Rets-Io/docs/asciidoc/retry.adoc

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[[retry]]

== Retry

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To make processing more robust and less prone to failure, it sometimes
    helps to automatically retry a failed operation in case it might
    succeed on a subsequent attempt. Errors that are susceptible to intermittent failure
    are often transient in nature. Examples include remote calls to a web
    service that fails because of a network glitch or a
    `DeadlockLoserDataAccessException` in a database update.

[[retryTemplate]]


=== `RetryTemplate`


[NOTE]
====
The retry functionality was pulled out of Spring Batch as of 2.2.0.
It is now part of a new library, https://github.com/spring-projects/spring-retry[Spring Retry].
====


To automate retry
    operations Spring Batch has the `RetryOperations`
    strategy. The following interface definition for `RetryOperations`:


[source, java]
----
public interface RetryOperations {

    <T, E extends Throwable> T execute(RetryCallback<T, E> retryCallback) throws E;

    <T, E extends Throwable> T execute(RetryCallback<T, E> retryCallback, RecoveryCallback<T> recoveryCallback)
        throws E;

    <T, E extends Throwable> T execute(RetryCallback<T, E> retryCallback, RetryState retryState)
        throws E, ExhaustedRetryException;

    <T, E extends Throwable> T execute(RetryCallback<T, E> retryCallback, RecoveryCallback<T> recoveryCallback,
        RetryState retryState) throws E;

}
----

The basic callback is a simple interface that lets you
    insert some business logic to be retried, as shown in the following interface definition:


[source, java]
----
public interface RetryCallback<T, E extends Throwable> {

    T doWithRetry(RetryContext context) throws E;

}
----

The callback runs and, if it fails (by throwing an
    `Exception`), it is retried until either it is
    successful or the implementation aborts. There are a number of
    overloaded `execute` methods in the
    `RetryOperations` interface. Those methods deal with various use
    cases for recovery when all retry attempts are exhausted and deal with
    retry state, which allows clients and implementations to store information
    between calls (we cover this in more detail later in the chapter).

The simplest general purpose implementation of
    `RetryOperations` is
    `RetryTemplate`. It can be used as follows:


[source, java]
----
RetryTemplate template = new RetryTemplate();

TimeoutRetryPolicy policy = new TimeoutRetryPolicy();
policy.setTimeout(30000L);

template.setRetryPolicy(policy);

Foo result = template.execute(new RetryCallback<Foo>() {

    public Foo doWithRetry(RetryContext context) {
        // Do stuff that might fail, e.g. webservice operation
        return result;
    }

});
----

In the preceding example, we make a web service call and return the result
    to the user. If that call fails, then it is retried until a timeout is
    reached.

[[retryContext]]


==== `RetryContext`

The method parameter for the `RetryCallback`
      is a `RetryContext`. Many callbacks
      ignore the context, but, if necessary, it can be used as an attribute bag
      to store data for the duration of the iteration.

A `RetryContext` has a parent context
      if there is a nested retry in progress in the same thread. The parent
      context is occasionally useful for storing data that need to be shared
      between calls to `execute`.

[[recoveryCallback]]


==== `RecoveryCallback`

When a retry is exhausted, the
      `RetryOperations` can pass control to a different
      callback, called the `RecoveryCallback`. To use this
      feature, clients pass in the callbacks together to the same method,
      as shown in the following example:


[source, java]
----
Foo foo = template.execute(new RetryCallback<Foo>() {
    public Foo doWithRetry(RetryContext context) {
        // business logic here
    },
  new RecoveryCallback<Foo>() {
    Foo recover(RetryContext context) throws Exception {
          // recover logic here
    }
});
----

If the business logic does not succeed before the template
      decides to abort, then the client is given the chance to do some
      alternate processing through the recovery callback.

[[statelessRetry]]


==== Stateless Retry

In the simplest case, a retry is just a while loop. The
      `RetryTemplate` can just keep trying until it
      either succeeds or fails. The `RetryContext`
      contains some state to determine whether to retry or abort, but this
      state is on the stack and there is no need to store it anywhere
      globally, so we call this stateless retry. The distinction between
      stateless and stateful retry is contained in the implementation of the
      `RetryPolicy` (the
      `RetryTemplate` can handle both). In a stateless
      retry, the retry callback is always executed in the same thread it was on
      when it failed.

[[statefulRetry]]


==== Stateful Retry

Where the failure has caused a transactional resource to become
      invalid, there are some special considerations. This does not apply to a
      simple remote call because there is no transactional resource (usually),
      but it does sometimes apply to a database update, especially when using
      Hibernate. In this case it only makes sense to re-throw the exception
      that called the failure immediately, so that the transaction can roll
      back and we can start a new, valid transaction.

In cases involving transactions, a stateless retry is not good enough, because the
      re-throw and roll back necessarily involve leaving the
      `RetryOperations.execute()` method and potentially losing the
      context that was on the stack. To avoid losing it we have to introduce a
      storage strategy to lift it off the stack and put it (at a minimum) in
      heap storage. For this purpose, Spring Batch provides a storage strategy called
      `RetryContextCache`, which can be injected into the
      `RetryTemplate`. The default implementation of the
      `RetryContextCache` is in memory, using a simple
      `Map`. Advanced usage with multiple processes in a
      clustered environment might also consider implementing the
      `RetryContextCache` with a cluster cache of some
      sort (however, even in a clustered environment, this might be
      overkill).

Part of the responsibility of the
      `RetryOperations` is to recognize the failed
      operations when they come back in a new execution (and usually wrapped
      in a new transaction). To facilitate this, Spring Batch provides the
      `RetryState` abstraction. This works in conjunction
      with a special `execute` methods in the
      `RetryOperations` interface.

The way the failed operations are recognized is by identifying the
      state across multiple invocations of the retry. To identify the state,
      the user can provide a `RetryState` object that is
      responsible for returning a unique key identifying the item. The
      identifier is used as a key in the
      `RetryContextCache` interface.


[WARNING]
====
Be very careful with the implementation of
        `Object.equals()` and `Object.hashCode()` in the
        key returned by `RetryState`. The best advice is
        to use a business key to identify the items. In the case of a JMS
        message, the message ID can be used.
====


When the retry is exhausted, there is also the option to handle the
      failed item in a different way, instead of calling the
      `RetryCallback` (which is now presumed to be likely
      to fail). Just like in the stateless case, this option is provided by
      the `RecoveryCallback`, which can be provided by
      passing it in to the `execute` method of
      `RetryOperations`.

The decision to retry or not is actually delegated to a regular
      `RetryPolicy`, so the usual concerns about limits
      and timeouts can be injected there (described later in this chapter).

[[retryPolicies]]


=== Retry Policies

Inside a `RetryTemplate`, the decision to retry
    or fail in the `execute` method is determined by a
    `RetryPolicy`, which is also a factory for the
    `RetryContext`. The
    `RetryTemplate` has the responsibility to use the
    current policy to create a `RetryContext` and pass
    that in to the `RetryCallback` at every attempt.
    After a callback fails, the `RetryTemplate` has to
    make a call to the `RetryPolicy` to ask it to update
    its state (which is stored in the
    `RetryContext`) and then asks the policy if
    another attempt can be made. If another attempt cannot be made (such as when a
    limit is reached or a timeout is detected) then the policy is also
    responsible for handling the exhausted state. Simple implementations
    throw `RetryExhaustedException`, which causes
    any enclosing transaction to be rolled back. More sophisticated
    implementations might attempt to take some recovery action, in which case
    the transaction can remain intact.


[TIP]
====
Failures are inherently either retryable or not. If the same
      exception is always going to be thrown from the business logic, it
      does no good to retry it. So do not retry on all exception types. Rather, try to
      focus on only those exceptions that you expect to be retryable. It is not
      usually harmful to the business logic to retry more aggressively, but
      it is wasteful, because, if a failure is deterministic, you spend time
      retrying something that you know in advance is fatal.
====


Spring Batch provides some simple general purpose implementations of
    stateless `RetryPolicy`, such as
    `SimpleRetryPolicy` and
    `TimeoutRetryPolicy` (used in the preceding example).

The `SimpleRetryPolicy` allows a retry on
    any of a named list of exception types, up to a fixed number of times. It
    also has a list of "fatal" exceptions that should never be retried, and
    this list overrides the retryable list so that it can be used to give
    finer control over the retry behavior, as shown in the following example:


[source, java]
----
SimpleRetryPolicy policy = new SimpleRetryPolicy();
// Set the max retry attempts
policy.setMaxAttempts(5);
// Retry on all exceptions (this is the default)
policy.setRetryableExceptions(new Class[] {Exception.class});
// ... but never retry IllegalStateException
policy.setFatalExceptions(new Class[] {IllegalStateException.class});

// Use the policy...
RetryTemplate template = new RetryTemplate();
template.setRetryPolicy(policy);
template.execute(new RetryCallback<Foo>() {
    public Foo doWithRetry(RetryContext context) {
        // business logic here
    }
});
----

There is also a more flexible implementation called
    `ExceptionClassifierRetryPolicy`, which allows the
    user to configure different retry behavior for an arbitrary set of
    exception types though the `ExceptionClassifier`
    abstraction. The policy works by calling on the classifier to convert an
    exception into a delegate `RetryPolicy`. For
    example, one exception type can be retried more times before failure than
    another by mapping it to a different policy.

Users might need to implement their own retry policies for more
    customized decisions. For instance, a custom retry policy makes sense when there is a well-known,
    solution-specific classification of exceptions into retryable and not
    retryable.

[[backoffPolicies]]


=== Backoff Policies

When retrying after a transient failure, it often helps to wait a bit
    before trying again, because usually the failure is caused by some problem
    that can only be resolved by waiting. If a
    `RetryCallback` fails, the
    `RetryTemplate` can pause execution according to the
    `BackoffPolicy`.

The following code shows the interface definition for the `BackOffPolicy` interface:

[source, java]
----
public interface BackoffPolicy {

    BackOffContext start(RetryContext context);

    void backOff(BackOffContext backOffContext)
        throws BackOffInterruptedException;

}
----

A `BackoffPolicy` is free to implement
    the backOff in any way it chooses. The policies provided by Spring Batch
    out of the box all use `Object.wait()`. A common use case is to
    backoff with an exponentially increasing wait period, to avoid two retries
    getting into lock step and both failing (this is a lesson learned from
    ethernet). For this purpose, Spring Batch provides the
    `ExponentialBackoffPolicy`.

[[retryListeners]]


=== Listeners

Often, it is useful to be able to receive additional callbacks for
    cross cutting concerns across a number of different retries. For this
    purpose, Spring Batch provides the `RetryListener`
    interface. The `RetryTemplate` lets users
    register `RetryListeners`, and they are given
    callbacks with `RetryContext` and
    `Throwable` where available during the
    iteration.

The following code shows the interface definition for `RetryListener`:


[source, java]
----
public interface RetryListener {

    <T, E extends Throwable> boolean open(RetryContext context, RetryCallback<T, E> callback);

    <T, E extends Throwable> void onError(RetryContext context, RetryCallback<T, E> callback, Throwable throwable);

    <T, E extends Throwable> void close(RetryContext context, RetryCallback<T, E> callback, Throwable throwable);
}
----

The `open` and
    `close` callbacks come before and after the entire
    retry in the simplest case, and `onError` applies to
    the individual `RetryCallback` calls. The
    `close` method might also receive a
    `Throwable`. If there has been an error, it is the
    last one thrown by the `RetryCallback`.

Note that, when there is more than one listener, they are in a list,
    so there is an order. In this case, `open` is
    called in the same order while `onError` and
    `close` are called in reverse order.

[[declarativeRetry]]


=== Declarative Retry

Sometimes, there is some business processing that you know you want
    to retry every time it happens. The classic example of this is the remote
    service call. Spring Batch provides an AOP interceptor that wraps a method
    call in a `RetryOperations` implementation for just this purpose.
    The `RetryOperationsInterceptor` executes the
    intercepted method and retries on failure according to the
    `RetryPolicy` in the provided
    `RetryTemplate`.

[role="xmlContent"]
The following example shows a declarative retry that uses the Spring AOP
    namespace to retry a service call to a method called
    `remoteCall` (for more detail on how to configure
    AOP interceptors, see the Spring User Guide):


[source, xml, role="xmlContent"]
----
<aop:config>
    <aop:pointcut id="transactional"
        expression="execution(* com..*Service.remoteCall(..))" />
    <aop:advisor pointcut-ref="transactional"
        advice-ref="retryAdvice" order="-1"/>
</aop:config>

<bean id="retryAdvice"
    class="org.springframework.batch.retry.interceptor.RetryOperationsInterceptor"/>
----

[role="javaContent"]
The following example shows a declarative retry that uses java configuration
    to retry a service call to a method called
    `remoteCall` (for more detail on how to configure
    AOP interceptors, see the Spring User Guide):


[source, java, role="javaContent"]
----
@Bean
public MyService myService() {
	ProxyFactory factory = new ProxyFactory(RepeatOperations.class.getClassLoader());
	factory.setInterfaces(MyService.class);
	factory.setTarget(new MyService());

	MyService service = (MyService) factory.getProxy();
	JdkRegexpMethodPointcut pointcut = new JdkRegexpMethodPointcut();
	pointcut.setPatterns(".*remoteCall.*");

	RetryOperationsInterceptor interceptor = new RetryOperationsInterceptor();

	((Advised) service).addAdvisor(new DefaultPointcutAdvisor(pointcut, interceptor));

	return service;
}
----

The preceding example uses a default
    `RetryTemplate` inside the interceptor. To change the
    policies or listeners, you can inject an instance of
    `RetryTemplate` into the interceptor.