This guide walks you through the process of creating a basic batch-driven solution.

What You Will build

You will build a service that imports data from a CSV spreadsheet, transforms it with custom code, and stores the final results in a database.

What you’ll need

How to complete this guide

Like most Spring Getting Started guides, you can start from scratch and complete each step or you can bypass basic setup steps that are already familiar to you. Either way, you end up with working code.

To start from scratch, move on to Starting with Spring Initializr.

To skip the basics, do the following:

When you finish, you can check your results against the code in gs-batch-processing/complete.

Business Data

Typically, your customer or a business analyst supplies a spreadsheet. For this simple example, you can find some made-up data in src/main/resources/sample-data.csv:


This spreadsheet contains a first name and a last name on each row, separated by a comma. This is a fairly common pattern that Spring can handle without customization.

Next, you need to write an SQL script to create a table to store the data. You can find such a script in src/main/resources/schema-all.sql:


CREATE TABLE people  (
    first_name VARCHAR(20),
    last_name VARCHAR(20)
Spring Boot runs [email protected]@[email protected]@.sql automatically during startup. -all is the default for all platforms.

Starting with Spring Initializr

For all Spring applications, you should start with the Spring Initializr. The Initializr offers a fast way to pull in all the dependencies you need for an application and does a lot of the set up for you. This example needs the Spring Batch and HyperSQL Database dependencies.

The following listing shows the pom.xml file created when you choose Maven:

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="" xmlns:xsi=""
		<relativePath/> <!-- lookup parent from repository -->
	<description>Demo project for Spring Boot</description>






The following listing shows the build.gradle file created when you choose Gradle:

plugins {
	id 'org.springframework.boot' version '2.2.2.RELEASE'
	id 'io.spring.dependency-management' version '1.0.8.RELEASE'
	id 'java'

group = 'com.example'
version = '0.0.1-SNAPSHOT'
sourceCompatibility = '1.8'

repositories {

dependencies {
	implementation 'org.springframework.boot:spring-boot-starter-batch'
	runtimeOnly 'org.hsqldb:hsqldb'
	testImplementation('org.springframework.boot:spring-boot-starter-test') {
		exclude group: 'org.junit.vintage', module: 'junit-vintage-engine'
	testImplementation 'org.springframework.batch:spring-batch-test'

test {

Create a Business Class

Now that you can see the format of data inputs and outputs, you can write code to represent a row of data, as the following example (from src/main/java/com/example/batchprocessing/ shows:

package com.example.batchprocessing;

public class Person {

  private String lastName;
  private String firstName;

  public Person() {

  public Person(String firstName, String lastName) {
    this.firstName = firstName;
    this.lastName = lastName;

  public void setFirstName(String firstName) {
    this.firstName = firstName;

  public String getFirstName() {
    return firstName;

  public String getLastName() {
    return lastName;

  public void setLastName(String lastName) {
    this.lastName = lastName;

  public String toString() {
    return "firstName: " + firstName + ", lastName: " + lastName;


You can instantiate the Person class either with first and last name through a constructor or by setting the properties.

Create an Intermediate Processor

A common paradigm in batch processing is to ingest data, transform it, and then pipe it out somewhere else. Here, you need to write a simple transformer that converts the names to uppercase. The following listing (from src/main/java/com/example/batchprocessing/ shows how to do so:

package com.example.batchprocessing;

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import org.springframework.batch.item.ItemProcessor;

public class PersonItemProcessor implements ItemProcessor<Person, Person> {

  private static final Logger log = LoggerFactory.getLogger(PersonItemProcessor.class);

  public Person process(final Person person) throws Exception {
    final String firstName = person.getFirstName().toUpperCase();
    final String lastName = person.getLastName().toUpperCase();

    final Person transformedPerson = new Person(firstName, lastName);"Converting (" + person + ") into (" + transformedPerson + ")");

    return transformedPerson;


PersonItemProcessor implements Spring Batch’s ItemProcessor interface. This makes it easy to wire the code into a batch job that you will define later in this guide. According to the interface, you receive an incoming Person object, after which you transform it to an upper-cased Person.

The input and output types need not be the same. In fact, after one source of data is read, sometimes the application’s data flow needs a different data type.

Put Together a Batch Job

Now you need to put together the actual batch job. Spring Batch provides many utility classes that reduce the need to write custom code. Instead, you can focus on the business logic.

To configure your job, you must first create a Spring @Configuration class like the following example in src/main/java/com/exampe/batchprocessing/

public class BatchConfiguration {

  public JobBuilderFactory jobBuilderFactory;

  public StepBuilderFactory stepBuilderFactory;



For starters, the @EnableBatchProcessing annotation adds many critical beans that support jobs and save you a lot of leg work. This example uses a memory-based database (provided by @EnableBatchProcessing), meaning that, when it is done, the data is gone. It also autowires a couple factories needed further below. Now add the following beans to your BatchConfiguration class to define a reader, a processor, and a writer:

public FlatFileItemReader<Person> reader() {
  return new FlatFileItemReaderBuilder<Person>()
    .resource(new ClassPathResource("sample-data.csv"))
    .names(new String[]{"firstName", "lastName"})
    .fieldSetMapper(new BeanWrapperFieldSetMapper<Person>() {{

public PersonItemProcessor processor() {
  return new PersonItemProcessor();

public JdbcBatchItemWriter<Person> writer(DataSource dataSource) {
  return new JdbcBatchItemWriterBuilder<Person>()
    .itemSqlParameterSourceProvider(new BeanPropertyItemSqlParameterSourceProvider<>())
    .sql("INSERT INTO people (first_name, last_name) VALUES (:firstName, :lastName)")

The first chunk of code defines the input, processor, and output.

  • reader() creates an ItemReader. It looks for a file called sample-data.csv and parses each line item with enough information to turn it into a Person.

  • processor() creates an instance of the PersonItemProcessor that you defined earlier, meant to convert the data to upper case.

  • writer(DataSource) creates an ItemWriter. This one is aimed at a JDBC destination and automatically gets a copy of the dataSource created by @EnableBatchProcessing. It includes the SQL statement needed to insert a single Person, driven by Java bean properties.

The last chunk (from src/main/java/com/example/batchprocessing/ shows the actual job configuration:

public Job importUserJob(JobCompletionNotificationListener listener, Step step1) {
  return jobBuilderFactory.get("importUserJob")
    .incrementer(new RunIdIncrementer())

public Step step1(JdbcBatchItemWriter<Person> writer) {
  return stepBuilderFactory.get("step1")
    .<Person, Person> chunk(10)

The first method defines the job, and the second one defines a single step. Jobs are built from steps, where each step can involve a reader, a processor, and a writer.

In this job definition, you need an incrementer, because jobs use a database to maintain execution state. You then list each step, (though this job has only one step). The job ends, and the Java API produces a perfectly configured job.

In the step definition, you define how much data to write at a time. In this case, it writes up to ten records at a time. Next, you configure the reader, processor, and writer by using the beans injected earlier.

chunk() is prefixed <Person,Person> because it is a generic method. This represents the input and output types of each “chunk” of processing and lines up with ItemReader<Person> and ItemWriter<Person>.

The last bit of batch configuration is a way to get notified when the job completes. The following example (from src/main/java/com/example/batchprocessing/ shows such a class:

package com.example.batchprocessing;

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.batch.core.BatchStatus;
import org.springframework.batch.core.JobExecution;
import org.springframework.batch.core.listener.JobExecutionListenerSupport;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.jdbc.core.JdbcTemplate;
import org.springframework.stereotype.Component;

public class JobCompletionNotificationListener extends JobExecutionListenerSupport {

  private static final Logger log = LoggerFactory.getLogger(JobCompletionNotificationListener.class);

  private final JdbcTemplate jdbcTemplate;

  public JobCompletionNotificationListener(JdbcTemplate jdbcTemplate) {
    this.jdbcTemplate = jdbcTemplate;

  public void afterJob(JobExecution jobExecution) {
    if(jobExecution.getStatus() == BatchStatus.COMPLETED) {"!!! JOB FINISHED! Time to verify the results");

      jdbcTemplate.query("SELECT first_name, last_name FROM people",
        (rs, row) -> new Person(
      ).forEach(person ->"Found <" + person + "> in the database."));

The JobCompletionNotificationListener listens for when a job is BatchStatus.COMPLETED and then uses JdbcTemplate to inspect the results.

Make the Application Executable

Although batch processing can be embedded in web apps and WAR files, the simpler approach demonstrated below creates a standalone application. You package everything in a single, executable JAR file, driven by a good old Java main() method.

The Spring Initializr created an application class for you. For this simple example, it works without further modification. The following listing (from src/main/java/com/example/batchprocessing/ shows the application class:

package com.example.batchprocessing;

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;

public class BatchProcessingApplication {

  public static void main(String[] args) throws Exception {
    System.exit(SpringApplication.exit(, args)));

@SpringBootApplication is a convenience annotation that adds all of the following:

  • @Configuration: Tags the class as a source of bean definitions for the application context.

  • @EnableAutoConfiguration: Tells Spring Boot to start adding beans based on classpath settings, other beans, and various property settings. For example, if spring-webmvc is on the classpath, this annotation flags the application as a web application and activates key behaviors, such as setting up a DispatcherServlet.

  • @ComponentScan: Tells Spring to look for other components, configurations, and services in the com/example package, letting it find the controllers.

The main() method uses Spring Boot’s method to launch an application. Did you notice that there was not a single line of XML? There is no web.xml file, either. This web application is 100% pure Java and you did not have to deal with configuring any plumbing or infrastructure.

Note that SpringApplication.exit() and System.exit() ensure that the JVM exits upon job completion. See the Application Exit section in Spring Boot Reference documentation for more details.

For demonstration purposes, there is code to create a JdbcTemplate, query the database, and print out the names of people the batch job inserts.

Build an executable JAR

You can run the application from the command line with Gradle or Maven. You can also build a single executable JAR file that contains all the necessary dependencies, classes, and resources and run that. Building an executable jar makes it easy to ship, version, and deploy the service as an application throughout the development lifecycle, across different environments, and so forth.

If you use Gradle, you can run the application by using ./gradlew bootRun. Alternatively, you can build the JAR file by using ./gradlew build and then run the JAR file, as follows:

java -jar build/libs/gs-batch-processing-0.1.0.jar

If you use Maven, you can run the application by using ./mvnw spring-boot:run. Alternatively, you can build the JAR file with ./mvnw clean package and then run the JAR file, as follows:

java -jar target/gs-batch-processing-0.1.0.jar
The steps described here create a runnable JAR. You can also build a classic WAR file.

The job prints out a line for each person that gets transformed. After the job runs, you can also see the output from querying the database. It should resemble the following output:

Converting (firstName: Jill, lastName: Doe) into (firstName: JILL, lastName: DOE)
Converting (firstName: Joe, lastName: Doe) into (firstName: JOE, lastName: DOE)
Converting (firstName: Justin, lastName: Doe) into (firstName: JUSTIN, lastName: DOE)
Converting (firstName: Jane, lastName: Doe) into (firstName: JANE, lastName: DOE)
Converting (firstName: John, lastName: Doe) into (firstName: JOHN, lastName: DOE)
Found <firstName: JILL, lastName: DOE> in the database.
Found <firstName: JOE, lastName: DOE> in the database.
Found <firstName: JUSTIN, lastName: DOE> in the database.
Found <firstName: JANE, lastName: DOE> in the database.
Found <firstName: JOHN, lastName: DOE> in the database.


Congratulations! You built a batch job that ingested data from a spreadsheet, processed it, and wrote it to a database.

See also

The following guides may also be helpful:

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