The simplest way to start parallel processing is to add a TaskExecutor to your Step configuration, e.g. as an attribute of the tasklet:

<step id="loading">
    <tasklet reader="stagingReader" 
             processor="stagingProcessor" 
             writer="tradeWriter" 
             commit-interval="1" 
             task-executor="taskExecutor"/>
</step>

In this example the taskExecutor is a reference to another bean definition, implementing the TaskExecutor interface. TaskExecutor is a standard Spring interface, so consult the Spring User Guide for details of available implementations. The simplest multi-threaded TaskExecutor is a SimpleAsyncTaskExecutor.

The result of the above configuration will be that the Step executes by reading, processing and writing each chunk of items (each commit interval) in a separate thread of execution.

There are some practical limitations of using multi-threaded Steps for some common Batch use cases. Many participants in a Step (e.g. readers and writers) are stateful, and if the state is not segregated by thread, then those components are not usable in a multi-threaded Step. In particular most of the off-the-shelf readers and writers from Spring Batch are not designed for multi-threaded use. It is, however, possible to work with stateless or thread safe readers and writers, and there is a sample (parallelJob) in the Spring Batch Samples that show the use of a process indicator (see Section 6.12, “Preventing State Persistence”) to keep track of items that have been processed in a database input table.

As long as the application logic that needs to be parallelized can be split into distinct responsibilities, and assigned to individual steps then it can be parallelized in a single process. Parallel Step execution is easy to configure and use, for example, to execute steps (step1,step2) in parallel with step3, you could configure a flow like this:

<job id="job1">
    <split id="split1" task-executor="taskExecutor" next="step4">
        <flow>
            <step id="step1" parent="s1" next="step2"/>
            <step id="step2" parent="s2"/>
        </flow>
        <flow>
            <step id="step3" parent="s3"/>
        </flow>
    </split>
    <step id="step4" parent="s4"/>
</job>

<beans:bean id="taskExecutor" class="org.spr...SimpleAsyncTaskExecutor"/>

The configurable "task-executor" attribute is used to specify which TaskExecutor implementation should be used to execute the individual flows. The default is SyncTaskExecutor, but an asynchronous TaskExecutor is required to run the steps in parallel. Note that the job will ensure that every flow in the split completes before aggregating the exit statuses and transitioning.

See the section on Section 5.3.5, “Split Flows” for more detail.

In Remote Chunking the Step processing is split across multiple processes, communicating with each other through some middleware. Here is a picture of the pattern in action:

The Master component is a single process, and the Slaves are multiple remote processes. Clearly this pattern works best if the Master is not a bottleneck, so the processing must be more expensive than the reading of items (this is often the case in practice).

The Master is just an implementation of a Spring Batch Step, with the ItemWriter replaced with a generic version that knows how to send chunks of items to the middleware as messages. The Slaves are standard listeners for whatever middleware is being used (e.g. with JMS they would be MesssageListeners), and their role is to process the chunks of items using a standard ItemWriter or ItemProcessor plus ItemWriter, through the ChunkProcessor interface. One of the advantages of using this pattern is that the reader, processor and writer components are off-the-shelf (the same as would be used for a local execution of the step). The items are divided up dynamically and work is shared through the middleware, so if the listeners are all eager consumers, then load balancing is automatic.

The middleware has to be durable, with guaranteed delivery and single consumer for each message. JMS is the obvious candidate, but other options exist in the grid computing and shared memory product space (e.g. Java Spaces).

Spring Batch has a sub-project (Spring Batch Integration), providing implementations of various patterns like this one using Spring Integration. Spring Batch Integration is available in subversion for people to use, but is not intended to be part of the official general release of Spring Batch until it builds up more of a community of users.

Spring Batch also provides an SPI for partitioning a Step execution and executing it remotely. In this case the remote participants are simply Step instances that could just as easily have been configured and used for local processing. Here is a picture of the pattern in action:

The Job is executing on the left hand side as a sequence of Steps, and one of the Steps is labelled as a Master. The Slaves in this picture are all identical instances of a Step, which could in fact take the place of the Master resulting in the same outcome for the Job. The Slaves are typically going to be remote services, but could also be local threads of execution. The messages sent by the Master to the Slaves in this pattern do not need to be durable, or have guaranteed delivery: Spring Batch meta-data in the JobRepository will ensure that each Slave is executed once and only once for each Job execution.

The SPI in Spring Batch consists of a special implementation of Step (the PartitionStep), and two strategy interfaces that need to be implemented for the specific environment. The strategy interfaces are PartitionHandler and StepExecutionSplitter, and their role is show in the sequence diagram below:

The Step on the right in this case is the "remote" Slave, so potentially there are many objects and or processes playing this role, and the PartitionStep is shown driving the execution. The PartitionStep configuration looks like this:

<bean name="step1:master" class="org.sfw...PartitionStep">
    <property name="partitionHandler" ref="partitionHandler"/>
    <property name="stepExecutionSplitter" ref="stepExecutionSplitter"/>
    <property name="jobRepository" ref="jobRepository" />
</bean>

There is a simple example which can be copied and extended in the unit test suite for Spring Batch Core (see org.springframework.batch.core.partition package).

<bean class="org.spr...TaskExecutorPartitionHandler">
    <property name="taskExecutor" ref="taskExecutor"/>
    <property name="step" ref="step1" />
    <property name="gridSize" value="10" />
</bean>

public interface StepExecutionSplitter {
    ...
    Set<StepExecution> split(StepExecution stepExecution, int gridSize) 
          throws JobExecutionException;
}

public interface Partitioner {
    Map<String, ExecutionContext> partition(int gridSize);
}

<bean id="itemReader" scope="step"
      class="org.spr...MultiResourceItemReader">
    <property name="resource" value="#{stepExecutionContext[fileName]}/*"/>
</bean>