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) allows users to implement this use case with a simple ItemReadListener, for errors on read, and an ItemWriteListener, for errors on write. The below code snippets illustrate 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, Object item) {
        logger.error("Encountered error on write", e);
    }

}

Having implemented this listener it must be registered with the step:

<step id="simpleStep">
    ...
    <listeners>
        <listener class="org.example...ItemFailureLoggerListener"/>
    </listeners>
</step>

Remember that if your listener does anything in an onError() method, it will 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 the value REQUIRES_NEW.

Spring Batch provides a stop() method through the JobLauncher 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 isn't retried indefinitely or skipped). For example, a custom exception type could be used, as in the example below:

public class PoisonPillItemWriter implements ItemWriter<T> {
    
    public void write(T item) throws Exception {
        if (isPoisonPill(item)) {
            throw new PoisonPillException("Posion pill detected: " + item);
       }
    }

}

Another simple way to stop a step from executing is to simply return null from the ItemReader:

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 which 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:

<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"/>

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. Here is an example of 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(true);
       }
    }

}

The default behavior here when the flag is set is for the step to throw a JobInterruptedException. This can be controlled through the StepInterruptionPolicy, but the only choice is to throw or not throw an exception, so this is always an abnormal ending to a job.

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 also be achieved using the FlatFileFooterCallback interface provided by Spring Batch. The FlatFileFooterCallback (and its counterpart, the FlatFileHeaderCallback) are optional properties of the FlatFileItemWriter:

<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 footer callback interface is very simple. It has just one method that is called when the footer must be written:

public interface FlatFileFooterCallback {

    void writeFooter(Writer writer) throws IOException;

}

public class TradeItemWriter implements ItemWriter<Trade>, 
                                        FlatFileFooterCallback {

    private ItemWriter<Trade> delegate;

    private BigDecimal totalAmount = BigDecimal.ZERO;

    public void write(List<? extends Trade> items) {
        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) {...}
}

<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>

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);
}

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 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 example illustrates:

As you can see, this example uses the same 'FOO' table as was used in the cursor based example. However, rather than selecting the entire row, only the ID's were selected in the SQL statement. So, rather than a FOO object being returned from read, an Integer will be returned. This number can then be used to query for the 'details', which is a complete Foo object:

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.

While it is usually the case with flat files that one 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 illustrates this:

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:

Because a single record spans multiple lines, and 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.

<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">
                        <bean class="org.spr...PassThroughFieldSetMapper" />
                    </property>
                </bean>
            </property>
        </bean>
    </property>
</bean>

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 Section 6.6.2.9, “Multiple Record Types within a Single File” for more details. The delegate reader will then use a PassThroughFieldSetMapper to deliver a FieldSet for each line back to the wrapping ItemReader.

<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>

This wrapper will have to be able 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.

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;
}

Many batch jobs may 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 meta-data 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:

<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>

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, etc) For this reason, the meta data 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 meta data for no items processed and causing failure is the best solution. Because this is a common use case, a listener is provided with just this functionality:

public class NoWorkFoundStepExecutionListener extends StepExecutionListenerSupport {

    public ExitStatus afterStep(StepExecution stepExecution) {
        if (stepExecution.getReadCount() == 0) {
            return ExitStatus.FAILED;
        }
        return null;
    }

}

The above 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 of FAILED is returned, indicating that the Step should fail. Otherwise, null is returned, which will not affect the status of the Step.

It is often useful to pass information from one step to another. This can be done using the ExecutionContext. The catch is that there are two ExecutionContexts: one at the Step level and one at the Job level. The Step ExecutionContext lives only as long as the step while the Job ExecutionContext lives 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. This will ensure that the data will be stored properly while the Step is on-going. If data is stored to the Job ExecutionContext, then it will not be persisted during Step execution and if the Step fails, that data will be lost.

public void SavingItemWriter implements ItemWriter<Object> {
    private StepExecution stepExecution;

    public void write(List<? 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 will have to 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.

<job id="job1">
    <step id="step1">
        <tasket>
            <chunk reader="reader" writer="savingWriter" commit-interval="10"/>
            <listeners>
                <listener ref="promotionListener"/>
            </listeners>
        </tasklet>
    </step>

    <step id="step2">
       ...
    </step>
</job>

<beans:bean id="promotionListener" class="org.spr....ExecutionContextPromotionListener">
    <beans:property name="keys" value="someKey"/>
</beans:bean>

Finally, to the saved values must be retrieved from the Job ExeuctionContext:

public void RetrievingItemWriter implements ItemWriter<Object> {
    private Object someObject;

    public void write(List<? extends Object> items) throws Exception {
        // ...
    }

    @BeforeStep
    public void saveStepExecution(StepExecution stepExecution) {
        JobExecution jobExecution = stepExecution.getJobExecution();
        ExecutionContext jobContext = jobExecution.getExecutionContext();
        this.someObject = jobContext.get("someKey");
    }
}