spring-batch/spring-batch-docs/asciidoc/spring-batch-integration.adoc

:batch-asciidoc: http://docs.spring.io/spring-batch/reference/html/
:toc: left
:toclevels: 4

[[springBatchIntegration]]

== Spring Batch Integration

[[spring-batch-integration-introduction]]

=== Spring Batch Integration Introduction

Many users of Spring Batch may encounter requirements that are
outside the scope of Spring Batch, yet may be efficiently and
concisely implemented using Spring Integration. Conversely, Spring
Batch users may encounter Spring Batch requirements and need a way
to efficiently integrate both frameworks. In this context several
patterns and use-cases emerge and Spring Batch Integration will
address those requirements.

The line between Spring Batch and Spring Integration is not always
clear, but there are guidelines that one can follow. Principally,
these are: think about granularity, and apply common patterns. Some
of those common patterns are described in this reference manual
section.

Adding messaging to a batch process enables automation of
operations, and also separation and strategizing of key concerns.
For example a message might trigger a job to execute, and then the
sending of the message can be exposed in a variety of ways. Or when
a job completes or fails that might trigger a message to be sent,
and the consumers of those messages might have operational concerns
that have nothing to do with the application itself. Messaging can
also be embedded in a job, for example reading or writing items for
processing via channels. Remote partitioning and remote chunking
provide methods to distribute workloads over an number of workers.


Some key concepts that we will cover are:

* <<spring-batch-integration.adoc#namespace-support,Namespace Support>>



* <<spring-batch-integration.adoc#launching-batch-jobs-through-messages,Launching Batch Jobs through Messages>>



* <<spring-batch-integration.adoc#providing-feedback-with-informational-messages,Providing Feedback with Informational Messages>>



* <<spring-batch-integration.adoc#asynchronous-processors,Asynchronous Processors>>



* <<spring-batch-integration.adoc#externalizing-batch-process-execution,Externalizing
Batch Process Execution>>


[[namespace-support]]

==== Namespace Support

Since Spring Batch Integration 1.3, dedicated XML Namespace
support was added, with the aim to provide an easier configuration
experience. In order to activate the namespace, add the following
namespace declarations to your Spring XML Application Context
file:

[source, xml]
----
<beans xmlns="http://www.springframework.org/schema/beans"
  xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xmlns:batch-int="http://www.springframework.org/schema/batch-integration"
  xsi:schemaLocation="
    http://www.springframework.org/schema/batch-integration
    http://www.springframework.org/schema/batch-integration/spring-batch-integration.xsd">

    ...

</beans>
----

A fully configured Spring XML Application Context file for Spring
Batch Integration may look like the following:

[source, xml]
----
<beans xmlns="http://www.springframework.org/schema/beans"
  xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xmlns:int="http://www.springframework.org/schema/integration"
  xmlns:batch="http://www.springframework.org/schema/batch"
  xmlns:batch-int="http://www.springframework.org/schema/batch-integration"
  xsi:schemaLocation="
    http://www.springframework.org/schema/batch-integration
    http://www.springframework.org/schema/batch-integration/spring-batch-integration.xsd
    http://www.springframework.org/schema/batch
    http://www.springframework.org/schema/batch/spring-batch.xsd
    http://www.springframework.org/schema/beans
    http://www.springframework.org/schema/beans/spring-beans.xsd
    http://www.springframework.org/schema/integration
    http://www.springframework.org/schema/integration/spring-integration.xsd">

    ...

</beans>
----

Appending version numbers to the referenced XSD file is also
allowed but, as a version-less declaration will always use the
latest schema, we generally don't recommend appending the version
number to the XSD name. Adding a version number, for instance,
would create possibly issues when updating the Spring Batch
Integration dependencies as they may require more recent versions
of the XML schema.


[[launching-batch-jobs-through-messages]]

==== Launching Batch Jobs through Messages


When starting batch jobs using the core Spring Batch API you
basically have 2 options:

* Command line via the `CommandLineJobRunner`
* Programatically via either `JobOperator.start()` or `JobLauncher.run()`.



For example, you may want to use the
`CommandLineJobRunner` when invoking Batch Jobs
using a shell script. Alternatively, you may use the
JobOperator directly, for example when using
Spring Batch as part of a web application. However, what about
more complex use-cases? Maybe you need to poll a remote (S)FTP
server to retrieve the data for the Batch Job. Or your application
has to support multiple different data sources simultaneously. For
example, you may receive data files not only via the web, but also
FTP etc. Maybe additional transformation of the input files is
needed before invoking Spring Batch.



Therefore, it would be much more powerful to execute the batch job
using Spring Integration and its numerous adapters. For example,
you can use a __File Inbound Channel Adapter__ to
monitor a directory in the file-system and start the Batch Job as
soon as the input file arrives. Additionally you can create Spring
Integration flows that use multiple different adapters to easily
ingest data for your Batch Jobs from multiple sources
simultaneously using configuration only. Implementing all these
scenarios with Spring Integration is easy as it allow for an
decoupled event-driven execution of the
`JobLauncher`.



Spring Batch Integration provides the
`JobLaunchingMessageHandler` class that you can
use to launch batch jobs. The input for the
`JobLaunchingMessageHandler` is provided by a
Spring Integration message, which payload is of type
JobLaunchRequest. This class is a wrapper around the Job
    that needs to be launched as well as the JobParameters
necessary to launch the Batch job.



The following image illustrates the typical Spring Integration
message flow in order to start a Batch job. The
link:$$http://www.eaipatterns.com/toc.html$$[EIP (Enterprise IntegrationPatterns) website]
provides a full overview of messaging icons and their descriptions.

.Launch Batch Job
image::{batch-asciidoc}images/launch-batch-job.png[Launch Batch Job, scaledwidth="60%"]


[[transforming-a-file-into-a-joblaunchrequest]]

===== Transforming a file into a JobLaunchRequest


[source, java]
----
package io.spring.sbi;

import org.springframework.batch.core.Job;
import org.springframework.batch.core.JobParametersBuilder;
import org.springframework.batch.integration.launch.JobLaunchRequest;
import org.springframework.integration.annotation.Transformer;
import org.springframework.messaging.Message;

import java.io.File;

public class FileMessageToJobRequest {
    private Job job;
    private String fileParameterName;

    public void setFileParameterName(String fileParameterName) {
        this.fileParameterName = fileParameterName;
    }

    public void setJob(Job job) {
        this.job = job;
    }

    @Transformer
    public JobLaunchRequest toRequest(Message<File> message) {
        JobParametersBuilder jobParametersBuilder =
            new JobParametersBuilder();

        jobParametersBuilder.addString(fileParameterName,
            message.getPayload().getAbsolutePath());

        return new JobLaunchRequest(job, jobParametersBuilder.toJobParameters());
    }
}
----

[[the-jobexecution-response]]

===== The JobExecution Response

When a Batch Job is being executed, a
`JobExecution` instance is returned. This
instance can be used to determine the status of an execution. If
a `JobExecution` was able to be created
successfully, it will always be returned, regardless of whether
or not the actual execution was successful.



The exact behavior on how the `JobExecution`
instance is returned depends on the provided
`TaskExecutor`. If a
`synchronous` (single-threaded)
`TaskExecutor` implementation is used, the
`JobExecution` response is only returned
`after` the job completes. When using an
`asynchronous`
`TaskExecutor`, the
`JobExecution` instance is returned
immediately. Users can then take the `id` of
`JobExecution` instance
(`JobExecution.getJobId()`) and query the
`JobRepository` for the job's updated status
using the `JobExplorer`. For more
information, please refer to the Spring
Batch reference documentation on
link:$$http://docs.spring.io/spring-batch/reference/html/configureJob.html#queryingRepository$$[Querying the Repository].



The following configuration will create a file
`inbound-channel-adapter` to listen for CSV
files in the provided directory, hand them off to our
transformer (`FileMessageToJobRequest`),
launch the job via the __Job Launching Gateway__ then simply log the output of the
`JobExecution` via the
`logging-channel-adapter`.


[[spring-batch-integration-configuration]]

===== Spring Batch Integration Configuration


[source, xml]
----
<int:channel id="inboundFileChannel"/>
<int:channel id="outboundJobRequestChannel"/>
<int:channel id="jobLaunchReplyChannel"/>

<int-file:inbound-channel-adapter id="filePoller"
    channel="inboundFileChannel"
    directory="file:/tmp/myfiles/"
    filename-pattern="*.csv">
  <int:poller fixed-rate="1000"/>
</int-file:inbound-channel-adapter>

<int:transformer input-channel="inboundFileChannel"
    output-channel="outboundJobRequestChannel">
  <bean class="io.spring.sbi.FileMessageToJobRequest">
    <property name="job" ref="personJob"/>
    <property name="fileParameterName" value="input.file.name"/>
  </bean>
</int:transformer>

<batch-int:job-launching-gateway request-channel="outboundJobRequestChannel"
    reply-channel="jobLaunchReplyChannel"/>

<int:logging-channel-adapter channel="jobLaunchReplyChannel"/>
----


Now that we are polling for files and launching jobs, we need to
configure for example our Spring Batch
`ItemReader` to utilize found file
represented by the job parameter "input.file.name":

[[example-itemreader-configuration]]

===== Example ItemReader Configuration


[source, xml]
----
<bean id="itemReader" class="org.springframework.batch.item.file.FlatFileItemReader"
    scope="step">
  <property name="resource" value="file://#{jobParameters['input.file.name']}"/>
    ...
</bean>
----


The main points of interest here are injecting the value of
`#{jobParameters['input.file.name']}`
as the Resource property value and setting the `ItemReader` bean
to be of __Step scope__ to take advantage of
the late binding support which allows access to the
`jobParameters` variable.


[[availableAttributesOfTheJobLaunchingGateway]]
=== Available Attributes of the Job-Launching Gateway

* `id` Identifies the underlying Spring bean definition, which is an instance of either:
** `EventDrivenConsumer`
** `PollingConsumer`

The exact implementation depends on whether the component's input channel is a:
`SubscribableChannel` or `PollableChannel`

* `auto-startup` Boolean flag to indicate that the endpoint should start automatically on
startup. The default is __true__.
* `request-channel` The input `MessageChannel` of this endpoint.
* `reply-channel` `Message Channel` to which the resulting `JobExecution` payload will be sent.
* `reply-timeout` Allows you to specify how long this gateway will wait for the reply message
to be sent successfully to the reply channel before throwing
an exception. This attribute only applies when the channel
might block, for example when using a bounded queue channel
that is currently full. Also, keep in mind that when sending to a
`DirectChannel`, the invocation will occur
in the sender's thread. Therefore, the failing of the send
operation may be caused by other components further downstream.
The `reply-timeout` attribute maps to the
`sendTimeout` property of the underlying
`MessagingTemplate` instance. The attribute
will default, if not specified, to<emphasis>-1</emphasis>,
meaning that by default, the `Gateway` will wait indefinitely.
The value is specified in milliseconds.
* `job-launcher` Pass in a
custom
`JobLauncher`
bean reference. This
attribute is optional. If not specified the adapter will
re-use the instance that is registered under the id
`jobLauncher`. If no default instance
exists an exception is thrown.
* `order` Specifies the order for invocation when this endpoint is connected as a subscriber
to a `SubscribableChannel`.

=== Sub-Elements
When this `Gateway` is receiving messages from a
`PollableChannel`, you must either provide
a global default Poller or provide a Poller sub-element to the
`Job Launching Gateway`:
[source, xml]
----
<batch-int:job-launching-gateway request-channel="queueChannel"
    reply-channel="replyChannel" job-launcher="jobLauncher">
  <int:poller fixed-rate="1000">
</batch-int:job-launching-gateway>
----

[[providing-feedback-with-informational-messages]]

==== Providing Feedback with Informational Messages


As Spring Batch jobs can run for long times, providing progress
information will be critical. For example, stake-holders may want
to be notified if a some or all parts of a Batch Job has failed.
Spring Batch provides support for this information being gathered
through:



* Active polling or

* Event-driven, using listeners.


When starting a Spring Batch job asynchronously, e.g. by using the
`Job Launching Gateway`, a
`JobExecution` instance is returned. Thus,
`JobExecution.getJobId()` can be used to
continuously poll for status updates by retrieving updated
instances of the `JobExecution` from the
`JobRepository` using the
`JobExplorer`. However, this is considered
sub-optimal and an event-driven approach should be preferred.


Therefore, Spring Batch provides listeners such as:

* StepListener
* ChunkListener
* JobExecutionListener

In the following example, a Spring Batch job was configured with a
`StepExecutionListener`. Thus, Spring
Integration will receive and process any step before/after step
events. For example, the received
`StepExecution` can be inspected using a
`Router`. Based on the results of that
inspection, various things can occur for example routing a message
to a Mail Outbound Channel Adapter, so that an Email notification
can be sent out based on some condition.

.Handling Informational Messages
image::{batch-asciidoc}images/handling-informational-messages.png[Handling Informational Messages, scaledwidth="60%"]


Below is an example of how a listener is configured to send a
message to a `Gateway` for
`StepExecution` events and log its output to a
`logging-channel-adapter`:

First create the notifications integration beans:

[source, xml]
----
<int:channel id="stepExecutionsChannel"/>

<int:gateway id="notificationExecutionsListener"
    service-interface="org.springframework.batch.core.StepExecutionListener"
    default-request-channel="stepExecutionsChannel"/>

<int:logging-channel-adapter channel="stepExecutionsChannel"/>
----


Then modify your job to add a step level listener:

[source, xml]
----
<job id="importPayments">
    <step id="step1">
        <tasklet ../>
            <chunk ../>
            <listeners>
                <listener ref="notificationExecutionsListener"/>
            </listeners>
        </tasklet>
        ...
    </step>
</job>
----

[[asynchronous-processors]]

==== Asynchronous Processors


Asynchronous Processors help you to to scale the processing of
items. In the asynchronous processor use-case, an
`AsyncItemProcessor` serves as a dispatcher,
executing the `ItemProcessor's` logic for an
item on a new thread. The `Future` is passed to
the AsynchItemWriter to be written once the
processor completes.



Therefore, you can increase performance by using asynchronous item
processing, basically allowing you to implement
__fork-join__ scenarios. The
`AsyncItemWriter` will gather the results and
write back the chunk as soon as all the results become available.



Configuration of both the `AsyncItemProcessor`
and `AsyncItemWriter` are simple, first the
`AsyncItemProcessor`:
			


[source, xml]
----
<bean id="processor"
    class="org.springframework.batch.integration.async.AsyncItemProcessor">
  <property name="delegate">
    <bean class="your.ItemProcessor"/>
  </property>
  <property name="taskExecutor">
    <bean class="org.springframework.core.task.SimpleAsyncTaskExecutor"/>
  </property>
</bean>
----


The property "`delegate`" is actually
a reference to your `ItemProcessor` bean and
the "taskExecutor" property is a
reference to the `TaskExecutor` of your choice.

Then we configure the `AsyncItemWriter`:

[source, xml]
----
<bean id="itemWriter"
    class="org.springframework.batch.integration.async.AsyncItemWriter">
  <property name="delegate">
    <bean id="itemWriter" class="your.ItemWriter"/>
  </property>
</bean>
----


Again, the property "`delegate`" is
actually a reference to your `ItemWriter` bean.


[[externalizing-batch-process-execution]]

==== Externalizing Batch Process Execution


The integration approaches discussed so far suggest use-cases
where Spring Integration wraps Spring Batch like an outer-shell.
However, Spring Batch can also use Spring Integration internally.
Using this approach, Spring Batch users can delegate the
processing of items or even chunks to outside processes. This
allows you to offload complex processing. Spring Batch Integration
provides dedicated support for:



* Remote Chunking



* Remote Partitioning


[[remote-chunking]]

===== Remote Chunking

.Remote Chunking
image::{batch-asciidoc}images/remote-chunking-sbi.png[Remote Chunking, scaledwidth="60%"]

Taking things one step further, one can also externalize the
chunk processing using the
`ChunkMessageChannelItemWriter` which is
provided by Spring Batch Integration which will send items out
and collect the result. Once sent, Spring Batch will continue the
process of reading and grouping items, without waiting for the results.
Rather it is the responsibility of the `ChunkMessageChannelItemWriter`
to gather the results and integrate them back into the Spring Batch process.


Using Spring Integration you have full
control over the concurrency of your processes, for instance by
using a `QueueChannel` instead of a
`DirectChannel`. Furthermore, by relying on
Spring Integration's rich collection of Channel Adapters (E.g.
JMS or AMQP), you can distribute chunks of a Batch job to
external systems for processing.

A simple job with a step to be remotely chunked would have a
configuration similar to the following:

[source, xml]
----
<job id="personJob">
  <step id="step1">
    <tasklet>
      <chunk reader="itemReader" writer="itemWriter" commit-interval="200"/>
    </tasklet>
    ...
  </step>
</job>
----

The `ItemReader` reference would point to the bean you would like
to use for reading data on the master. The `ItemWriter` reference
points to a special `ItemWriter`
"`ChunkMessageChannelItemWriter`"
as described above. The processor (if any) is left off the
master configuration as it is configured on the slave. The
following configuration provides a basic master setup. It's
advised to check any additional component properties such as
throttle limits and so on when implementing your use case.

[source, xml]
----
<bean id="connectionFactory" class="org.apache.activemq.ActiveMQConnectionFactory">
  <property name="brokerURL" value="tcp://localhost:61616"/>
</bean>

<int-jms:outbound-channel-adapter id="requests" destination-name="requests"/>

<bean id="messagingTemplate"
    class="org.springframework.integration.core.MessagingTemplate">
  <property name="defaultChannel" ref="requests"/>
  <property name="receiveTimeout" value="2000"/>
</bean>

<bean id="itemWriter"
    class="org.springframework.batch.integration.chunk.ChunkMessageChannelItemWriter"
    scope="step">
  <property name="messagingOperations" ref="messagingTemplate"/>
  <property name="replyChannel" ref="replies"/>
</bean>

<bean id="chunkHandler"
    class="org.springframework.batch.integration.chunk.RemoteChunkHandlerFactoryBean">
  <property name="chunkWriter" ref="itemWriter"/>
  <property name="step" ref="step1"/>
</bean>

<int:channel id="replies">
  <int:queue/>
</int:channel>

<int-jms:message-driven-channel-adapter id="jmsReplies"
    destination-name="replies"
    channel="replies"/>
----


This configuration provides us with a number of beans. We
configure our messaging middleware using ActiveMQ and
inbound/outbound JMS adapters provided by Spring Integration. As
shown, our `itemWriter` bean which is
referenced by our job step utilizes the
`ChunkMessageChannelItemWriter` for writing chunks over the
configured middleware.

Now lets move on to the slave configuration:



[source, xml]
----
<bean id="connectionFactory" class="org.apache.activemq.ActiveMQConnectionFactory">
  <property name="brokerURL" value="tcp://localhost:61616"/>
</bean>

<int:channel id="requests"/>
<int:channel id="replies"/>

<int-jms:message-driven-channel-adapter id="jmsIn"
    destination-name="requests"
    channel="requests"/>

<int-jms:outbound-channel-adapter id="outgoingReplies"
    destination-name="replies"
    channel="replies">
</int-jms:outbound-channel-adapter>

<int:service-activator id="serviceActivator"
    input-channel="requests"
    output-channel="replies"
    ref="chunkProcessorChunkHandler"
    method="handleChunk"/>

<bean id="chunkProcessorChunkHandler"
    class="org.springframework.batch.integration.chunk.ChunkProcessorChunkHandler">
  <property name="chunkProcessor">
    <bean class="org.springframework.batch.core.step.item.SimpleChunkProcessor">
      <property name="itemWriter">
        <bean class="io.spring.sbi.PersonItemWriter"/>
      </property>
      <property name="itemProcessor">
        <bean class="io.spring.sbi.PersonItemProcessor"/>
      </property>
    </bean>
  </property>
</bean>
----


Most of these configuration items should look familiar from the
master configuration. Slaves do not need access to things like
the Spring Batch `JobRepository` nor access
to the actual job configuration file. The main bean of interest
is the "`chunkProcessorChunkHandler`". The
`chunkProcessor` property of `ChunkProcessorChunkHandler` takes a
configured `SimpleChunkProcessor` which is where you would provide a reference to your
`ItemWriter` and optionally your
`ItemProcessor` that will run on the slave
when it receives chunks from the master.

For more information, please also consult the Spring Batch
manual, specifically the chapter on
link:$$http://docs.spring.io/spring-batch/reference/html/scalability.html#remoteChunking$$[Remote Chunking].


[[remote-partitioning]]

===== Remote Partitioning

.Remote Partitioning
image::{batch-asciidoc}images/remote-partitioning.png[Remote Partitioning, scaledwidth="60%"]


Remote Partitioning, on the other hand, is useful when the
problem is not the processing of items, but the associated I/O
represents the bottleneck. Using Remote Partitioning, work can
be farmed out to slaves that execute complete Spring Batch
steps. Thus, each slave has its own `ItemReader`, `ItemProcessor` and
`ItemWriter`. For this purpose, Spring Batch
Integration provides the `MessageChannelPartitionHandler`.



This implementation of the `PartitionHandler`
interface uses MessageChannel instances to
send instructions to remote workers and receive their responses.
This provides a nice abstraction from the transports (E.g. JMS
or AMQP) being used to communicate with the remote workers.



The reference manual section
link:$$http://docs.spring.io/spring-batch/reference/html/scalability.html#partitioning$$[Remote Partitioning] provides an overview of the concepts and
components needed to configure Remote Partitioning and shows an
example of using the default
`TaskExecutorPartitionHandler` to partition
in separate local threads of execution. For Remote Partitioning
to multiple JVM's, two additional components are required:

* Remoting fabric or grid environment
* A `PartitionHandler` implementation that supports the desired
remoting fabric or grid environment



Similar to Remote Chunking JMS can be used as the "remoting
fabric" and the `PartitionHandler` implementation to be used
as described above is the
`MessageChannelPartitionHandler`. The example
shown below assumes an existing partitioned job and focuses on
the `MessageChannelPartitionHandler` and JMS
configuration:



[source, xml]
----
<bean id="partitionHandler"
   class="org.springframework.batch.integration.partition.MessageChannelPartitionHandler">
  <property name="stepName" value="step1"/>
  <property name="gridSize" value="3"/>
  <property name="replyChannel" ref="outbound-replies"/>
  <property name="messagingOperations">
    <bean class="org.springframework.integration.core.MessagingTemplate">
      <property name="defaultChannel" ref="outbound-requests"/>
      <property name="receiveTimeout" value="100000"/>
    </bean>
  </property>
</bean>

<int:channel id="outbound-requests"/>
<int-jms:outbound-channel-adapter destination="requestsQueue"
    channel="outbound-requests"/>

<int:channel id="inbound-requests"/>
<int-jms:message-driven-channel-adapter destination="requestsQueue"
    channel="inbound-requests"/>

<bean id="stepExecutionRequestHandler"
    class="org.springframework.batch.integration.partition.StepExecutionRequestHandler">
  <property name="jobExplorer" ref="jobExplorer"/>
  <property name="stepLocator" ref="stepLocator"/>
</bean>

<int:service-activator ref="stepExecutionRequestHandler" input-channel="inbound-requests"
    output-channel="outbound-staging"/>

<int:channel id="outbound-staging"/>
<int-jms:outbound-channel-adapter destination="stagingQueue"
    channel="outbound-staging"/>

<int:channel id="inbound-staging"/>
<int-jms:message-driven-channel-adapter destination="stagingQueue"
    channel="inbound-staging"/>

<int:aggregator ref="partitionHandler" input-channel="inbound-staging"
    output-channel="outbound-replies"/>

<int:channel id="outbound-replies">
  <int:queue/>
</int:channel>

<bean id="stepLocator"
    class="org.springframework.batch.integration.partition.BeanFactoryStepLocator" />
----

Also ensure the partition `handler` attribute maps to the `partitionHandler` bean:

[source, xml]
----
<job id="personJob">
  <step id="step1.master">
    <partition partitioner="partitioner" handler="partitionHandler"/>
    ...
  </step>
</job>
----