0d9f4ce6f1
I made a new implementation of the XML/Java toggle (and added a third choice for having both available). Changes to make a dynamic ToC work with content selection toggles Various asciidoc and JavaScript changes to make the dynamic ToC (tocbot) work with the content toggle (XML or Java in this case but also more options in other projects).
457 lines
16 KiB
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457 lines
16 KiB
Plaintext
:batch-asciidoc: ./
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:toc: left
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:toclevels: 4
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[[retry]]
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== Retry
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ifndef::onlyonetoggle[]
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include::toggle.adoc[]
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endif::onlyonetoggle[]
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To make processing more robust and less prone to failure, it sometimes
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helps to automatically retry a failed operation in case it might
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succeed on a subsequent attempt. Errors that are susceptible to intermittent failure
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are often transient in nature. Examples include remote calls to a web
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service that fails because of a network glitch or a
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`DeadlockLoserDataAccessException` in a database update.
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[[retryTemplate]]
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=== `RetryTemplate`
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[NOTE]
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====
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The retry functionality was pulled out of Spring Batch as of 2.2.0.
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It is now part of a new library, Spring Retry.
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====
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To automate retry
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operations Spring Batch has the `RetryOperations`
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strategy. The following interface definition for `RetryOperations`:
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[source, java]
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----
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public interface RetryOperations {
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<T> T execute(RetryCallback<T> retryCallback) throws Exception;
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<T> T execute(RetryCallback<T> retryCallback, RecoveryCallback<T> recoveryCallback)
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throws Exception;
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<T> T execute(RetryCallback<T> retryCallback, RetryState retryState)
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throws Exception, ExhaustedRetryException;
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<T> T execute(RetryCallback<T> retryCallback, RecoveryCallback<T> recoveryCallback,
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RetryState retryState) throws Exception;
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}
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----
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The basic callback is a simple interface that lets you
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insert some business logic to be retried, as shown in the following interface definition:
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[source, java]
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----
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public interface RetryCallback<T> {
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T doWithRetry(RetryContext context) throws Throwable;
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}
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----
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The callback runs and, if it fails (by throwing an
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`Exception`), it is retried until either it is
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successful or the implementation aborts. There are a number of
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overloaded `execute` methods in the
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`RetryOperations` interface. Those methods deal with various use
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cases for recovery when all retry attempts are exhausted and deal with
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retry state, which allows clients and implementations to store information
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between calls (we cover this in more detail later in the chapter).
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The simplest general purpose implementation of
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`RetryOperations` is
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`RetryTemplate`. It can be used as follows:
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[source, java]
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----
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RetryTemplate template = new RetryTemplate();
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TimeoutRetryPolicy policy = new TimeoutRetryPolicy();
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policy.setTimeout(30000L);
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template.setRetryPolicy(policy);
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Foo result = template.execute(new RetryCallback<Foo>() {
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public Foo doWithRetry(RetryContext context) {
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// Do stuff that might fail, e.g. webservice operation
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return result;
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}
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});
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----
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In the preceding example, we make a web service call and return the result
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to the user. If that call fails, then it is retried until a timeout is
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reached.
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[[retryContext]]
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==== `RetryContext`
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The method parameter for the `RetryCallback`
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is a `RetryContext`. Many callbacks
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ignore the context, but, if necessary, it can be used as an attribute bag
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to store data for the duration of the iteration.
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A `RetryContext` has a parent context
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if there is a nested retry in progress in the same thread. The parent
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context is occasionally useful for storing data that need to be shared
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between calls to `execute`.
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[[recoveryCallback]]
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==== `RecoveryCallback`
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When a retry is exhausted, the
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`RetryOperations` can pass control to a different
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callback, called the `RecoveryCallback`. To use this
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feature, clients pass in the callbacks together to the same method,
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as shown in the following example:
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[source, java]
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----
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Foo foo = template.execute(new RetryCallback<Foo>() {
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public Foo doWithRetry(RetryContext context) {
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// business logic here
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},
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new RecoveryCallback<Foo>() {
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Foo recover(RetryContext context) throws Exception {
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// recover logic here
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}
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});
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----
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If the business logic does not succeed before the template
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decides to abort, then the client is given the chance to do some
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alternate processing through the recovery callback.
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[[statelessRetry]]
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==== Stateless Retry
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In the simplest case, a retry is just a while loop. The
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`RetryTemplate` can just keep trying until it
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either succeeds or fails. The `RetryContext`
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contains some state to determine whether to retry or abort, but this
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state is on the stack and there is no need to store it anywhere
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globally, so we call this stateless retry. The distinction between
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stateless and stateful retry is contained in the implementation of the
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`RetryPolicy` (the
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`RetryTemplate` can handle both). In a stateless
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retry, the retry callback is always executed in the same thread it was on
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when it failed.
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[[statefulRetry]]
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==== Stateful Retry
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Where the failure has caused a transactional resource to become
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invalid, there are some special considerations. This does not apply to a
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simple remote call because there is no transactional resource (usually),
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but it does sometimes apply to a database update, especially when using
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Hibernate. In this case it only makes sense to re-throw the exception
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that called the failure immediately, so that the transaction can roll
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back and we can start a new, valid transaction.
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In cases involving transactions, a stateless retry is not good enough, because the
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re-throw and roll back necessarily involve leaving the
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`RetryOperations.execute()` method and potentially losing the
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context that was on the stack. To avoid losing it we have to introduce a
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storage strategy to lift it off the stack and put it (at a minimum) in
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heap storage. For this purpose, Spring Batch provides a storage strategy called
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`RetryContextCache`, which can be injected into the
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`RetryTemplate`. The default implementation of the
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`RetryContextCache` is in memory, using a simple
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`Map`. Advanced usage with multiple processes in a
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clustered environment might also consider implementing the
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`RetryContextCache` with a cluster cache of some
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sort (however, even in a clustered environment, this might be
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overkill).
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Part of the responsibility of the
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`RetryOperations` is to recognize the failed
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operations when they come back in a new execution (and usually wrapped
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in a new transaction). To facilitate this, Spring Batch provides the
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`RetryState` abstraction. This works in conjunction
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with a special `execute` methods in the
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`RetryOperations` interface.
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The way the failed operations are recognized is by identifying the
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state across multiple invocations of the retry. To identify the state,
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the user can provide a `RetryState` object that is
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responsible for returning a unique key identifying the item. The
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identifier is used as a key in the
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`RetryContextCache` interface.
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[WARNING]
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====
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Be very careful with the implementation of
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`Object.equals()` and `Object.hashCode()` in the
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key returned by `RetryState`. The best advice is
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to use a business key to identify the items. In the case of a JMS
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message, the message ID can be used.
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====
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When the retry is exhausted, there is also the option to handle the
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failed item in a different way, instead of calling the
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`RetryCallback` (which is now presumed to be likely
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to fail). Just like in the stateless case, this option is provided by
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the `RecoveryCallback`, which can be provided by
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passing it in to the `execute` method of
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`RetryOperations`.
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The decision to retry or not is actually delegated to a regular
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`RetryPolicy`, so the usual concerns about limits
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and timeouts can be injected there (described later in this chapter).
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[[retryPolicies]]
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=== Retry Policies
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Inside a `RetryTemplate`, the decision to retry
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or fail in the `execute` method is determined by a
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`RetryPolicy`, which is also a factory for the
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`RetryContext`. The
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`RetryTemplate` has the responsibility to use the
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current policy to create a `RetryContext` and pass
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that in to the `RetryCallback` at every attempt.
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After a callback fails, the `RetryTemplate` has to
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make a call to the `RetryPolicy` to ask it to update
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its state (which is stored in the
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`RetryContext`) and then asks the policy if
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another attempt can be made. If another attempt cannot be made (such as when a
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limit is reached or a timeout is detected) then the policy is also
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responsible for handling the exhausted state. Simple implementations
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throw `RetryExhaustedException`, which causes
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any enclosing transaction to be rolled back. More sophisticated
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implementations might attempt to take some recovery action, in which case
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the transaction can remain intact.
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[TIP]
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====
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Failures are inherently either retryable or not. If the same
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exception is always going to be thrown from the business logic, it
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does no good to retry it. So do not retry on all exception types. Rather, try to
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focus on only those exceptions that you expect to be retryable. It is not
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usually harmful to the business logic to retry more aggressively, but
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it is wasteful, because, if a failure is deterministic, you spend time
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retrying something that you know in advance is fatal.
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====
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Spring Batch provides some simple general purpose implementations of
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stateless `RetryPolicy`, such as
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`SimpleRetryPolicy` and
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`TimeoutRetryPolicy` (used in the preceding example).
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The `SimpleRetryPolicy` allows a retry on
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any of a named list of exception types, up to a fixed number of times. It
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also has a list of "fatal" exceptions that should never be retried, and
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this list overrides the retryable list so that it can be used to give
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finer control over the retry behavior, as shown in the following example:
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[source, java]
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----
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SimpleRetryPolicy policy = new SimpleRetryPolicy();
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// Set the max retry attempts
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policy.setMaxAttempts(5);
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// Retry on all exceptions (this is the default)
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policy.setRetryableExceptions(new Class[] {Exception.class});
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// ... but never retry IllegalStateException
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policy.setFatalExceptions(new Class[] {IllegalStateException.class});
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// Use the policy...
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RetryTemplate template = new RetryTemplate();
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template.setRetryPolicy(policy);
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template.execute(new RetryCallback<Foo>() {
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public Foo doWithRetry(RetryContext context) {
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// business logic here
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}
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});
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----
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There is also a more flexible implementation called
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`ExceptionClassifierRetryPolicy`, which allows the
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user to configure different retry behavior for an arbitrary set of
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exception types though the `ExceptionClassifier`
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abstraction. The policy works by calling on the classifier to convert an
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exception into a delegate `RetryPolicy`. For
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example, one exception type can be retried more times before failure than
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another by mapping it to a different policy.
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Users might need to implement their own retry policies for more
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customized decisions. For instance, a custom retry policy makes sense when there is a well-known,
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solution-specific classification of exceptions into retryable and not
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retryable.
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[[backoffPolicies]]
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=== Backoff Policies
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When retrying after a transient failure, it often helps to wait a bit
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before trying again, because usually the failure is caused by some problem
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that can only be resolved by waiting. If a
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`RetryCallback` fails, the
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`RetryTemplate` can pause execution according to the
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`BackoffPolicy`.
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The following code shows the interface definition for the `BackOffPolicy` interface:
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[source, java]
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----
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public interface BackoffPolicy {
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BackOffContext start(RetryContext context);
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void backOff(BackOffContext backOffContext)
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throws BackOffInterruptedException;
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}
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----
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A `BackoffPolicy` is free to implement
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the backOff in any way it chooses. The policies provided by Spring Batch
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out of the box all use `Object.wait()`. A common use case is to
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backoff with an exponentially increasing wait period, to avoid two retries
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getting into lock step and both failing (this is a lesson learned from
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ethernet). For this purpose, Spring Batch provides the
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`ExponentialBackoffPolicy`.
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[[retryListeners]]
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=== Listeners
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Often, it is useful to be able to receive additional callbacks for
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cross cutting concerns across a number of different retries. For this
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purpose, Spring Batch provides the `RetryListener`
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interface. The `RetryTemplate` lets users
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register `RetryListeners`, and they are given
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callbacks with `RetryContext` and
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`Throwable` where available during the
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iteration.
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The following code shows the interface definition for `RetryListener`:
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[source, java]
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----
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public interface RetryListener {
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void open(RetryContext context, RetryCallback<T> callback);
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void onError(RetryContext context, RetryCallback<T> callback, Throwable e);
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void close(RetryContext context, RetryCallback<T> callback, Throwable e);
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}
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----
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The `open` and
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`close` callbacks come before and after the entire
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retry in the simplest case, and `onError` applies to
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the individual `RetryCallback` calls. The
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`close` method might also receive a
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`Throwable`. If there has been an error, it is the
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last one thrown by the `RetryCallback`.
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Note that, when there is more than one listener, they are in a list,
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so there is an order. In this case, `open` is
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called in the same order while `onError` and
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`close` are called in reverse order.
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[[declarativeRetry]]
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=== Declarative Retry
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Sometimes, there is some business processing that you know you want
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to retry every time it happens. The classic example of this is the remote
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service call. Spring Batch provides an AOP interceptor that wraps a method
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call in a `RetryOperations` implementation for just this purpose.
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The `RetryOperationsInterceptor` executes the
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intercepted method and retries on failure according to the
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`RetryPolicy` in the provided
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`RepeatTemplate`.
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[role="xmlContent"]
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The following example shows a declarative retry that uses the Spring AOP
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namespace to retry a service call to a method called
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`remoteCall` (for more detail on how to configure
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AOP interceptors, see the Spring User Guide):
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[source, xml, role="xmlContent"]
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----
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<aop:config>
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<aop:pointcut id="transactional"
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expression="execution(* com..*Service.remoteCall(..))" />
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<aop:advisor pointcut-ref="transactional"
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advice-ref="retryAdvice" order="-1"/>
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</aop:config>
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<bean id="retryAdvice"
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class="org.springframework.batch.retry.interceptor.RetryOperationsInterceptor"/>
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----
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[role="javaContent"]
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The following example shows a declarative retry that uses java configuration
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to retry a service call to a method called
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`remoteCall` (for more detail on how to configure
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AOP interceptors, see the Spring User Guide):
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[source, java, role="javaContent"]
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----
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@Bean
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public MyService myService() {
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ProxyFactory factory = new ProxyFactory(RepeatOperations.class.getClassLoader());
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factory.setInterfaces(MyService.class);
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factory.setTarget(new MyService());
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MyService service = (MyService) factory.getProxy();
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JdkRegexpMethodPointcut pointcut = new JdkRegexpMethodPointcut();
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pointcut.setPatterns(".*remoteCall.*");
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RetryOperationsInterceptor interceptor = new RetryOperationsInterceptor();
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((Advised) service).addAdvisor(new DefaultPointcutAdvisor(pointcut, interceptor));
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return service;
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}
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----
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The preceding example uses a default
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`RetryTemplate` inside the interceptor. To change the
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policies or listeners, you can inject an instance of
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`RetryTemplate` into the interceptor.
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