Common Patterns
Common Batch Patterns
Some batch jobs can be assembled purely from off-the-shelf components in Spring Batch.
For instance, the ItemReader and ItemWriter implementations can be configured to
cover a wide range of scenarios. However, for the majority of cases, custom code must be
written. The main API entry points for application developers are the Tasklet, the
ItemReader, the ItemWriter, and the various listener interfaces. Most simple batch
jobs can use off-the-shelf input from a Spring Batch ItemReader, but it is often the
case that there are custom concerns in the processing and writing that require developers
to implement an ItemWriter or ItemProcessor.
In this chapter, we provide a few examples of common patterns in custom business logic.
These examples primarily feature the listener interfaces. It should be noted that an
ItemReader or ItemWriter can implement a listener interface as well, if appropriate.
Logging Item Processing and Failures
A common use case is the need for special handling of errors in a step, item by item,
perhaps logging to a special channel or inserting a record into a database. A
chunk-oriented Step (created from the step factory beans) lets users implement this use
case with a simple ItemReadListener for errors on read and an ItemWriteListener for
errors on write. The following code snippet illustrates a listener that logs both read
and write failures:
public class ItemFailureLoggerListener extends ItemListenerSupport {
private static Log logger = LogFactory.getLog("item.error");
public void onReadError(Exception ex) {
logger.error("Encountered error on read", e);
}
public void onWriteError(Exception ex, List<? extends Object> items) {
logger.error("Encountered error on write", ex);
}
}
Having implemented this listener, it must be registered with a step.
The following example shows how to register a listener with a step in XML:
<step id="simpleStep">
...
<listeners>
<listener>
<bean class="org.example...ItemFailureLoggerListener"/>
</listener>
</listeners>
</step>The following example shows how to register a listener with a step Java:
@Bean
public Step simpleStep(JobRepository jobRepository) {
return new StepBuilder("simpleStep", jobRepository)
...
.listener(new ItemFailureLoggerListener())
.build();
}
if your listener does anything in an onError() method, it must be inside
a transaction that is going to be rolled back. If you need to use a transactional
resource, such as a database, inside an onError() method, consider adding a declarative
transaction to that method (see Spring Core Reference Guide for details), and giving its
propagation attribute a value of REQUIRES_NEW.
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Stopping a Job Manually for Business Reasons
Spring Batch provides a stop() method through the JobOperator interface, but this is
really for use by the operator rather than the application programmer. Sometimes, it is
more convenient or makes more sense to stop a job execution from within the business
logic.
The simplest thing to do is to throw a RuntimeException (one that is neither retried
indefinitely nor skipped). For example, a custom exception type could be used, as shown
in the following example:
public class PoisonPillItemProcessor<T> implements ItemProcessor<T, T> {
@Override
public T process(T item) throws Exception {
if (isPoisonPill(item)) {
throw new PoisonPillException("Poison pill detected: " + item);
}
return item;
}
}
Another simple way to stop a step from executing is to return null from the
ItemReader, as shown in the following example:
public class EarlyCompletionItemReader implements ItemReader<T> {
private ItemReader<T> delegate;
public void setDelegate(ItemReader<T> delegate) { ... }
public T read() throws Exception {
T item = delegate.read();
if (isEndItem(item)) {
return null; // end the step here
}
return item;
}
}
The previous example actually relies on the fact that there is a default implementation
of the CompletionPolicy strategy that signals a complete batch when the item to be
processed is null. A more sophisticated completion policy could be implemented and
injected into the Step through the SimpleStepFactoryBean.
The following example shows how to inject a completion policy into a step in XML:
<step id="simpleStep">
<tasklet>
<chunk reader="reader" writer="writer" commit-interval="10"
chunk-completion-policy="completionPolicy"/>
</tasklet>
</step>
<bean id="completionPolicy" class="org.example...SpecialCompletionPolicy"/>The following example shows how to inject a completion policy into a step in Java:
@Bean
public Step simpleStep(JobRepository jobRepository, PlatformTransactionManager transactionManager) {
return new StepBuilder("simpleStep", jobRepository)
.<String, String>chunk(new SpecialCompletionPolicy(), transactionManager)
.reader(reader())
.writer(writer())
.build();
}
An alternative is to set a flag in the StepExecution, which is checked by the Step
implementations in the framework in between item processing. To implement this
alternative, we need access to the current StepExecution, and this can be achieved by
implementing a StepListener and registering it with the Step. The following example
shows a listener that sets the flag:
public class CustomItemWriter extends ItemListenerSupport implements StepListener {
private StepExecution stepExecution;
public void beforeStep(StepExecution stepExecution) {
this.stepExecution = stepExecution;
}
public void afterRead(Object item) {
if (isPoisonPill(item)) {
stepExecution.setTerminateOnly();
}
}
}
When the flag is set, the default behavior is for the step to throw a
JobInterruptedException. This behavior can be controlled through the
StepInterruptionPolicy. However, the only choice is to throw or not throw an exception,
so this is always an abnormal ending to a job.
Adding a Footer Record
Often, when writing to flat files, a “footer” record must be appended to the end of the
file, after all processing has be completed. This can be achieved using the
FlatFileFooterCallback interface provided by Spring Batch. The FlatFileFooterCallback
(and its counterpart, the FlatFileHeaderCallback) are optional properties of the
FlatFileItemWriter and can be added to an item writer.
The following example shows how to use the FlatFileHeaderCallback and the
FlatFileFooterCallback in XML:
<bean id="itemWriter" class="org.spr...FlatFileItemWriter">
<property name="resource" ref="outputResource" />
<property name="lineAggregator" ref="lineAggregator"/>
<property name="headerCallback" ref="headerCallback" />
<property name="footerCallback" ref="footerCallback" />
</bean>The following example shows how to use the FlatFileHeaderCallback and the
FlatFileFooterCallback in Java:
@Bean
public FlatFileItemWriter<String> itemWriter(Resource outputResource) {
return new FlatFileItemWriterBuilder<String>()
.name("itemWriter")
.resource(outputResource)
.lineAggregator(lineAggregator())
.headerCallback(headerCallback())
.footerCallback(footerCallback())
.build();
}
The footer callback interface has just one method that is called when the footer must be written, as shown in the following interface definition:
public interface FlatFileFooterCallback {
void writeFooter(Writer writer) throws IOException;
}
Writing a Summary Footer
A common requirement involving footer records is to aggregate information during the output process and to append this information to the end of the file. This footer often serves as a summarization of the file or provides a checksum.
For example, if a batch job is writing Trade records to a flat file, and there is a
requirement that the total amount from all the Trades is placed in a footer, then the
following ItemWriter implementation can be used:
public class TradeItemWriter implements ItemWriter<Trade>,
FlatFileFooterCallback {
private ItemWriter<Trade> delegate;
private BigDecimal totalAmount = BigDecimal.ZERO;
public void write(Chunk<? extends Trade> items) throws Exception {
BigDecimal chunkTotal = BigDecimal.ZERO;
for (Trade trade : items) {
chunkTotal = chunkTotal.add(trade.getAmount());
}
delegate.write(items);
// After successfully writing all items
totalAmount = totalAmount.add(chunkTotal);
}
public void writeFooter(Writer writer) throws IOException {
writer.write("Total Amount Processed: " + totalAmount);
}
public void setDelegate(ItemWriter delegate) {...}
}
This TradeItemWriter stores a totalAmount value that is increased with the amount
from each Trade item written. After the last Trade is processed, the framework calls
writeFooter, which puts the totalAmount into the file. Note that the write method
makes use of a temporary variable, chunkTotal, that stores the total of the
Trade amounts in the chunk. This is done to ensure that, if a skip occurs in the
write method, the totalAmount is left unchanged. It is only at the end of the write
method, once we are guaranteed that no exceptions are thrown, that we update the
totalAmount.
In order for the writeFooter method to be called, the TradeItemWriter (which
implements FlatFileFooterCallback) must be wired into the FlatFileItemWriter as the
footerCallback.
The following example shows how to wire the TradeItemWriter in XML:
<bean id="tradeItemWriter" class="..TradeItemWriter">
<property name="delegate" ref="flatFileItemWriter" />
</bean>
<bean id="flatFileItemWriter" class="org.spr...FlatFileItemWriter">
<property name="resource" ref="outputResource" />
<property name="lineAggregator" ref="lineAggregator"/>
<property name="footerCallback" ref="tradeItemWriter" />
</bean>The following example shows how to wire the TradeItemWriter in Java:
@Bean
public TradeItemWriter tradeItemWriter() {
TradeItemWriter itemWriter = new TradeItemWriter();
itemWriter.setDelegate(flatFileItemWriter(null));
return itemWriter;
}
@Bean
public FlatFileItemWriter<String> flatFileItemWriter(Resource outputResource) {
return new FlatFileItemWriterBuilder<String>()
.name("itemWriter")
.resource(outputResource)
.lineAggregator(lineAggregator())
.footerCallback(tradeItemWriter())
.build();
}
The way that the TradeItemWriter has been written so far functions correctly only if
the Step is not restartable. This is because the class is stateful (since it stores the
totalAmount), but the totalAmount is not persisted to the database. Therefore, it
cannot be retrieved in the event of a restart. In order to make this class restartable,
the ItemStream interface should be implemented along with the methods open and
update, as shown in the following example:
public void open(ExecutionContext executionContext) {
if (executionContext.containsKey("total.amount") {
totalAmount = (BigDecimal) executionContext.get("total.amount");
}
}
public void update(ExecutionContext executionContext) {
executionContext.put("total.amount", totalAmount);
}
The update method stores the most current version of totalAmount to the
ExecutionContext just before that object is persisted to the database. The open method
retrieves any existing totalAmount from the ExecutionContext and uses it as the
starting point for processing, allowing the TradeItemWriter to pick up on restart where
it left off the previous time the Step was run.
Driving Query Based ItemReaders
In the chapter on readers and writers, database input using paging was discussed. Many database vendors, such as DB2, have extremely pessimistic locking strategies that can cause issues if the table being read also needs to be used by other portions of the online application. Furthermore, opening cursors over extremely large datasets can cause issues on databases from certain vendors. Therefore, many projects prefer to use a 'Driving Query' approach to reading in data. This approach works by iterating over keys, rather than the entire object that needs to be returned, as the following image illustrates:
As you can see, the example shown in the preceding image uses the same 'FOO' table as was
used in the cursor-based example. However, rather than selecting the entire row, only the
IDs were selected in the SQL statement. So, rather than a FOO object being returned
from read, an Integer is returned. This number can then be used to query for the
'details', which is a complete Foo object, as shown in the following image:
An ItemProcessor should be used to transform the key obtained from the driving query
into a full Foo object. An existing DAO can be used to query for the full object based
on the key.
Multi-Line Records
While it is usually the case with flat files that each record is confined to a single line, it is common that a file might have records spanning multiple lines with multiple formats. The following excerpt from a file shows an example of such an arrangement:
HEA;0013100345;2007-02-15 NCU;Smith;Peter;;T;20014539;F BAD;;Oak Street 31/A;;Small Town;00235;IL;US FOT;2;2;267.34
Everything between the line starting with 'HEA' and the line starting with 'FOT' is considered one record. There are a few considerations that must be made in order to handle this situation correctly:
-
Instead of reading one record at a time, the
ItemReadermust read every line of the multi-line record as a group, so that it can be passed to theItemWriterintact. -
Each line type may need to be tokenized differently.
Because a single record spans multiple lines and because we may not know how many lines
there are, the ItemReader must be careful to always read an entire record. In order to
do this, a custom ItemReader should be implemented as a wrapper for the
FlatFileItemReader.
The following example shows how to implement a custom ItemReader in XML:
<bean id="itemReader" class="org.spr...MultiLineTradeItemReader">
<property name="delegate">
<bean class="org.springframework.batch.item.file.FlatFileItemReader">
<property name="resource" value="data/iosample/input/multiLine.txt" />
<property name="lineMapper">
<bean class="org.spr...DefaultLineMapper">
<property name="lineTokenizer" ref="orderFileTokenizer"/>
<property name="fieldSetMapper" ref="orderFieldSetMapper"/>
</bean>
</property>
</bean>
</property>
</bean>The following example shows how to implement a custom ItemReader in Java:
@Bean
public MultiLineTradeItemReader itemReader() {
MultiLineTradeItemReader itemReader = new MultiLineTradeItemReader();
itemReader.setDelegate(flatFileItemReader());
return itemReader;
}
@Bean
public FlatFileItemReader flatFileItemReader() {
FlatFileItemReader<Trade> reader = new FlatFileItemReaderBuilder<>()
.name("flatFileItemReader")
.resource(new ClassPathResource("data/iosample/input/multiLine.txt"))
.lineTokenizer(orderFileTokenizer())
.fieldSetMapper(orderFieldSetMapper())
.build();
return reader;
}
To ensure that each line is tokenized properly, which is especially important for
fixed-length input, the PatternMatchingCompositeLineTokenizer can be used on the
delegate FlatFileItemReader. See
FlatFileItemReader in the Readers and
Writers chapter for more details. The delegate reader then uses a
PassThroughFieldSetMapper to deliver a FieldSet for each line back to the wrapping
ItemReader.
The following example shows how to ensure that each line is properly tokenized in XML:
<bean id="orderFileTokenizer" class="org.spr...PatternMatchingCompositeLineTokenizer">
<property name="tokenizers">
<map>
<entry key="HEA*" value-ref="headerRecordTokenizer" />
<entry key="FOT*" value-ref="footerRecordTokenizer" />
<entry key="NCU*" value-ref="customerLineTokenizer" />
<entry key="BAD*" value-ref="billingAddressLineTokenizer" />
</map>
</property>
</bean>The following example shows how to ensure that each line is properly tokenized in Java:
@Bean
public PatternMatchingCompositeLineTokenizer orderFileTokenizer() {
PatternMatchingCompositeLineTokenizer tokenizer =
new PatternMatchingCompositeLineTokenizer();
Map<String, LineTokenizer> tokenizers = new HashMap<>(4);
tokenizers.put("HEA*", headerRecordTokenizer());
tokenizers.put("FOT*", footerRecordTokenizer());
tokenizers.put("NCU*", customerLineTokenizer());
tokenizers.put("BAD*", billingAddressLineTokenizer());
tokenizer.setTokenizers(tokenizers);
return tokenizer;
}
This wrapper has to be able to recognize the end of a record so that it can continually
call read() on its delegate until the end is reached. For each line that is read, the
wrapper should build up the item to be returned. Once the footer is reached, the item can
be returned for delivery to the ItemProcessor and ItemWriter, as shown in the
following example:
private FlatFileItemReader<FieldSet> delegate;
public Trade read() throws Exception {
Trade t = null;
for (FieldSet line = null; (line = this.delegate.read()) != null;) {
String prefix = line.readString(0);
if (prefix.equals("HEA")) {
t = new Trade(); // Record must start with header
}
else if (prefix.equals("NCU")) {
Assert.notNull(t, "No header was found.");
t.setLast(line.readString(1));
t.setFirst(line.readString(2));
...
}
else if (prefix.equals("BAD")) {
Assert.notNull(t, "No header was found.");
t.setCity(line.readString(4));
t.setState(line.readString(6));
...
}
else if (prefix.equals("FOT")) {
return t; // Record must end with footer
}
}
Assert.isNull(t, "No 'END' was found.");
return null;
}
Executing System Commands
Many batch jobs require that an external command be called from within the batch job. Such a process could be kicked off separately by the scheduler, but the advantage of common metadata about the run would be lost. Furthermore, a multi-step job would also need to be split up into multiple jobs as well.
Because the need is so common, Spring Batch provides a Tasklet implementation for
calling system commands.
The following example shows how to call an external command in XML:
<bean class="org.springframework.batch.core.step.tasklet.SystemCommandTasklet">
<property name="command" value="echo hello" />
<!-- 5 second timeout for the command to complete -->
<property name="timeout" value="5000" />
</bean>The following example shows how to call an external command in Java:
@Bean
public SystemCommandTasklet tasklet() {
SystemCommandTasklet tasklet = new SystemCommandTasklet();
tasklet.setCommand("echo hello");
tasklet.setTimeout(5000);
return tasklet;
}
Handling Step Completion When No Input is Found
In many batch scenarios, finding no rows in a database or file to process is not
exceptional. The Step is simply considered to have found no work and completes with 0
items read. All of the ItemReader implementations provided out of the box in Spring
Batch default to this approach. This can lead to some confusion if nothing is written out
even when input is present (which usually happens if a file was misnamed or some similar
issue arises). For this reason, the metadata itself should be inspected to determine how
much work the framework found to be processed. However, what if finding no input is
considered exceptional? In this case, programmatically checking the metadata for no items
processed and causing failure is the best solution. Because this is a common use case,
Spring Batch provides a listener with exactly this functionality, as shown in
the class definition for NoWorkFoundStepExecutionListener:
public class NoWorkFoundStepExecutionListener extends StepExecutionListenerSupport {
public ExitStatus afterStep(StepExecution stepExecution) {
if (stepExecution.getReadCount() == 0) {
return ExitStatus.FAILED;
}
return null;
}
}
The preceding StepExecutionListener inspects the readCount property of the
StepExecution during the 'afterStep' phase to determine if no items were read. If that
is the case, an exit code FAILED is returned, indicating that the Step should fail.
Otherwise, null is returned, which does not affect the status of the Step.
Passing Data to Future Steps
It is often useful to pass information from one step to another. This can be done through
the ExecutionContext. The catch is that there are two ExecutionContexts: one at the
Step level and one at the Job level. The Step ExecutionContext remains only as
long as the step, while the Job ExecutionContext remains through the whole Job. On
the other hand, the Step ExecutionContext is updated every time the Step commits a
chunk, while the Job ExecutionContext is updated only at the end of each Step.
The consequence of this separation is that all data must be placed in the Step
ExecutionContext while the Step is executing. Doing so ensures that the data is
stored properly while the Step runs. If data is stored to the Job ExecutionContext,
then it is not persisted during Step execution. If the Step fails, that data is lost.
public class SavingItemWriter implements ItemWriter<Object> {
private StepExecution stepExecution;
public void write(Chunk<? extends Object> items) throws Exception {
// ...
ExecutionContext stepContext = this.stepExecution.getExecutionContext();
stepContext.put("someKey", someObject);
}
@BeforeStep
public void saveStepExecution(StepExecution stepExecution) {
this.stepExecution = stepExecution;
}
}
To make the data available to future Steps, it must be “promoted” to the Job
ExecutionContext after the step has finished. Spring Batch provides the
ExecutionContextPromotionListener for this purpose. The listener must be configured
with the keys related to the data in the ExecutionContext that must be promoted. It can
also, optionally, be configured with a list of exit code patterns for which the promotion
should occur (COMPLETED is the default). As with all listeners, it must be registered
on the Step.
The following example shows how to promote a step to the Job ExecutionContext in XML:
<job id="job1">
<step id="step1">
<tasklet>
<chunk reader="reader" writer="savingWriter" commit-interval="10"/>
</tasklet>
<listeners>
<listener ref="promotionListener"/>
</listeners>
</step>
<step id="step2">
...
</step>
</job>
<beans:bean id="promotionListener" class="org.spr....ExecutionContextPromotionListener">
<beans:property name="keys">
<list>
<value>someKey</value>
</list>
</beans:property>
</beans:bean>The following example shows how to promote a step to the Job ExecutionContext in Java:
@Bean
public Job job1(JobRepository jobRepository) {
return new JobBuilder("job1", jobRepository)
.start(step1())
.next(step1())
.build();
}
@Bean
public Step step1(JobRepository jobRepository, PlatformTransactionManager transactionManager) {
return new StepBuilder("step1", jobRepository)
.<String, String>chunk(10, transactionManager)
.reader(reader())
.writer(savingWriter())
.listener(promotionListener())
.build();
}
@Bean
public ExecutionContextPromotionListener promotionListener() {
ExecutionContextPromotionListener listener = new ExecutionContextPromotionListener();
listener.setKeys(new String[] {"someKey"});
return listener;
}
Finally, the saved values must be retrieved from the Job ExecutionContext, as shown
in the following example:
public class RetrievingItemWriter implements ItemWriter<Object> {
private Object someObject;
public void write(Chunk<? extends Object> items) throws Exception {
// ...
}
@BeforeStep
public void retrieveInterstepData(StepExecution stepExecution) {
JobExecution jobExecution = stepExecution.getJobExecution();
ExecutionContext jobContext = jobExecution.getExecutionContext();
this.someObject = jobContext.get("someKey");
}
}