Java concurrency (multi-threading)

Table of Contents
Java concurrency (multi-threading). This article describes how to do concurrent programming with Java. It covers the concepts of parallel programming, immutability, threads, the executor framework (thread pools), futures, callables CompletableFuture and the fork-join framework.

1. Concurrency

1.1. What is concurrency?

Concurrency is the ability to run several programs or several parts of a program in parallel. If a time consuming task can be performed asynchronously or in parallel, this improve the throughput and the interactivity of the program.

A modern computer has several CPU’s or several cores within one CPU. The ability to leverage these multi-cores can be the key for a successful high-volume application.

1.2. Process vs. threads

A process runs independently and isolated of other processes. It cannot directly access shared data in other processes. The resources of the process, e.g. memory and CPU time, are allocated to it via the operating system.

A thread is a so called lightweight process. It has its own call stack, but can access shared data of other threads in the same process. Every thread has its own memory cache. If a thread reads shared data it stores this data in its own memory cache. A thread can re-read the shared data.

A Java application runs by default in one process. Within a Java application you work with several threads to achieve parallel processing or asynchronous behavior.

2. Improvements and issues with concurrency

2.1. Limits of concurrency gains

Within a Java application you work with several threads to achieve parallel processing or asynchronous behavior. Concurrency promises to perform certain task faster as these tasks can be divided into subtasks and these subtasks can be executed in parallel. Of course the runtime is limited by parts of the task which can be performed in parallel.

The theoretical possible performance gain can be calculated by the following rule which is referred to as Amdahl’s Law.

If F is the percentage of the program which can not run in parallel and N is the number of processes, then the maximum performance gain is 1 / (F+ ((1-F)/n)).

2.2. Concurrency issues

Threads have their own call stack, but can also access shared data. Therefore you have two basic problems, visibility and access problems.

A visibility problem occurs if thread A reads shared data which is later changed by thread B and thread A is unaware of this change.

An access problem can occur if several thread access and change the same shared data at the same time.

Visibility and access problem can lead to

  • Liveness failure: The program does not react anymore due to problems in the concurrent access of data, e.g. deadlocks.
  • Safety failure: The program creates incorrect data.

3. Concurrency in Java

3.1. Processes and Threads

A Java program runs in its own process and by default in one thread. Java supports threads as part of the Java language via the Thread code. The Java application can create new threads via this class.

Java 1.5 also provides improved support for concurrency with the in the java.util.concurrent package.

3.2. Locks and thread synchronization

Java provides locks to protect certain parts of the code to be executed by several threads at the same time. The simplest way of locking a certain method or Java class is to define the method or class with the synchronized keyword.

The synchronized keyword in Java ensures:

  • that only a single thread can execute a block of code at the same time
  • that each thread entering a synchronized block of code sees the effects of all previous modifications that were guarded by the same lock

Synchronization is necessary for mutually exclusive access to blocks of and for reliable communication between threads.

You can use the synchronized keyword for the definition of a method. This would ensure that only one thread can enter this method at the same time. Another threads which is calling this method would wait until the first threads leaves this method.

You can also use the synchronized keyword to protect blocks of code within a method. This block is guarded by a key, which can be either a string or an object. This key is called the lock.

All code which is protected by the same lock can only be executed by one thread at the same time

For example the following datastructure will ensure that only one thread can access the inner block of the add() and next() methods.

3.3. Volatile

If a variable is declared with the volatile keyword then it is guaranteed that any thread that reads the field will see the most recently written value. The volatile keyword will not perform any mutual exclusive lock on the variable.

As of Java 5 write access to a volatile variable will also update non-volatile variables which were modified by the same thread. This can also be used to update values within a reference variable, e.g. for a volatile variable person. In this case you must use a temporary variable person and use the setter to initialize the variable and then assign the temporary variable to the final variable. This will then make the address changes of this variable and the values visible to other threads.

4. The Java memory model

4.1. Overview

The Java memory model describes the communication between the memory of the threads and the main memory of the application.

It defines the rules how changes in the memory done by threads are propagated to other threads.

The Java memory model also defines the situations in which a thread re-fresh its own memory from the main memory.

It also describes which operations are atomic and the ordering of the operations.

4.2. Atomic operation

An atomic operation is an operation which is performed as a single unit of work without the possibility of interference from other operations.

The Java language specification guarantees that reading or writing a variable is an atomic operation(unless the variable is of type long or double ). Operations variables of type long or double are only atomic if they declared with the volatile keyword.

Assume i is defined as int. The i++ (increment) operation it not an atomic operation in Java. This also applies for the other numeric types, e.g. long. etc).

The i++ operation first reads the value which is currently stored in i (atomic operations) and then it adds one to it (atomic operation). But between the read and the write the value of i might have changed.

Since Java 1.5 the java language provides atomic variables, e.g. AtomicInteger or AtomicLong which provide methods like getAndDecrement(), getAndIncrement() and getAndSet() which are atomic.

4.3. Memory updates in synchronized code

The Java memory model guarantees that each thread entering a synchronized block of code sees the effects of all previous modifications that were guarded by the same lock.

5. Immutability and Defensive Copies

5.1. Immutability

The simplest way to avoid problems with concurrency is to share only immutable data between threads. Immutable data is data which cannot changed.

To make a class immutable make

  • all its fields final
  • the class declared as final
  • the this reference is not allowed to escape during construction
  • Any fields which refer to mutable data objects are
  • private
  • have no setter method
  • they are never directly returned of otherwise exposed to a caller
  • if they are changed internally in the class this change is not visible and has no effect outside of the class

An immutable class may have some mutable data which is uses to manages its state but from the outside this class nor any attribute of this class can get changed.

For all mutable fields, e.g. Arrays, that are passed from the outside to the class during the construction phase, the class needs to make a defensive-copy of the elements to make sure that no other object from the outside still can change the data

5.2. Defensive Copies

You must protect your classes from calling code. Assume that calling code will do its best to change your data in a way you didn’t expect it. While this is especially true in case of immutable data it is also true for non-immutable data which you still not expect that this data is changed outside your class.

To protect your class against that you should copy data you receive and only return copies of data to calling code.

The following example creates a copy of a list (ArrayList) and returns only the copy of the list. This way the client of this class cannot remove elements from the list.

6. Threads in Java

The base means for concurrency are is the java.lang.Threads class. A Thread executes an object of type java.lang.Runnable.

Runnable is an interface with defines the run() method. This method is called by the Thread object and contains the work which should be done. Therefore the “Runnable” is the task to perform. The Thread is the worker who is doing this task.

The following demonstrates a task (Runnable) which counts the sum of a given range of numbers. Create a new Java project called de.vogella.concurrency.threads for the example code of this section.

The following example demonstrate the usage of the Thread and the Runnable class.

Using the Thread class directly has the following disadvantages.

  • Creating a new thread causes some performance overhead.
  • Too many threads can lead to reduced performance, as the CPU needs to switch between these threads.
  • You cannot easily control the number of threads, therefore you may run into out of memory errors due to too many threads.

The java.util.concurrent package offers improved support for concurrency compared to the direct usage of Threads. This package is described in the next section.

7. Threads pools with the Executor Framework

You find this examples in the source section in Java project called de.vogella.concurrency.threadpools.

Thread pools manage a pool of worker threads. The thread pools contains a work queue which holds tasks waiting to get executed.

A thread pool can be described as a collection of Runnable objects.

(work queue) and a connections of running threads. These threads are constantly running and are checking the work query for new work. If there is new work to be done they execute this Runnable. The Thread class itself provides a method, e.g. execute(Runnable r) to add a new Runnable object to the work queue.

The Executor framework provides example implementation of the java.util.concurrent.Executor interface, e.g. Executors.newFixedThreadPool(int n) which will create n worker threads. The ExecutorService adds life cycle methods to the Executor, which allows to shutdown the Executor and to wait for termination.

If you want to use one thread pool with one thread which executes several runnables you can use the Executors.newSingleThreadExecutor() method.

Create again the Runnable.

Now you run your runnables with the executor framework.

In case the threads should return some value (result-bearing threads) then you can use the java.util.concurrent.Callable class.

8. Futures and Callables

8.1. Futures and Callables

The executor framework presented in the last chapter uses Runnable objects. Unfortunately a Runnable cannot return a result to the caller.

In case you expect your threads to return a computed result you can use java.util.concurrent.Callable. The Callable object allows to return values after completion.

The Callable object uses generics to define the type of object which is returned.

If you submit a Callable object to an Executor, the framework returns an object of type java.util.concurrent.Future. Future exposes methods allowing a client to monitor the progress of a task being executed by a different thread. Therefore, a Future object can be used to check the status of a Callable. It can also be used to retrieve the result from the Callable.

On the Executor you can use the method submit to submit a Callable and to get a future. To retrieve the result of the future use the get() method.

8.2. Drawbacks with Futures and Callables

The Future interface is limited as a model of asynchronously executed tasks. Future allows a client to query a Callable task for its result. It does not provide the option to register a callback method. A callback method would allow you to get a callback once a task is done. In Java 5 you could use ExecutorCompletionService for this purpose but as of Java 8 you can use the CompletableFuture interface which allows to provide a callback interface which is called once a task is completed.

9. CompletableFuture

Asynchronous task handling is important for any application which performs time consuming activities, as IO operations. Two basic approaches to asynchronous task handling are available to a Java application:

  • application logic blocks until a task completes
  • application logic is called once the task completes, this is called a nonblocking approach.

CompletableFuture extends the functionality of the Future interface for asynchronous calls. It also implements the CompletionStage interface. CompletionStage offers methods, that let you attach callbacks that will be executed on completion.

It adds standard techniques for executing application code when a task completes, including various ways to combine tasks. CompletableFuture support both blocking and nonblocking approaches, including regular callbacks.

This callback can be executed in another thread as the thread in which the CompletableFuture is executed.

The following example demonstrates how to create a basic CompletableFuture.

CompletableFuture.supplyAsync runs the task asynchronously on the default thread pool of Java. It has the option to supply your custom executor to define the ThreadPool.

The usage of the thenApply method is demonstrated by the following code snippet.

10. Nonblocking algorithms

Java 5.0 provides supports for additional atomic operations. This allows to develop algorithm which are non-blocking algorithm, e.g. which do not require synchronization, but are based on low-level atomic hardware primitives such as compare-and-swap (CAS). A compare-and-swap operation check if the variable has a certain value and if it has this value it will perform this operation.

Non-blocking algorithms are typically faster than blocking algorithms, as the synchronization of threads appears on a much finer level (hardware).

For example this created a non-blocking counter which always increases. This example is contained in the project called de.vogella.concurrency.nonblocking.counter.

And a test.

The interesting part is how the incrementAndGet() method is implemented. It uses a CAS operation.

The JDK itself makes more and more use of non-blocking algorithms to increase performance for every developer. Developing correct non-blocking algorithm is not a trivial task.

For more information on non-blocking algorithm, e.g. examples for a non-blocking Stack and non-block LinkedList, please see

11. Fork-Join in Java 7

Java 7 introduce a new parallel mechanism for compute intensive tasks, the fork-join framework. The fork-join framework allows you to distribute a certain task on several workers and then wait for the result.

For Java 6.0 you can download the package (jsr166y) from the Download site.

For testing create the Java project “de.vogella.performance.forkjoin”. If you are not using Java 7 you also need to jsr166y.jar to the classpath.

Create first a algorithm package and then the following class.

Define now the Solver class as shown in the following example coding.

The API defines other top classes, e.g. RecursiveAction, AsyncAction. Check the Javadoc for details.

Now define a small test class for testing it efficiency.

12. Deadlock

A concurrent application has the risk of a deadlock. A set of processes are deadlocked if all processes are waiting for an event which another process in the same set has to cause.

For example if thread A waits for a lock on object Z which thread B holds and thread B wait for a look on object Y which is hold be process A then these two processes are locked and cannot continue in their processing.

This can be compared to a traffic jam, where cars(threads) require the access to a certain street(resource), which is currently blocked by another car(lock).


Copyright © 2012-2017 vogella GmbH. Free use of the software examples is granted under the terms of the EPL License. This tutorial is published under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Germany license.

See Licence.



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