67853f22de
This commit migrates the old Spring Batch documentation to a new asciidoc toolchain. It will be the first piece in modernizing the existing Spring Batch documentation. Future steps will include making java based configuraion more prominant in the reference documentation. Resolves BATCH-2620
636 lines
21 KiB
Plaintext
636 lines
21 KiB
Plaintext
:batch-asciidoc: http://docs.spring.io/spring-batch/reference/html/
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:toc: left
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:toclevels: 4
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[[commonPatterns]]
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== Common Batch Patterns
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Some batch jobs can be assembled purely from off-the-shelf components
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in Spring Batch. For instance the `ItemReader` and
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`ItemWriter` implementations can be configured to cover
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a wide range of scenarios. However, for the majority of cases, custom code
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will have to be written. The main API entry points for application
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developers are the `Tasklet`,
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`ItemReader`, `ItemWriter` and the
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various listener interfaces. Most simple batch jobs will be able to use
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off-the-shelf input from a Spring Batch `ItemReader`,
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but it is often the case that there are custom concerns in the processing
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and writing, which require developers to implement an
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`ItemWriter` or
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`ItemProcessor`.
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Here, we provide a few examples of common patterns in custom business
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logic. These examples primarily feature the listener interfaces. It should
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be noted that an `ItemReader` or
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`ItemWriter` can implement a listener interface as
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well, if appropriate.
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[[loggingItemProcessingAndFailures]]
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=== Logging Item Processing and Failures
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A common use case is the need for special handling of errors in a
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step, item by item, perhaps logging to a special channel, or inserting a
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record into a database. A chunk-oriented `Step`
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(created from the step factory beans) allows users to implement this use
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case with a simple `ItemReadListener`, for errors on
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read, and an `ItemWriteListener`, for errors on
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write. The below code snippets illustrate a listener that logs both read
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and write failures:
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[source, java]
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----
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public class ItemFailureLoggerListener extends ItemListenerSupport {
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private static Log logger = LogFactory.getLog("item.error");
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public void onReadError(Exception ex) {
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logger.error("Encountered error on read", e);
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}
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public void onWriteError(Exception ex, Object item) {
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logger.error("Encountered error on write", ex);
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}
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}
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----
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Having implemented this listener it must be registered with the step:
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[source, xml]
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----
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<step id="simpleStep">
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...
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<listeners>
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<listener>
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<bean class="org.example...ItemFailureLoggerListener"/>
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</listener>
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</listeners>
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</step>
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----
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Remember that if your listener does anything in an
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`onError()` method, it will be inside a transaction that is
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going to be rolled back. If you need to use a transactional resource such
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as a database inside an `onError()` method, consider adding a
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declarative transaction to that method (see Spring Core Reference Guide
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for details), and giving its propagation attribute the value
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REQUIRES_NEW.
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[[stoppingAJobManuallyForBusinessReasons]]
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=== Stopping a Job Manually for Business Reasons
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Spring Batch provides a `stop()` method
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through the `JobLauncher` interface, but this is
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really for use by the operator rather than the application programmer.
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Sometimes it is more convenient or makes more sense to stop a job
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execution from within the business logic.
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The simplest thing to do is to throw a
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`RuntimeException` (one that isn't retried
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indefinitely or skipped). For example, a custom exception type could be
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used, as in the example below:
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[source, java]
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----
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public class PoisonPillItemWriter implements ItemWriter<T> {
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public void write(T item) throws Exception {
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if (isPoisonPill(item)) {
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throw new PoisonPillException("Posion pill detected: " + item);
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}
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}
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}
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----
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Another simple way to stop a step from executing is to simply return
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`null` from the `ItemReader`:
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[source, java]
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----
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public class EarlyCompletionItemReader implements ItemReader<T> {
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private ItemReader<T> delegate;
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public void setDelegate(ItemReader<T> delegate) { ... }
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public T read() throws Exception {
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T item = delegate.read();
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if (isEndItem(item)) {
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return null; // end the step here
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}
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return item;
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}
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}
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----
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The previous example actually relies on the fact that there is a
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default implementation of the `CompletionPolicy`
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strategy which signals a complete batch when the item to be processed is
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`null`. A more sophisticated completion policy could be implemented and
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injected into the `Step` through the
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`SimpleStepFactoryBean`:
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[source, xml]
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----
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<step id="simpleStep">
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<tasklet>
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<chunk reader="reader" writer="writer" commit-interval="10"
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chunk-completion-policy="completionPolicy"/>
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</tasklet>
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</step>
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<bean id="completionPolicy" class="org.example...SpecialCompletionPolicy"/>
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----
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An alternative is to set a flag in the
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`StepExecution`, which is checked by the
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`Step` implementations in the framework in between
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item processing. To implement this alternative, we need access to the
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current `StepExecution`, and this can be achieved by
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implementing a `StepListener` and registering it with
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the `Step`. Here is an example of a listener that
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sets the flag:
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[source, java]
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----
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public class CustomItemWriter extends ItemListenerSupport implements StepListener {
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private StepExecution stepExecution;
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public void beforeStep(StepExecution stepExecution) {
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this.stepExecution = stepExecution;
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}
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public void afterRead(Object item) {
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if (isPoisonPill(item)) {
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stepExecution.setTerminateOnly(true);
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}
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}
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}
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----
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The default behavior here when the flag is set is for the step to
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throw a `JobInterruptedException`. This can be
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controlled through the `StepInterruptionPolicy`, but
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the only choice is to throw or not throw an exception, so this is always
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an abnormal ending to a job.
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[[addingAFooterRecord]]
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=== Adding a Footer Record
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Often when writing to flat files, a "footer" record must be appended
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to the end of the file, after all processing has be completed. This can
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also be achieved using the `FlatFileFooterCallback`
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interface provided by Spring Batch. The
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`FlatFileFooterCallback` (and its counterpart, the
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`FlatFileHeaderCallback`) are optional properties of
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the `FlatFileItemWriter`:
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[source, xml]
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----
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<bean id="itemWriter" class="org.spr...FlatFileItemWriter">
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<property name="resource" ref="outputResource" />
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<property name="lineAggregator" ref="lineAggregator"/>
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<property name="headerCallback" ref="headerCallback" />
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<property name="footerCallback" ref="footerCallback" />
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</bean>
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----
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The footer callback interface is very simple. It has just one method
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that is called when the footer must be written:
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[source, java]
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----
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public interface FlatFileFooterCallback {
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void writeFooter(Writer writer) throws IOException;
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}
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----
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[[writingASummaryFooter]]
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==== Writing a Summary Footer
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A very common requirement involving footer records is to aggregate
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information during the output process and to append this information to
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the end of the file. This footer serves as a summarization of the file
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or provides a checksum.
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For example, if a batch job is writing
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`Trade` records to a flat file, and there is a
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requirement that the total amount from all the
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`Trades` is placed in a footer, then the following
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`ItemWriter` implementation can be used:
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[source, java]
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----
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public class TradeItemWriter implements ItemWriter<Trade>,
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FlatFileFooterCallback {
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private ItemWriter<Trade> delegate;
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private BigDecimal totalAmount = BigDecimal.ZERO;
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public void write(List<? extends Trade> items) {
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BigDecimal chunkTotal = BigDecimal.ZERO;
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for (Trade trade : items) {
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chunkTotal = chunkTotal.add(trade.getAmount());
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}
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delegate.write(items);
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// After successfully writing all items
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totalAmount = totalAmount.add(chunkTotal);
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}
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public void writeFooter(Writer writer) throws IOException {
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writer.write("Total Amount Processed: " + totalAmount);
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}
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public void setDelegate(ItemWriter delegate) {...}
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}
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----
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This `TradeItemWriter` stores a
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`totalAmount` value that is increased with the
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`amount` from each Trade item written.
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After the last Trade is processed, the framework
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will call `writeFooter`, which will put that
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`totalAmount` into the file. Note that the
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`write` method makes use of a temporary variable,
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chunkTotalAmount, that stores the total of the `Trades`
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in the chunk. This is done to ensure that if a skip occurs in the
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`write` method, that the
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`totalAmount` will be left unchanged. It is only at
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the end of the `write` method, once we are
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guaranteed that no exceptions will be thrown, that we update the
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`totalAmount`.
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In order for the `writeFooter` method to be
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called, the `TradeItemWriter` (which implements
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`FlatFileFooterCallback`) must be wired into the
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`FlatFileItemWriter` as the
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`footerCallback`:
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[source, xml]
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----
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<bean id="tradeItemWriter" class="..TradeItemWriter">
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<property name="delegate" ref="flatFileItemWriter" />
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</bean>
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<bean id="flatFileItemWriter" class="org.spr...FlatFileItemWriter">
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<property name="resource" ref="outputResource" />
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<property name="lineAggregator" ref="lineAggregator"/>
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<property name="footerCallback" ref="tradeItemWriter" />
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</bean>
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----
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The way that the `TradeItemWriter` has been
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so far will only function correctly if the `Step`
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is not restartable. This is because the class is stateful (since it
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stores the `totalAmount`), but the `totalAmount`
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is not persisted to the database, and therefore, it cannot be retrieved
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in the event of a restart. In order to make this class restartable, the
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`ItemStream` interface should be implemented along
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with the methods `open` and
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`update`:
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[source, java]
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----
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public void open(ExecutionContext executionContext) {
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if (executionContext.containsKey("total.amount") {
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totalAmount = (BigDecimal) executionContext.get("total.amount");
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}
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}
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public void update(ExecutionContext executionContext) {
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executionContext.put("total.amount", totalAmount);
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}
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----
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The update method will store the most
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current version of `totalAmount` to the
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`ExecutionContext` just before that object is
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persisted to the database. The open method will
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retrieve any existing `totalAmount` from the
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`ExecutionContext` and use it as the starting point
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for processing, allowing the `TradeItemWriter` to
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pick up on restart where it left off the previous time the
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`Step` was executed.
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[[drivingQueryBasedItemReaders]]
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=== Driving Query Based ItemReaders
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In the chapter on readers and writers, database input using paging
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was discussed. Many database vendors, such as DB2, have extremely
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pessimistic locking strategies that can cause issues if the table being
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read also needs to be used by other portions of the online application.
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Furthermore, opening cursors over extremely large datasets can cause
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issues on certain vendors. Therefore, many projects prefer to use a
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'Driving Query' approach to reading in data. This approach works by
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iterating over keys, rather than the entire object that needs to be
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returned, as the following example illustrates:
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.Driving Query Job
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image::{batch-asciidoc}images/drivingQueryExample.png[Driving Query Job, scaledwidth="60%"]
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As you can see, this example uses the same 'FOO' table as was used
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in the cursor based example. However, rather than selecting the entire
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row, only the ID's were selected in the SQL statement. So, rather than a
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FOO object being returned from `read`, an Integer
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will be returned. This number can then be used to query for the 'details',
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which is a complete Foo object:
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.Driving Query Example
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image::{batch-asciidoc}images/drivingQueryJob.png[Driving Query Example, scaledwidth="60%"]
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An `ItemProcessor` should be used to transform the key obtained from
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the driving query into a full 'Foo' object. An existing DAO can be used to
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query for the full object based on the key.
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[[multiLineRecords]]
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==== Multi-Line Records
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While it is usually the case with flat files that one each record is
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confined to a single line, it is common that a file might have records
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spanning multiple lines with multiple formats. The following excerpt from
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a file illustrates this:
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----
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HEA;0013100345;2007-02-15
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NCU;Smith;Peter;;T;20014539;F
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BAD;;Oak Street 31/A;;Small Town;00235;IL;US
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FOT;2;2;267.34
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----
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Everything between the line starting with 'HEA' and the line
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starting with 'FOT' is considered one record. There are a few
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considerations that must be made in order to handle this situation
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correctly:
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Instead of reading one record at a time, the
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`ItemReader` must read every line of the
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multi-line record as a group, so that it can be passed to the
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`ItemWriter` intact.
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Each line type may need to be tokenized differently.
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Because a single record spans multiple lines, and we may not know
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how many lines there are, the `ItemReader` must be
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careful to always read an entire record. In order to do this, a custom
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`ItemReader` should be implemented as a wrapper for
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the `FlatFileItemReader`.
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[source, xml]
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----
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<bean id="itemReader" class="org.spr...MultiLineTradeItemReader">
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<property name="delegate">
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<bean class="org.springframework.batch.item.file.FlatFileItemReader">
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<property name="resource" value="data/iosample/input/multiLine.txt" />
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<property name="lineMapper">
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<bean class="org.spr...DefaultLineMapper">
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<property name="lineTokenizer" ref="orderFileTokenizer"/>
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<property name="fieldSetMapper">
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<bean class="org.spr...PassThroughFieldSetMapper" />
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</property>
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</bean>
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</property>
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</bean>
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</property>
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</bean>
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----
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To ensure that each line is tokenized properly, which is especially
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important for fixed length input, the
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`PatternMatchingCompositeLineTokenizer` can be used
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on the delegate `FlatFileItemReader`. See for more details. The delegate
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reader will then use a `PassThroughFieldSetMapper` to
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deliver a `FieldSet` for each line back to the
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wrapping `ItemReader`.
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[source, xml]
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----
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<bean id="orderFileTokenizer" class="org.spr...PatternMatchingCompositeLineTokenizer">
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<property name="tokenizers">
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<map>
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<entry key="HEA*" value-ref="headerRecordTokenizer" />
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<entry key="FOT*" value-ref="footerRecordTokenizer" />
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<entry key="NCU*" value-ref="customerLineTokenizer" />
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<entry key="BAD*" value-ref="billingAddressLineTokenizer" />
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</map>
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</property>
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</bean>
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----
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This wrapper will have to be able recognize the end of a record so
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that it can continually call `read()` on its
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delegate until the end is reached. For each line that is read, the wrapper
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should build up the item to be returned. Once the footer is reached, the
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item can be returned for delivery to the
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`ItemProcessor` and `ItemWriter`.
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[source, java]
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----
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private FlatFileItemReader<FieldSet> delegate;
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public Trade read() throws Exception {
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Trade t = null;
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for (FieldSet line = null; (line = this.delegate.read()) != null;) {
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String prefix = line.readString(0);
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if (prefix.equals("HEA")) {
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t = new Trade(); // Record must start with header
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}
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else if (prefix.equals("NCU")) {
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Assert.notNull(t, "No header was found.");
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t.setLast(line.readString(1));
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t.setFirst(line.readString(2));
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...
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}
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else if (prefix.equals("BAD")) {
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Assert.notNull(t, "No header was found.");
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t.setCity(line.readString(4));
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t.setState(line.readString(6));
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...
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}
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else if (prefix.equals("FOT")) {
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return t; // Record must end with footer
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}
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}
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Assert.isNull(t, "No 'END' was found.");
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return null;
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}
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----
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[[executingSystemCommands]]
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=== Executing System Commands
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Many batch jobs may require that an external command be called from
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within the batch job. Such a process could be kicked off separately by the
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scheduler, but the advantage of common meta-data about the run would be
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lost. Furthermore, a multi-step job would also need to be split up into
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multiple jobs as well.
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Because the need is so common, Spring Batch provides a
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`Tasklet` implementation for calling system
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commands:
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[source, xml]
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----
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<bean class="org.springframework.batch.core.step.tasklet.SystemCommandTasklet">
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<property name="command" value="echo hello" />
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<!-- 5 second timeout for the command to complete -->
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<property name="timeout" value="5000" />
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</bean>
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----
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[[handlingStepCompletionWhenNoInputIsFound]]
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=== Handling Step Completion When No Input is Found
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In many batch scenarios, finding no rows in a database or file to
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process is not exceptional. The `Step` is simply
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considered to have found no work and completes with 0 items read. All of
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the `ItemReader` implementations provided out of the
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box in Spring Batch default to this approach. This can lead to some
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confusion if nothing is written out even when input is present. (which
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usually happens if a file was misnamed, etc) For this reason, the meta
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data itself should be inspected to determine how much work the framework
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found to be processed. However, what if finding no input is considered
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exceptional? In this case, programmatically checking the meta data for no
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items processed and causing failure is the best solution. Because this is
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a common use case, a listener is provided with just this
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functionality:
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[source, java]
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----
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public class NoWorkFoundStepExecutionListener extends StepExecutionListenerSupport {
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public ExitStatus afterStep(StepExecution stepExecution) {
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if (stepExecution.getReadCount() == 0) {
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return ExitStatus.FAILED;
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}
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return null;
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}
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}
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----
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The above `StepExecutionListener` inspects the
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readCount property of the `StepExecution` during the
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'afterStep' phase to determine if no items were read. If that is the case,
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an exit code of FAILED is returned, indicating that the
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`Step` should fail. Otherwise, `null` is returned,
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which will not affect the status of the
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`Step`.
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[[passingDataToFutureSteps]]
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=== Passing Data to Future Steps
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It is often useful to pass information from one step to another.
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This can be done using the `ExecutionContext`. The
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catch is that there are two `ExecutionContexts`: one
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at the `Step` level and one at the
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`Job` level. The `Step`
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`ExecutionContext` lives only as long as the step
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while the `Job`
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`ExecutionContext` lives through the whole
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`Job`. On the other hand, the
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`Step` `ExecutionContext` is
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updated every time the `Step` commits a chunk while
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the `Job` `ExecutionContext` is
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updated only at the end of each `Step`.
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The consequence of this separation is that all data must be placed
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in the `Step` `ExecutionContext`
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while the `Step` is executing. This will ensure that
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the data will be stored properly while the `Step` is
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on-going. If data is stored to the `Job`
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`ExecutionContext`, then it will not be persisted
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during `Step` execution and if the
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`Step` fails, that data will be lost.
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[source, java]
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----
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public class SavingItemWriter implements ItemWriter<Object> {
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private StepExecution stepExecution;
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public void write(List<? extends Object> items) throws Exception {
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// ...
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ExecutionContext stepContext = this.stepExecution.getExecutionContext();
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stepContext.put("someKey", someObject);
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}
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@BeforeStep
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public void saveStepExecution(StepExecution stepExecution) {
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this.stepExecution = stepExecution;
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}
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}
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----
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To make the data available to future `Steps`,
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it will have to be "promoted" to the `Job`
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`ExecutionContext` after the step has finished.
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Spring Batch provides the
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`ExecutionContextPromotionListener` for this purpose.
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The listener must be configured with the keys related to the data in the
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`ExecutionContext` that must be promoted. It can
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also, optionally, be configured with a list of exit code patterns for
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which the promotion should occur ("COMPLETED" is the default). As with all
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listeners, it must be registered on the
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`Step`.
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[source, xml]
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----
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<job id="job1">
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<step id="step1">
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<tasklet>
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<chunk reader="reader" writer="savingWriter" commit-interval="10"/>
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</tasklet>
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<listeners>
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<listener ref="promotionListener"/>
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</listeners>
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</step>
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<step id="step2">
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...
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</step>
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</job>
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<beans:bean id="promotionListener" class="org.spr....ExecutionContextPromotionListener">
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<beans:property name="keys" value="someKey"/>
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</beans:bean>
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----
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Finally, the saved values must be retrieved from the
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`Job` `ExecutionContext`:
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[source, java]
|
|
----
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|
public class RetrievingItemWriter implements ItemWriter<Object> {
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private Object someObject;
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public void write(List<? extends Object> items) throws Exception {
|
|
// ...
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|
}
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|
|
@BeforeStep
|
|
public void retrieveInterstepData(StepExecution stepExecution) {
|
|
JobExecution jobExecution = stepExecution.getJobExecution();
|
|
ExecutionContext jobContext = jobExecution.getExecutionContext();
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|
this.someObject = jobContext.get("someKey");
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|
}
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|
}
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----
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