com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.package-info Maven / Gradle / Ivy
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* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
/**
* Provides support classes for multi-threaded programming.
* This package is intended to be an extension to {@link 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 {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.ConcurrentInitializer} interface which provides just a
* single method:
*
*
*
*
* public interface ConcurrentInitializer<T> {
* T get() throws ConcurrentException;
* }
*
*
*
* A ConcurrentInitializer produces an object.
* By calling the {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.ConcurrentInitializer#get() get()} method the object managed by the initializer can be obtained.
* There are different implementations of the interface available
* addressing various use cases:
*
*
* {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.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 {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.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 {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.LazyInitializer#initialize() 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 {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.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 {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.AtomicInitializer#initialize() 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 {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.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 {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.AtomicSafeInitializer#initialize() 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 {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.BackgroundInitializer}.
* It is again an abstract base class with an {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.BackgroundInitializer#initialize() 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 {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.MultiBackgroundInitializer} class.
* As the name implies, this class can handle multiplie 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 {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.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 {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.MultiBackgroundInitializer#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 {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.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 {@link java.util.concurrent.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 {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.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 {@link java.util.concurrent.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 {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.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 {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.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 {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.ConcurrentUtils#extractCauseUnchecked(java.util.concurrent.ExecutionException)} method which behaves like extractCause(), but returns the unchecked exception {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.ConcurrentRuntimeException} instead.
*
* In addition to the extractCause() methods there are corresponding {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.ConcurrentUtils#handleCause(java.util.concurrent.ExecutionException)} and {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.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 {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.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 {@link java.util.concurrent.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 {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.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 {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.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 {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.BasicThreadFactory.Builder#wrappedFactory(java.util.concurrent.ThreadFactory) 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.
*
* {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.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 {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.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 {@link com.aliyun.openservices.ons.shaded.commons.lang3.concurrent.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.
*/
package com.aliyun.openservices.ons.shaded.commons.lang3.concurrent;