This project provides declarative retry support for Spring applications. It is used in Spring Batch, Spring Integration, and others. Imperative retry is also supported for explicit usage.
This section provides a quick introduction to getting started with Spring Retry. It includes a declarative example and an imperative example.
The following example shows how to use Spring Retry in its declarative style:
@Configuration
@EnableRetry
public class Application {
@Bean
public Service service() {
return new Service();
}
}
@Service
class Service {
@Retryable(RemoteAccessException.class)
public void service() {
// ... do something
}
@Recover
public void recover(RemoteAccessException e) {
// ... panic
}
}This example calls the service method and, if it fails with a RemoteAccessException, retries
(by default, up to three times), and then tries the recover method if unsuccessful.
There are various options in the @Retryable annotation attributes for including and
excluding exception types, limiting the number of retries, and setting the policy for backoff.
The declarative approach to applying retry handling by using the @Retryable annotation shown earlier has an additional
runtime dependency on AOP classes. For details on how to resolve this dependency in your project, see the
'Java Configuration for Retry Proxies' section.
The following example shows how to use Spring Retry in its imperative style (available since version 1.3):
RetryTemplate template = RetryTemplate.builder()
.maxAttempts(3)
.fixedBackoff(1000)
.retryOn(RemoteAccessException.class)
.build();
template.execute(ctx -> {
// ... do something
});For versions prior to 1.3, see the examples in the RetryTemplate section.
Spring Retry requires Java 1.7 and Maven 3.0.5 (or greater). To build, run the following Maven command:
$ mvn install
This section discusses the features of Spring Retry and shows how to use its API.
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 this kind of treatment are transient in nature. For
example, a remote call to a web service or an RMI service that fails because of a network
glitch or a DeadLockLoserException in a database update may resolve itself after a
short wait. To automate the retry of such operations, Spring Retry has the
RetryOperations strategy. The RetryOperations interface definition follows:
public interface RetryOperations {
<T> T execute(RetryCallback<T> retryCallback) throws Exception;
<T> T execute(RetryCallback<T> retryCallback, RecoveryCallback<T> recoveryCallback)
throws Exception;
<T> T execute(RetryCallback<T> retryCallback, RetryState retryState)
throws Exception, ExhaustedRetryException;
<T> T execute(RetryCallback<T> retryCallback, RecoveryCallback<T> recoveryCallback,
RetryState retryState) throws Exception;
}The basic callback is a simple interface that lets you insert some business logic to be retried:
public interface RetryCallback<T> {
T doWithRetry(RetryContext context) throws Throwable;
}The callback is tried, and, if it fails (by throwing an Exception), it is retried
until either it is successful or the implementation decides to abort. There are a number
of overloaded execute methods in the RetryOperations interface, to deal with various
use cases for recovery when all retry attempts are exhausted and to deal with retry state, which
lets clients and implementations store information between calls (more on this later).
The simplest general purpose implementation of RetryOperations is RetryTemplate.
The following example shows how to use it:
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 execute a web service call and return the result to the user. If that call fails, it is retried until a timeout is reached.
Since version 1.3, fluent configuration of RetryTemplate is also available, as follows:
RetryTemplate.builder()
.maxAttempts(10)
.exponentialBackoff(100, 2, 10000)
.retryOn(IOException.class)
.traversingCauses()
.build();
RetryTemplate.builder()
.fixedBackoff(10)
.withinMillis(3000)
.build();
RetryTemplate.builder()
.infiniteRetry()
.retryOn(IOException.class)
.uniformRandomBackoff(1000, 3000)
.build();The method parameter for the RetryCallback is a RetryContext. Many callbacks ignore
the context. However, if necessary, you can use it 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 needs to be shared
between calls to execute.
When a retry is exhausted, the RetryOperations can pass control to a different
callback: RecoveryCallback. To use this feature, clients can pass in the callbacks
together to the same method, as the following example shows:
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, the client is given the chance to do some alternate processing through the recovery callback.
In the simplest case, a retry is just a while loop: the RetryTemplate can keep trying
until it either succeeds or fails. The RetryContext contains some state to determine
whether to retry or abort. However, this state is on the stack, and there is no need to
store it anywhere globally. Consequently, we call this "stateless retry". The distinction
between stateless and stateful retry is contained in the implementation of RetryPolicy
(RetryTemplate can handle both). In a stateless retry, the callback is always executed
in the same thread as when it failed on 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 (usually) no transactional resource, but it does sometimes apply to a database update, especially when using Hibernate. In this case, it only makes sense to rethrow the exception that called the failure immediately so that the transaction can roll back and we can start a new (and valid) one.
In these cases, 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 the context, 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 Retry provides a storage strategy called RetryContextCache, which
you can inject into the RetryTemplate. The default implementation of the
RetryContextCache is in-memory, using a simple Map. It has a strictly enforced maximum
capacity, to avoid memory leaks, but it does not have any advanced cache features (such as
time to live). You should consider injecting a Map that has those features if you need
them. For advanced usage with multiple processes in a clustered environment, you might
also consider implementing the RetryContextCache with a cluster cache of some sort
(though, 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 Retry provides the RetryState abstraction. This works in
conjunction with special execute methods in the RetryOperations.
The failed operations are recognized by identifying the state across multiple invocations
of the retry. To identify the state, you can provide a RetryState object that is
responsible for returning a unique key that identifies the item. The identifier is used as
a key in the RetryContextCache.
Warning: Be very careful with the implementation of
Object.equals()andObject.hashCode()in the key returned byRetryState. The best advice is to use a business key to identify the items. In the case of a JMS message, you can use the message ID.
When the retry is exhausted, you also have 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). As in the stateless case, this option is provided by the RecoveryCallback,
which you can provide 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 (see the Additional Dependencies section).
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 is responsible for using the current policy to create a RetryContext and
passing 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 RetryContext). It then asks the policy if another attempt can be
made. If another attempt cannot be made (for example, because a limit has been reached or
a timeout has been detected), the policy is also responsible for identifying the
exhausted state -- but not for handling the exception. RetryTemplate throws the
original exception, except in the stateful case, when no recovery is available. In that
case, it throws RetryExhaustedException. You can also set a flag in the
RetryTemplate to have it unconditionally throw the original exception from the
callback (that is, from user code) instead.
Tip: Failures are inherently either retryable or not -- if the same exception is always going to be thrown from the business logic, it does not help to retry it. So you should 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, time is spent retrying something that you know in advance is fatal.
Spring Retry provides some simple general-purpose implementations of stateless
RetryPolicy (for example, a SimpleRetryPolicy) and the 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. The following example shows how to use it:
// Set the max attempts including the initial attempt before retrying
// and retry on all exceptions (this is the default):
SimpleRetryPolicy policy = new SimpleRetryPolicy(5, Collections.singletonMap(Exception.class, true));
// Use the policy...
RetryTemplate template = new RetryTemplate();
template.setRetryPolicy(policy);
template.execute(new RetryCallback<Foo>() {
public Foo doWithRetry(RetryContext context) {
// business logic here
}
});A more flexible implementation called ExceptionClassifierRetryPolicy is also available.
It lets you configure different retry behavior for an arbitrary set of exception types
through 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.
You might need to implement your own retry policies for more customized decisions. For instance, if there is a well-known, solution-specific, classification of exceptions into retryable and not retryable.
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 be resolved only by
waiting. If a RetryCallback fails, the RetryTemplate can pause execution according to
the BackoffPolicy. The following listing shows the definition of the BackoffPolicy
interface:
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 Retry all use Object.wait(). A common use case is to
back off with an exponentially increasing wait period, to avoid two retries getting into
lock step and both failing (a lesson learned from Ethernet). For this purpose, Spring
Retry provides ExponentialBackoffPolicy. Spring Retry also provides randomized versions
of delay policies that are quite useful to avoid resonating between related failures in a
complex system.
It is often useful to be able to receive additional callbacks for cross cutting concerns across a number of different retries. For this purpose, Spring Retry provides the RetryListener interface. The RetryTemplate lets you register RetryListener instances, and they are given callbacks with the RetryContext and Throwable (where available during the iteration).
The following listing shows the RetryListener interface:
public interface RetryListener {
void open(RetryContext context, RetryCallback<T> callback);
void onError(RetryContext context, RetryCallback<T> callback, Throwable e);
void close(RetryContext context, RetryCallback<T> callback, Throwable e);
}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.
When dealing with methods that are annotated with @Retryable or with Spring AOP intercepted methods, Spring Retry allows a detailed inspection of the method invocation within the RetryListener implementation.
Such a scenario could be particularly useful when there is a need to monitor how often a certain method call has been retried and expose it with detailed tagging information (such as class name, method name, or even parameter values in some exotic cases).
The following example registers such a listener:
template.registerListener(new MethodInvocationRetryListenerSupport() {
@Override
protected <T, E extends Throwable> void doClose(RetryContext context,
MethodInvocationRetryCallback<T, E> callback, Throwable throwable) {
monitoringTags.put(labelTagName, callback.getLabel());
Method method = callback.getInvocation()
.getMethod();
monitoringTags.put(classTagName,
method.getDeclaringClass().getSimpleName());
monitoringTags.put(methodTagName, method.getName());
// register a monitoring counter with appropriate tags
// ...
}
});Sometimes, you want to retry some business processing every time it happens. The classic
example of this is the remote service call. Spring Retry provides an AOP interceptor that
wraps a method call in a RetryOperations instance for exactly this purpose. The
RetryOperationsInterceptor executes the intercepted method and retries on failure
according to the RetryPolicy in the provided RepeatTemplate.
You can add the @EnableRetry annotation to one of your @Configuration classes and use
@Retryable on the methods (or on the type level for all methods) that you want to retry.
You can also specify any number of retry listeners. The following example shows how to do
so:
@Configuration
@EnableRetry
public class Application {
@Bean
public Service service() {
return new Service();
}
@Bean public RetryListener retryListener1() {
return new RetryListener() {...}
}
@Bean public RetryListener retryListener2() {
return new RetryListener() {...}
}
}
@Service
class Service {
@Retryable(RemoteAccessException.class)
public service() {
// ... do something
}
}You can use the attributes of @Retryable to control the RetryPolicy and BackoffPolicy, as follows:
@Service
class Service {
@Retryable(maxAttempts=12, backoff=@Backoff(delay=100, maxDelay=500))
public service() {
// ... do something
}
}The preceding example creates a random backoff between 100 and 500 milliseconds and up to
12 attempts. There is also a stateful attribute (default: false) to control whether
the retry is stateful or not. To use stateful retry, the intercepted method has to have
arguments, since they are used to construct the cache key for the state.
The @EnableRetry annotation also looks for beans of type Sleeper and other strategies
used in the RetryTemplate and interceptors to control the behavior of the retry at runtime.
The @EnableRetry annotation creates proxies for @Retryable beans, and the proxies
(that is, the bean instances in the application) have the Retryable interface added to
them. This is purely a marker interface, but it might be useful for other tools looking to
apply retry advice (they should usually not bother if the bean already implements
Retryable).
If you want to take an alternative code path when
the retry is exhausted, you can supply a recovery method. Methods should be declared in the same class as the @Retryable
instance and marked @Recover. The return type must match the @Retryable method. The arguments
for the recovery method can optionally include the exception that was thrown and
(optionally) the arguments passed to the original retryable method (or a partial list of
them as long as none are omitted up to the last one needed). The following example shows how to do so:
@Service
class Service {
@Retryable(RemoteAccessException.class)
public void service(String str1, String str2) {
// ... do something
}
@Recover
public void recover(RemoteAccessException e, String str1, String str2) {
// ... error handling making use of original args if required
}
}To resolve conflicts between multiple methods that can be picked for recovery, you can explicitly specify recovery method name. The following example shows how to do so:
@Service
class Service {
@Retryable(recover = "service1Recover", value = RemoteAccessException.class)
public void service1(String str1, String str2) {
// ... do something
}
@Retryable(recover = "service2Recover", value = RemoteAccessException.class)
public void service2(String str1, String str2) {
// ... do something
}
@Recover
public void service1Recover(RemoteAccessException e, String str1, String str2) {
// ... error handling making use of original args if required
}
@Recover
public void service2Recover(RemoteAccessException e, String str1, String str2) {
// ... error handling making use of original args if required
}
}Version 1.3.2 and later supports matching a parameterized (generic) return type to detect the correct recovery method:
@Service
class Service {
@Retryable(RemoteAccessException.class)
public List<Thing1> service1(String str1, String str2) {
// ... do something
}
@Retryable(RemoteAccessException.class)
public List<Thing2> service2(String str1, String str2) {
// ... do something
}
@Recover
public List<Thing1> recover1(RemoteAccessException e, String str1, String str2) {
// ... error handling for service1
}
@Recover
public List<Thing2> recover2(RemoteAccessException e, String str1, String str2) {
// ... error handling for service2
}
}Version 1.2 introduced the ability to use expressions for certain properties. The following example show how to use expressions this way:
@Retryable(exceptionExpression="message.contains('this can be retried')")
public void service1() {
...
}
@Retryable(exceptionExpression="message.contains('this can be retried')")
public void service2() {
...
}
@Retryable(exceptionExpression="@exceptionChecker.shouldRetry(#root)",
maxAttemptsExpression = "#{@integerFiveBean}",
backoff = @Backoff(delayExpression = "#{1}", maxDelayExpression = "#{5}", multiplierExpression = "#{1.1}"))
public void service3() {
...
}Since Spring Retry 1.2.5, for exceptionExpression, templated expressions (#{...}) are
deprecated in favor of simple expression strings
(message.contains('this can be retried')).
Expressions can contain property placeholders, such as #{${max.delay}} or
#{@exceptionChecker.${retry.method}(#root)}. The following rules apply:
exceptionExpressionis evaluated against the thrown exception as the#rootobject.maxAttemptsExpressionand the@BackOffexpression attributes are evaluated once, during initialization. There is no root object for the evaluation but they can reference other beans in the context.
The declarative approach to applying retry handling by using the @Retryable annotation
shown earlier has an additional runtime dependency on AOP classes that need to be declared
in your project. If your application is implemented by using Spring Boot, this dependency
is best resolved by using the Spring Boot starter for AOP. For example, for Gradle, add
the following line to your build.gradle file:
runtime('org.springframework.boot:spring-boot-starter-aop')
For non-Boot apps, you need to declare a runtime dependency on the latest version of
AspectJ's aspectjweaver module. For example, for Gradle, you should add the following
line to your build.gradle file:
runtime('org.aspectj:aspectjweaver:1.8.13')
The following example of declarative iteration uses Spring AOP to repeat a service call to
a method called remoteCall:
<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.retry.interceptor.RetryOperationsInterceptor"/>For more detail on how to configure AOP interceptors, see the Spring Framework Documentation.
The preceding example uses a default RetryTemplate inside the interceptor. To change the
policies or listeners, you need only inject an instance of RetryTemplate into the
interceptor.
Spring Retry is released under the non-restrictive Apache 2.0 license and follows a very standard Github development process, using Github tracker for issues and merging pull requests into the master branch. If you want to contribute even something trivial, please do not hesitate, but do please follow the guidelines in the next paragraph.
Before we can accept a non-trivial patch or pull request, we need you to sign the contributor's agreement. Signing the contributor's agreement does not grant anyone commit rights to the main repository, but it does mean that we can accept your contributions, and you will get an author credit if we do. Active contributors might be asked to join the core team and be given the ability to merge pull requests.
This project adheres to the Contributor Covenant. By participating, you are expected to uphold this code. Please report unacceptable behavior to [email protected].