal ( noSkip).

Best‑Practice Guidelines

Keep batch architecture simple and avoid overly complex logic.

Process data close to where it is stored to reduce I/O.

Minimize system resource usage, especially I/O, by caching data when possible.

Avoid duplicate processing; aggregate results during the initial pass.

Allocate sufficient memory at startup to prevent costly reallocations.

Assume worst‑case data integrity and add validation checks.

Plan and execute performance tests with realistic data volumes.

Ensure reliable backup strategies for both databases and files.

Common Configuration Tips

Disable Auto‑Start

To prevent a job from running automatically on application start, set:

spring.batch.job.enabled=false

Handle Memory Exhaustion

If a reader loads all records into memory, switch to a paging reader or increase JVM heap size to avoid Resource exhaustion errors.

Do you have any additional questions?