# Package org.apache.commons.lang3.concurrent

Provides support classes for multi-threaded programming.

See: Description

- Interface Summary
  Interface | Description
  --- | ---
  CircuitBreaker<T> | An interface describing a Circuit Breaker component.
  Computable<I,O> | Definition of an interface for a wrapper around a calculation that takes a single parameter and returns a result.
  ConcurrentInitializer<T> | Definition of an interface for the thread-safe initialization of objects.

- Class Summary
  Class | Description
  --- | ---
  AbstractCircuitBreaker<T> | Base class for circuit breakers.
  AtomicInitializer<T> | A specialized implementation of the `ConcurrentInitializer` interface based on an `AtomicReference` variable.
  AtomicSafeInitializer<T> | A specialized `ConcurrentInitializer` implementation which is similar to `AtomicInitializer`, but ensures that the `AtomicSafeInitializer.initialize()` method is called only once.
  BackgroundInitializer<T> | A class that allows complex initialization operations in a background task.
  BasicThreadFactory | An implementation of the `ThreadFactory` interface that provides some configuration options for the threads it creates.
  BasicThreadFactory.Builder | A builder class for creating instances of `BasicThreadFactory`.
  CallableBackgroundInitializer<T> | A specialized `BackgroundInitializer` implementation that wraps a `Callable` object.
  ConcurrentUtils | An utility class providing functionality related to the `java.util.concurrent` package.
  ConstantInitializer<T> | A very simple implementation of the `ConcurrentInitializer` interface which always returns the same object.
  EventCountCircuitBreaker | A simple implementation of the Circuit Breaker pattern that counts specific events.
  LazyInitializer<T> | This class provides a generic implementation of the lazy initialization pattern.
  Memoizer<I,O> | Definition of an interface for a wrapper around a calculation that takes a single parameter and returns a result.
  MultiBackgroundInitializer | A specialized `BackgroundInitializer` implementation that can deal with multiple background initialization tasks.
  MultiBackgroundInitializer.MultiBackgroundInitializerResults | A data class for storing the results of the background initialization performed by `MultiBackgroundInitializer`.
  ThresholdCircuitBreaker | A simple implementation of the Circuit Breaker pattern that opens if the requested increment amount is greater than a given threshold.
  TimedSemaphore | A specialized semaphore implementation that provides a number of permits in a given time frame.

- Enum Summary
  Enum | Description
  --- | ---
  AbstractCircuitBreaker.State | An internal enumeration representing the different states of a circuit breaker.

- Exception Summary
  Exception | Description
  --- | ---
  CircuitBreakingException | An exception class used for reporting runtime error conditions related to circuit breakers.
  ConcurrentException | An exception class used for reporting error conditions related to accessing data of background tasks.
  ConcurrentRuntimeException | An exception class used for reporting runtime error conditions related to accessing data of background tasks.

## Package org.apache.commons.lang3.concurrent Description

Provides support classes for multi-threaded programming. This package is intended to be an extension to `java.util.concurrent`. These classes are thread-safe.

###

A group of classes deals with the correct creation and initialization of objects that are accessed by multiple threads. All these classes implement the `ConcurrentInitializer` interface which provides just a single method:

     public interface ConcurrentInitializer<T> {
        T get() throws ConcurrentException;
     }

A `ConcurrentInitializer` produces an object. By calling the `get()` method the object managed by the initializer can be obtained. There are different implementations of the interface available addressing various use cases:

`ConstantInitializer` is a very straightforward implementation of the `ConcurrentInitializer` interface: An instance is passed an object when it is constructed. In its `get()` method it simply returns this object. This is useful, for instance in unit tests or in cases when you want to pass a specific object to a component which expects a `ConcurrentInitializer`.

The `LazyInitializer` class can be used to defer the creation of an object until it is actually used. This makes sense, for instance, if the creation of the object is expensive and would slow down application startup or if the object is needed only for special executions. `LazyInitializer` implements the double-check idiom for an instance field as discussed in Joshua Bloch's "Effective Java", 2nd edition, item 71. It uses volatile fields to reduce the amount of synchronization. Note that this idiom is appropriate for instance fields only. For static fields there are superior alternatives.

We provide an example use case to demonstrate the usage of this class: A server application uses multiple worker threads to process client requests. If such a request causes a fatal error, an administrator is to be notified using a special messaging service. We assume that the creation of the messaging service is an expensive operation. So it should only be performed if an error actually occurs. Here is where `LazyInitializer` comes into play. We create a specialized subclass for creating and initializing an instance of our messaging service. `LazyInitializer` declares an abstract `initialize()` method which we have to implement to create the messaging service object:

     public class MessagingServiceInitializer extends LazyInitializer<MessagingService> {
       protected MessagingService initialize() throws ConcurrentException {
         // Do all necessary steps to create and initialize the service object
         MessagingService service = ...
         return service;
       }
     }

Now each server thread is passed a reference to a shared instance of our new `MessagingServiceInitializer` class. The threads run in a loop processing client requests. If an error is detected, the messaging service is obtained from the initializer, and the administrator is notified:

     public class ServerThread implements Runnable {
      // The initializer for obtaining the messaging service.
      private final ConcurrentInitializer<MessagingService> initializer;

      public ServerThread(ConcurrentInitializer<MessagingService> init) {
        initializer = init;
      }

      public void run() {
        while (true) {
          try {
            // wait for request
            // process request
          } catch (FatalServerException ex) {
            // get messaging service
            try {
              MessagingService svc = initializer.get();
              svc.notifyAdministrator(ex);
            } catch (ConcurrentException cex) {
              cex.printStackTrace();
            }
          }
        }
      }
     }

The `AtomicInitializer` class is very similar to `LazyInitializer`. It serves the same purpose: to defer the creation of an object until it is needed. The internal structure is also very similar. Again there is an abstract `initialize()` method which has to be implemented by concrete subclasses in order to create and initialize the managed object. Actually, in our example above we can turn the `MessagingServiceInitializer` into an atomic initializer by simply changing the extends declaration to refer to `AtomicInitializer<MessagingService>` as super class.

With `AtomicSafeInitializer` there is yet another variant implementing the lazy initializing pattern. Its implementation is close to `AtomicInitializer`; it also uses atomic variables internally and therefore does not need synchronization. The name "Safe" is derived from the fact that it implements an additional check which guarantees that the `initialize()` method is called only once. So it behaves exactly in the same way as `LazyInitializer`.

Now, which one of the lazy initializer implementations should you use? First of all we have to state that is is problematic to give general recommendations regarding the performance of these classes. The initializers make use of low-level functionality whose efficiency depends on multiple factors including the target platform and the number of concurrent threads. So developers should make their own benchmarks in scenarios close to their specific use cases. The following statements are rules of thumb which have to be verified in practice.

`AtomicInitializer` is probably the most efficient implementation due to its lack of synchronization and further checks. Its main drawback is that the `initialize()` method can be called multiple times. In cases where this is not an issue `AtomicInitializer` is a good choice. `AtomicSafeInitializer` and `LazyInitializer` both guarantee that the initialization method is called only once. Because `AtomicSafeInitializer` does not use synchronization it is probably slightly more efficient than `LazyInitializer`, but the concrete numbers might depend on the level of concurrency.

Another implementation of the `ConcurrentInitializer` interface is `BackgroundInitializer`. It is again an abstract base class with an `initialize()` method that has to be defined by concrete subclasses. The idea of `BackgroundInitializer` is that it calls the `initialize()` method in a separate worker thread. An application creates a background initializer and starts it. Then it can continue with its work while the initializer runs in parallel. When the application needs the results of the initializer it calls its `get()` method. `get()` blocks until the initialization is complete. This is useful for instance at application startup. Here initialization steps (e.g. reading configuration files, opening a database connection, etc.) can be run in background threads while the application shows a splash screen and constructs its UI.

As a concrete example consider an application that has to read the content of a URL - maybe a page with news - which is to be displayed to the user after login. Because loading the data over the network can take some time a specialized implementation of `BackgroundInitializer` can be created for this purpose:

     public class URLLoader extends BackgroundInitializer<String> {
       // The URL to be loaded.
       private final URL url;

       public URLLoader(URL u) {
         url = u;
       }

       protected String initialize() throws ConcurrentException {
         try {
           InputStream in = url.openStream();
           // read content into string
           ...
           return content;
         } catch (IOException ioex) {
           throw new ConcurrentException(ioex);
         }
       }
     }

An application creates an instance of `URLLoader` and starts it. Then it can do other things. When it needs the content of the URL it calls the initializer's `get()` method:

     URL url = new URL("http://www.application-home-page.com/");
     URLLoader loader = new URLLoader(url);
     loader.start();  // this starts the background initialization

     // do other stuff
     ...
     // now obtain the content of the URL
     String content;
     try {
       content = loader.get();  // this may block
     } catch (ConcurrentException cex) {
       content = "Error when loading URL " + url;
     }
     // display content

Related to `BackgroundInitializer` is the `MultiBackgroundInitializer` class. As the name implies, this class can handle multiple initializations in parallel. The basic usage scenario is that a `MultiBackgroundInitializer` instance is created. Then an arbitrary number of `BackgroundInitializer` objects is added using the `MultiBackgroundInitializer.addInitializer(String, BackgroundInitializer)` method. When adding an initializer a string has to be provided which is later used to obtain the result for this initializer. When all initializers have been added the `BackgroundInitializer.start()` method is called. This starts processing of all initializers. Later the `get()` method can be called. It waits until all initializers have finished their initialization. `get()` returns an object of type `MultiBackgroundInitializer.MultiBackgroundInitializerResults`. This object provides information about all initializations that have been performed. It can be checked whether a specific initializer was successful or threw an exception. Of course, all initialization results can be queried.

With `MultiBackgroundInitializer` we can extend our example to perform multiple initialization steps. Suppose that in addition to loading a web site we also want to create a JPA entity manager factory and read a configuration file. We assume that corresponding `BackgroundInitializer` implementations exist. The following example fragment shows the usage of `MultiBackgroundInitializer` for this purpose:

     MultiBackgroundInitializer initializer = new MultiBackgroundInitializer();
     initializer.addInitializer("url", new URLLoader(url));
     initializer.addInitializer("jpa", new JPAEMFInitializer());
     initializer.addInitializer("config", new ConfigurationInitializer());
     initializer.start();  // start background processing

     // do other interesting things in parallel
     ...
     // evaluate the results of background initialization
     MultiBackgroundInitializer.MultiBackgroundInitializerResults results =
     initializer.get();
     String urlContent = (String) results.getResultObject("url");
     EntityManagerFactory emf =
     (EntityManagerFactory) results.getResultObject("jpa");
     ...

The child initializers are added to the multi initializer and are assigned a unique name. The object returned by the `get()` method is then queried for the single results using these unique names.

If background initializers - including `MultiBackgroundInitializer` - are created using the standard constructor, they create their own `ExecutorService` which is used behind the scenes to execute the worker tasks. It is also possible to pass in an `ExecutorService` when the initializer is constructed. That way client code can configure the `ExecutorService` according to its specific needs; for instance, the number of threads available could be limited.

### Utility Classes

Another group of classes in the new `concurrent` package offers some generic functionality related to concurrency. There is the `ConcurrentUtils` class with a bunch of static utility methods. One focus of this class is dealing with exceptions thrown by JDK classes. Many JDK classes of the executor framework throw exceptions of type `ExecutionException` if something goes wrong. The root cause of these exceptions can also be a runtime exception or even an error. In typical Java programming you often do not want to deal with runtime exceptions directly; rather you let them fall through the hierarchy of method invocations until they reach a central exception handler. Checked exceptions in contrast are usually handled close to their occurrence. With `ExecutionException` this principle is violated. Because it is a checked exception, an application is forced to handle it even if the cause is a runtime exception. So you typically have to inspect the cause of the `ExecutionException` and test whether it is a checked exception which has to be handled. If this is not the case, the causing exception can be rethrown.

The `ConcurrentUtils.extractCause(java.util.concurrent.ExecutionException)` method does this work for you. It is passed an `ExecutionException` and tests its root cause. If this is an error or a runtime exception, it is directly rethrown. Otherwise, an instance of `ConcurrentException` is created and initialized with the root cause (`ConcurrentException` is a new exception class in the `o.a.c.l.concurrent` package). So if you get such a `ConcurrentException`, you can be sure that the original cause for the `ExecutionException` was a checked exception. For users who prefer runtime exceptions in general there is also an `ConcurrentUtils.extractCauseUnchecked(java.util.concurrent.ExecutionException)` method which behaves like `extractCause()`, but returns the unchecked exception `ConcurrentRuntimeException` instead.

In addition to the `extractCause()` methods there are corresponding `ConcurrentUtils.handleCause(java.util.concurrent.ExecutionException)` and `ConcurrentUtils.handleCauseUnchecked(java.util.concurrent.ExecutionException)` methods. These methods extract the cause of the passed in `ExecutionException` and throw the resulting `ConcurrentException` or `ConcurrentRuntimeException`. This makes it easy to transform an `ExecutionException` into a `ConcurrentException` ignoring unchecked exceptions:

     Future<Object> future = ...;
     try {
       Object result = future.get();
       ...
     } catch (ExecutionException eex) {
       ConcurrentUtils.handleCause(eex);
     }

There is also some support for the concurrent initializers introduced in the last sub section. The `initialize()` method is passed a `ConcurrentInitializer` object and returns the object created by this initializer. It is null-safe. The `initializeUnchecked()` method works analogously, but a `ConcurrentException` throws by the initializer is rethrown as a `ConcurrentRuntimeException`. This is especially useful if the specific `ConcurrentInitializer` does not throw checked exceptions. Using this method the code for requesting the object of an initializer becomes less verbose. The direct invocation looks as follows:

     ConcurrentInitializer<MyClass> initializer = ...;
     try {
       MyClass obj = initializer.get();
       // do something with obj
     } catch (ConcurrentException cex) {
       // exception handling
     }

Using the `ConcurrentUtils.initializeUnchecked(ConcurrentInitializer)` method, this becomes:

     ConcurrentInitializer<MyClass> initializer = ...;
     MyClass obj = ConcurrentUtils.initializeUnchecked(initializer);
     // do something with obj

Another utility class deals with the creation of threads. When using the Executor framework new in JDK 1.5 the developer usually does not have to care about creating threads; the executors create the threads they need on demand. However, sometimes it is desired to set some properties of the newly created worker threads. This is possible through the `ThreadFactory` interface; an implementation of this interface has to be created and passed to an executor on creation time. Currently, the JDK does not provide an implementation of `ThreadFactory`, so one has to start from scratch.

With `BasicThreadFactory` Commons Lang has an implementation of `ThreadFactory` that works out of the box for many common use cases. For instance, it is possible to set a naming pattern for the new threads, set the daemon flag and a priority, or install a handler for uncaught exceptions. Instances of `BasicThreadFactory` are created and configured using the nested `BasicThreadFactory.Builder` class. The following example shows a typical usage scenario:

     BasicThreadFactory factory = new BasicThreadFactory.Builder()
       .namingPattern("worker-thread-%d")
       .daemon(true)
       .uncaughtExceptionHandler(myHandler)
       .build();
     ExecutorService exec = Executors.newSingleThreadExecutor(factory);

The nested `Builder` class defines some methods for configuring the new `BasicThreadFactory` instance. Objects of this class are immutable, so these attributes cannot be changed later. The naming pattern is a string which can be passed to `String.format()`. The placeholder %d is replaced by an increasing counter value. An instance can wrap another `ThreadFactory` implementation; this is achieved by calling the builder's `wrappedFactory(ThreadFactory)` method. This factory is then used for creating new threads; after that the specific attributes are applied to the new thread. If no wrapped factory is set, the default factory provided by the JDK is used.

### Synchronization objects

The `concurrent` package also provides some support for specific synchronization problems with threads.

`TimedSemaphore` allows restricted access to a resource in a given time frame. Similar to a semaphore, a number of permits can be acquired. What is new is the fact that the permits available are related to a given time unit. For instance, the timed semaphore can be configured to allow 10 permits in a second. Now multiple threads access the semaphore and call its `TimedSemaphore.acquire()` method. The semaphore keeps track about the number of granted permits in the current time frame. Only 10 calls are allowed; if there are further callers, they are blocked until the time frame (one second in this example) is over. Then all blocking threads are released, and the counter of available permits is reset to 0. So the game can start anew.

What are use cases for `TimedSemaphore`? One example is to artificially limit the load produced by multiple threads. Consider a batch application accessing a database to extract statistical data. The application runs multiple threads which issue database queries in parallel and perform some calculation on the results. If the database to be processed is huge and is also used by a production system, multiple factors have to be balanced: On one hand, the time required for the statistical evaluation should not take too long. Therefore you will probably use a larger number of threads because most of its life time a thread will just wait for the database to return query results. On the other hand, the load on the database generated by all these threads should be limited so that the responsiveness of the production system is not affected. With a `TimedSemaphore` object this can be achieved. The semaphore can be configured to allow e.g. 100 queries per second. After these queries have been sent to the database the threads have to wait until the second is over - then they can query again. By fine-tuning the limit enforced by the semaphore a good balance between performance and database load can be established. It is even possible to chang? the number of available permits at runtime. So this number can be reduced during the typical working hours and increased at night.

The following code examples demonstrate parts of the implementation of such a scenario. First the batch application has to create an instance of `TimedSemaphore` and to initialize its properties with default values:

`TimedSemaphore semaphore = new TimedSemaphore(1, TimeUnit.SECONDS, 100);`

Here we specify that the semaphore should allow 100 permits in one second. This is effectively the limit of database queries per second in our example use case. Next the server threads issuing database queries and performing statistical operations can be initialized. They are passed a reference to the semaphore at creation time. Before they execute a query they have to acquire a permit.

     public class StatisticsTask implements Runnable {
     // The semaphore for limiting database load.
       private final TimedSemaphore semaphore;

       public StatisticsTask(TimedSemaphore sem, Connection con) {
         semaphore = sem;
          ...
       }

       //The main processing method. Executes queries and evaluates their results.
       public void run() {
         try {
           while (!isDone()) {
             semaphore.acquire();    // enforce the load limit
             executeAndEvaluateQuery();
           }
         } catch (InterruptedException iex) {
           // fall through
         }
       }
     }

The important line here is the call to `semaphore.acquire()`. If the number of permits in the current time frame has not yet been reached, the call returns immediately. Otherwise, it blocks until the end of the time frame. The last piece missing is a scheduler service which adapts the number of permits allowed by the semaphore according to the time of day. We assume that this service is pretty simple and knows only two different time slots: working shift and night shift. The service is triggered periodically. It then determines the current time slot and configures the timed semaphore accordingly.

     public class SchedulerService {
       // The semaphore for limiting database load.
       private final TimedSemaphore semaphore;
         ...

       // Configures the timed semaphore based on the current time of day. This method is called periodically.
       public void configureTimedSemaphore() {
          int limit;
          if (isWorkshift()) {
            limit = 50;    // low database load
          } else {
            limit = 250;   // high database load
          }

          semaphore.setLimit(limit);
       }
     }

With the `TimedSemaphore.setLimit(int)` method the number of permits allowed for a time frame can be changed. There are some other methods for querying the internal state of a timed semaphore. Also some statistical data is available, e.g. the average number of `acquire()` calls per time frame. When a timed semaphore is no more needed, its `shutdown()` method has to be called.

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