Atomic variables in Java have gained significant importance over the years, especially in high-concurrency applications. They are essential to building efficient, scalable, and thread-safe programs. Without atomic variables, managing shared mutable state between threads becomes increasingly complex and error-prone, leading to subtle and hard-to-diagnose bugs such as race conditions.
Atomic variables provide a lower-level, lock-free mechanism for handling concurrent operations on a single variable. They are a cornerstone for building complex lock-free data structures and algorithms. They can significantly boost the performance of your concurrent applications when used properly, thus understanding them and their efficient usage is crucial for any serious Java developer.
This guide is designed for intermediate to advanced Java developers who already have a basic understanding of Java’s threading and concurrency concepts. It’s suitable for those who want to delve deeper into Java’s atomic variables, understand how to use them efficiently, and apply them to solve real-world concurrency problems. Whether you are working on a highly concurrent system, or you just want to boost your knowledge and skills in Java’s concurrency utilities, this guide offers valuable insights that will help you on your path.
Background of Atomic Variables
The need for Atomic Variables: Understanding Race Conditions
In concurrent programming, race conditions occur when two or more threads can access shared data and they try to change it at the same time. As a result, the values of variables may be unpredictable as they can depend on the timings of context switches of the threads. Race conditions can lead to unpredictable results and subtle programming bugs that can be hard to detect and fix.
Atomic variables in Java come into play as a solution to these race conditions. The word ‘atomic’ comes from the Greek word ‘atomos’, meaning indivisible. In programming terms, an atomic operation is one that effectively happens all at once, without the possibility of interruption.
Java’s atomic variables provide a way for you to manipulate single variables without worrying about race conditions, thus making your code thread-safe without resorting to explicit synchronization, which can be more expensive and may decrease performance.
Java Memory Model and Happens-Before Consistency
The Java Memory Model (JMM) is a specification that guarantees that the Java Virtual Machine (JVM) will see a consistent view of memory. It sets rules around how and when changes made by one thread become visible to others. The JMM is essential for understanding how atomic variables work under the hood.
One of the key aspects of the JMM is the happens-before relationship, which is a guarantee that memory writes by one specific statement are visible to another specific statement. Atomic variables in Java have clearly defined happens-before relationships that make their operations thread-safe.
Introduction to Java’s Concurrency Package
Java provides a rich set of tools for creating multi-threaded applications through its java.util.concurrent package. This package contains a set of high-performance, well-tested utility classes that are indispensable for creating reliable, scalable, and efficient concurrent applications.
Among the various tools offered by the java.util.concurrent package, one set of classes stands out for handling atomic operations: the atomic package (java.util.concurrent.atomic). This package provides atomicity for operations such as incrementing a value (incrementAndGet()), decrementing a value (decrementAndGet()), adding to a current value (addAndGet()), and comparing and swapping values (compareAndSet()), among others.
These atomic classes are thread-safe but the key advantage is that they perform these compound operations atomically without the use of locks, which makes them faster and more scalable under high contention.
Basics of Java’s Atomic Variables
Types of Atomic Variables in Java
Java provides a variety of atomic classes to support atomic operations on single variables, which can be broadly classified as follows:
- Basic types: These classes provide atomic operations on single variables of the corresponding type. This includes classes such as
AtomicBoolean,AtomicInteger,AtomicLong, andAtomicReference. - Array types: These classes provide atomic operations on elements within an array of the corresponding type. This includes classes such as
AtomicIntegerArray,AtomicLongArray, andAtomicReferenceArray. - Updaters: These classes can be used to atomically update fields of objects. This includes classes such as
AtomicIntegerFieldUpdater,AtomicLongFieldUpdater, andAtomicReferenceFieldUpdater. - Accumulators and Adders: These classes provide high throughput under high contention. This includes classes like
LongAccumulator,LongAdder,DoubleAccumulator, andDoubleAdder. - Advanced classes: These include
AtomicMarkableReferenceandAtomicStampedReference, which can be used for more advanced concurrent algorithms.
Atomic Variables Vs Volatile Keyword
While both atomic variables and the volatile keyword provide a mechanism for ensuring visibility of field changes across threads, they serve different purposes.
The volatile keyword in Java is used to mark a Java variable as “being stored in main memory”. More precisely, each read of a volatile variable will be read from the computer’s main memory, and not from the CPU cache, and each write to a volatile variable will be written to main memory, and not just to the CPU cache.
However, volatile only guarantees visibility; it does not guarantee atomicity. For instance, compound operations like incrementing a value (i++) are not atomic with volatile variables. If you need to perform compound operations atomically, atomic variables should be used.
Atomic Variables Vs Synchronized Blocks
While both atomic variables and synchronized blocks can be used to achieve thread safety, atomic variables have several advantages:
- Performance: Atomic variables typically offer better performance than synchronization. They internally use efficient machine-level atomic instructions provided by modern CPUs to ensure atomicity.
- Deadlock Safety: Since atomic operations do not acquire locks, they do not participate in deadlocks, which can occur with inappropriate use of synchronized blocks.
- Coding Simplicity: Atomic variables can be simpler to use correctly, because you don’t have to remember to use a synchronized block every time you access the variable.
However, synchronized blocks or methods are still necessary if you need to coordinate access to multiple related variables, or if you need to perform multiple operations as an atomic unit of work. Atomic variables can only guarantee atomicity of individual operations.
Working with Atomic Boolean
AtomicBoolean is a boolean value that may be updated atomically in a thread-safe manner. It is located in the java.util.concurrent.atomic package and is used when a boolean variable needs to be shared between multiple threads, ensuring the atomicity of operations on it. The atomic classes make heavy use of Compare-and-Swap (CAS), an atomic instruction directly supported by most modern CPU’s.
Practical Use Cases of Atomic Boolean
One common use case of AtomicBoolean is to check if some expensive operation is required. The operation can be executed by only one thread while other threads will see the updated value without executing the operation.
Another frequent use of AtomicBoolean is in implementing a non-blocking (lock-free) synchronization strategy, often used for flagging or signal mechanisms.
Coding Examples & Performance Analysis
Consider a scenario where we have multiple threads trying to execute some costly operation but only the first one should actually execute it:
class ExpensiveOperation implements Runnable {
private final AtomicBoolean shouldExecute;
public ExpensiveOperation(AtomicBoolean shouldExecute) {
this.shouldExecute = shouldExecute;
}
public void run() {
if (shouldExecute.compareAndSet(true, false)) {
// Only the first thread entering this block gets to execute the costly operation
System.out.println("Executing expensive operation by thread " + Thread.currentThread().getName());
// Here goes the costly operation...
}
}
}
public class AtomicBooleanExample {
public static void main(String[] args) {
AtomicBoolean shouldExecute = new AtomicBoolean(true);
for (int i = 0; i < 10; i++) {
new Thread(new ExpensiveOperation(shouldExecute)).start();
}
}
}Code language: Java (java)In this example, only the first thread will execute the expensive operation and then set the shouldExecute AtomicBoolean to false. All the other threads will see the false value and skip the execution block.
Performance-wise, using AtomicBoolean can provide significant benefits over using synchronized blocks in high contention scenarios. The AtomicBoolean relies on hardware level atomic instructions that are significantly faster than entering and exiting synchronized blocks. However, for less contended scenarios, the performance difference might not be noticeable.
Please note that the performance can greatly vary based on hardware, JVM, and the nature of the contention, therefore performance testing in the specific use case scenario is recommended.
Working with Atomic Integer
AtomicInteger is a class that provides you with a int value, which can be read and written atomically, and which also contains advanced atomic operations. These atomic operations cannot be performed on an ordinary int variable. AtomicInteger is located in the java.util.concurrent.atomic package, and it provides various methods to perform atomic operations.
Practical Use Cases of Atomic Integer
AtomicInteger is commonly used for counters in multithreaded environments where the variable might be updated by multiple threads concurrently. AtomicInteger provides atomic operations like increment, decrement and add, which ensures that these operations are atomic and avoids race conditions.
Coding Examples & Performance Analysis
Let’s look at a simple example where we use AtomicInteger as a counter in a multi-threaded environment:
class Counter {
private AtomicInteger count = new AtomicInteger(0);
public void increment() {
count.incrementAndGet();
}
public int getCount() {
return count.get();
}
}
public class AtomicIntegerExample {
public static void main(String[] args) throws InterruptedException {
Counter counter = new Counter();
Thread t1 = new Thread(() -> {
for (int i = 0; i < 1000; i++) {
counter.increment();
}
});
Thread t2 = new Thread(() -> {
for (int i = 0; i < 1000; i++) {
counter.increment();
}
});
t1.start();
t2.start();
t1.join();
t2.join();
System.out.println("Final Count is : " + counter.getCount());
}
}Code language: Java (java)In the example above, two threads are incrementing the same counter. AtomicInteger ensures that increments are atomic, and no increments are lost.
When it comes to performance, AtomicInteger offers an advantage over traditional synchronization under high contention (many threads frequently trying to update the counter at the same time). It avoids the overhead of acquiring and releasing locks.
However, under low contention scenarios (few threads or updates are infrequent), the performance difference between AtomicInteger and a synchronized block might be negligible.
It’s also important to consider that AtomicInteger provides atomic operations for single variables. If you need to synchronize access to multiple related variables, you would need to use a synchronized block or a Lock.
In terms of performance, it’s always best to benchmark different solutions under conditions that closely resemble your actual use case, as the results can vary depending on the specifics of your hardware and software environment.
Working with Atomic Long
AtomicLong is a long value that may be updated atomically. Like AtomicInteger, AtomicLong is used in a multithreaded environment to provide atomic operations for a long value. It is part of the java.util.concurrent.atomic package and it includes methods for addition, increment, decrement and it also includes a method to get the current value.
Practical Use Cases of Atomic Long
AtomicLong is often used for counters and sequence generator in multithreaded environments. It can also be used for rate limiting, in which case the AtomicLong could represent the number of requests made in a certain time frame.
Coding Examples & Performance Analysis
Let’s look at an example where we use AtomicLong as a sequence generator:
class SequenceGenerator {
private AtomicLong sequence = new AtomicLong(0);
public long next() {
return sequence.incrementAndGet();
}
}
public class AtomicLongExample {
public static void main(String[] args) throws InterruptedException {
SequenceGenerator sequenceGenerator = new SequenceGenerator();
Thread t1 = new Thread(() -> {
for (int i = 0; i < 1000; i++) {
System.out.println("Thread 1: " + sequenceGenerator.next());
}
});
Thread t2 = new Thread(() -> {
for (int i = 0; i < 1000; i++) {
System.out.println("Thread 2: " + sequenceGenerator.next());
}
});
t1.start();
t2.start();
t1.join();
t2.join();
}
}Code language: Java (java)In the example above, two threads are requesting sequence numbers from the same SequenceGenerator. AtomicLong ensures that each request gets a unique sequence number, even when the requests happen concurrently.
As with AtomicInteger, AtomicLong is more efficient than synchronized blocks when contention is high (many threads trying to update the same value frequently). It avoids the overhead of acquiring and releasing locks.
However, under low contention scenarios (few threads or updates are infrequent), the performance difference between AtomicLong and a synchronized block might be negligible.
Again, it’s important to understand that AtomicLong only provides atomicity for individual variables. If you need to synchronize access to multiple related variables or need multiple operations to be atomic, you would need to use a synchronized block or a Lock.
Working with Atomic Reference
AtomicReference is a class in java.util.concurrent.atomic package that provides an object reference variable which can be read and written atomically. AtomicReference supports atomic operations on a reference type. It means that we can read and write a reference to an object atomically, and it’s thread-safe.
Practical Use Cases of Atomic Reference
AtomicReference is often used in lock-free algorithms and data structures. For example, it can be used to create atomic arrays, lists, sets, and other complex atomic classes. Moreover, AtomicReference is used when we need to change the reference to an object atomically to ensure that an object’s reference is completely formed when it’s accessed by another thread.
Another practical use case is the implementation of atomic “check-then-act” operations. These operations first check a condition and then act upon it, and these two operations as a whole need to be atomic.
Coding Examples & Performance Analysis
Let’s look at a simple example of using AtomicReference:
import java.util.concurrent.atomic.AtomicReference;
public class AtomicReferenceExample {
static class Book {
private String title;
public Book(String title) {
this.title = title;
}
public String getTitle() {
return title;
}
}
public static void main(String[] args) {
AtomicReference<Book> atomicReference = new AtomicReference<>(new Book("The Old Man and The Sea"));
new Thread(() -> {
System.out.println("Thread 1 Current book is: " + atomicReference.get().getTitle());
try {
Thread.sleep(2000);
atomicReference.compareAndSet(new Book("The Old Man and The Sea"), new Book("The Great Gatsby"));
} catch (InterruptedException e) {
e.printStackTrace();
}
}).start();
new Thread(() -> {
try {
Thread.sleep(1000);
atomicReference.compareAndSet(new Book("The Old Man and The Sea"), new Book("Moby Dick"));
System.out.println("Thread 2 Current book is: " + atomicReference.get().getTitle());
} catch (InterruptedException e) {
e.printStackTrace();
}
}).start();
}
}Code language: Java (java)In the above example, we have an AtomicReference to a Book object. Two threads are trying to update the book title concurrently. AtomicReference ensures that these updates are atomic, and the result will be deterministic.
When it comes to performance, AtomicReference provides better throughput under high contention scenarios compared to using synchronized blocks. As with other atomic classes, it is able to provide atomic operations without the overhead of acquiring and releasing locks.
However, under low contention scenarios, the performance difference between AtomicReference and synchronized blocks might be negligible.
Atomic Array Classes
Java provides atomic array classes: AtomicIntegerArray, AtomicLongArray, and AtomicReferenceArray. These classes are part of the java.util.concurrent.atomic package and provide a way to work with arrays in a thread-safe manner.
- AtomicIntegerArray provides an array of integer values that can be updated atomically. It means that we can read and write integer values in the array without worrying about thread safety.
- AtomicLongArray is similar to AtomicIntegerArray but for long values. It provides an array of long values that can be updated atomically.
- AtomicReferenceArray is an array class that provides an array of object reference variables which can be read and written atomically. It means we can read and write an object reference in the array atomically.
Practical Use Cases
Atomic array classes are used in multithreaded environments where we need to perform atomic operations on array elements. They are often used in high performance concurrent algorithms and data structures.
Coding Examples & Performance Analysis
Here’s an example using AtomicIntegerArray:
import java.util.concurrent.atomic.AtomicIntegerArray;
public class AtomicIntegerArrayExample {
public static void main(String[] args) {
AtomicIntegerArray atomicIntegerArray = new AtomicIntegerArray(10);
Thread t1 = new Thread(() -> {
for (int i = 0; i < atomicIntegerArray.length(); i++) {
atomicIntegerArray.incrementAndGet(i);
}
});
Thread t2 = new Thread(() -> {
for (int i = 0; i < atomicIntegerArray.length(); i++) {
atomicIntegerArray.incrementAndGet(i);
}
});
t1.start();
t2.start();
try {
t1.join();
t2.join();
} catch (InterruptedException e) {
e.printStackTrace();
}
System.out.println(atomicIntegerArray);
}
}Code language: Java (java)In this example, we have an AtomicIntegerArray with a size of 10. Two threads increment each element in the array concurrently. AtomicIntegerArray ensures that the increments are atomic and the final array will be [2, 2, 2, 2, 2, 2, 2, 2, 2, 2].
Performance-wise, the atomic array classes offer significant advantages in high contention scenarios over using synchronized blocks or a volatile array. This is because atomic array classes use hardware level atomic instructions which are significantly faster than acquiring and releasing locks.
However, as with other atomic classes, under low contention scenarios, the performance difference might be negligible.
Advanced Concepts
Understanding Atomic Field Updater Classes
Atomic Field Updater classes are a part of the java.util.concurrent.atomic package that allows us to update volatile fields of objects atomically. They provide a way to update volatile fields of any object given the object reference and the field name, without having to create a new atomic object for every volatile field.
Java provides three types of Atomic Field Updaters:
AtomicIntegerFieldUpdater: Allows to update integer fields atomically.AtomicLongFieldUpdater: Allows to update long fields atomically.AtomicReferenceFieldUpdater: Allows to update reference fields atomically.
These classes are generally used when you have a large number of instances that each have an updatable field. They can be more memory-efficient than using atomic wrapper classes because they don’t require an extra atomic object for every field in your objects.
AtomicStampedReference and its use cases
AtomicStampedReference is a class in the java.util.concurrent.atomic package that provides an object reference variable which may be updated atomically with a “stamp”. The stamp is an integer value, that you can use to prevent ABA problems in lock-free data structures. The ABA problem is a situation where during a “compare and set” operation, a variable has the same value as it had at the time of comparison, but had been changed to another value and back between the time of comparison and the time of setting.
One common use case of AtomicStampedReference is to solve the ABA problem in concurrent stack and queue data structures. These data structures often use a linked list under the hood, and they need to atomically update the head of the list while also ensuring that the head has not been changed to a different node and back to the original node in the meantime.
The role of atomic variables in Java’s Fork/Join Framework
Java’s Fork/Join framework is a framework for parallel execution of recursive problems. It works by breaking a problem down into smaller subproblems that can be solved independently and in parallel, and then combining the results of these subproblems to get the final result.
Atomic variables play a crucial role in the Fork/Join framework. They are often used to collect results from the subtasks. Each subtask updates a shared atomic variable with its result, and these updates are safe from race conditions due to the atomic nature of the variable.
Atomic variables also play a role in controlling the execution of tasks in the Fork/Join framework. They can be used to keep track of the number of active tasks, and this count can be used to determine when to create new tasks and when to start combining results. This kind of control is essential for maximizing the parallelism of the Fork/Join framework.
Performance Considerations
Comparing Performance: Atomic Variables vs Synchronized Methods
When working in a multithreaded environment, a major concern is the efficiency and effectiveness of synchronization techniques. Let’s compare the two most common techniques: atomic variables and synchronized methods.
Atomic Variables – Atomic variables use low-level machine instructions (compare-and-swap (CAS), etc.) to achieve synchronization, avoiding the need for traditional lock-based synchronization. This allows multiple threads to read and write to the variable simultaneously, while still ensuring that the value remains consistent across all threads. As a result, atomic variables are usually more efficient under high contention scenarios where many threads are attempting to update the variable simultaneously.
Synchronized Methods – Synchronized methods use intrinsic locks or monitors to protect code blocks or methods from concurrent access by multiple threads. This ensures that only one thread can access the block or method at a time. While this guarantees thread safety, it comes with an overhead: threads must wait for the lock to be released if it’s held by another thread. This context-switching and waiting for locks to be released can degrade performance, particularly under high contention scenarios.
However, under low contention scenarios, the difference in performance between atomic variables and synchronized methods might be negligible. It’s always best to benchmark different solutions under conditions that closely resemble your actual use case.
Profiling Java’s Atomic Variables
Profiling involves measuring the resources used by different parts of your program, in this case, atomic variables. There are various tools like JProfiler, VisualVM, and YourKit that provide detailed statistics about memory, CPU usage, and the number of garbage collections that occur during the execution of your program.
To profile atomic variables, focus on key metrics such as memory usage (since each atomic variable has an overhead compared to a standard variable), CPU usage (as atomic variables can use more CPU due to CAS operations), and the number of garbage collections (since atomic variables don’t necessarily produce more garbage, but if they are used incorrectly they can).
Optimization Tips for Better Performance
- Minimize Contention: The performance of atomic variables degrades with contention. If possible, design your algorithms to minimize contention.
- Use Appropriate Data Structures: If multiple atomic variables need to be updated together, consider using concurrent data structures like
ConcurrentHashMapwhich are designed for such use cases. - Avoid Premature Optimization: Don’t assume that atomic variables are always faster. Test and profile your code to understand where the actual bottlenecks are.
- Understand Hardware Implications: The performance of atomic operations can depend on the underlying hardware, particularly the design of the CPU cache. Ensure your program runs efficiently on your target hardware.
- Avoid ABA Problem: If using
compareAndSetoperations, be aware of the ABA problem and consider usingAtomicStampedReferenceto avoid it. - Prefer
lazySetOverset: If order of writes is not important, consider usinglazySetmethods. They have less memory visibility guarantees, but are faster because they avoid a memory fence operation.
Best Practices and Pitfalls
Do’s and Don’ts when using Atomic Variables
Do’s
- Use the right atomic class: Use the atomic class that matches your data type. Using the wrong atomic class could lead to unexpected behavior or performance issues.
- Use atomic classes for simple state: Atomic classes are great for maintaining simple state across threads, such as a counter or a flag.
- Take advantage of hardware acceleration: Atomic variables leverage hardware-level support for atomic operations, which can make them faster than alternatives in some scenarios.
- Use atomic classes for lock-free programming: If you’re creating a lock-free data structure or algorithm, atomic variables can be a very useful tool.
Don’ts
- Don’t use atomic variables for complex state: If you’re maintaining complex state across threads, you might need to use a more sophisticated concurrency control mechanism, such as a
Lockor aSemaphore. - Don’t forget about memory visibility: When one thread writes to an atomic variable, that change is immediately made visible to all other threads. This is usually what you want, but if it’s not, you might need to consider other options.
- Don’t use atomic variables when you need synchronization: Atomic variables provide atomicity, but they don’t provide the mutual exclusion that’s sometimes needed in multithreaded programming. If you need to synchronize access to a block of code (as opposed to a single variable), you’ll need to use a synchronized block or method.
Common Mistakes and How to Avoid Them
- Misunderstanding atomicity: Atomic variables only guarantee atomicity for single operations. If you’re performing multiple operations that need to be atomic as a whole, you’ll need to use other synchronization techniques.
- Assuming too much about performance: Atomic variables can be faster than locks in some scenarios, but not always. Performance depends on many factors, including the specific hardware and JVM you’re using, as well as the nature of the contention. Always benchmark your code under realistic conditions to understand its performance characteristics.
- Not handling the ABA problem: When using
compareAndSetoperations, be aware of the ABA problem. This problem occurs when a variable changes from value A to B and back to A between the time you read the value and when you try to set it. This can lead to unexpected behavior. UseAtomicStampedReferenceto avoid this problem. - Neglecting garbage collection: If you’re creating a lot of short-lived atomic variables, they can create pressure on the garbage collector, which can impact performance. Be mindful of how you’re using and discarding atomic variables.
When and where to use Atomic Variables
Use atomic variables in the following scenarios:
- When maintaining simple state across threads: If you have a simple piece of state, such as a counter or a flag, that needs to be shared across threads, an atomic variable can be an efficient and effective tool.
- When creating lock-free data structures or algorithms: Atomic variables provide atomic operations, which are a building block for lock-free and wait-free data structures and algorithms.
- When performance is a concern: In scenarios where many threads are trying to update a shared variable simultaneously, atomic variables can offer better performance than lock-based synchronization.
- When working with the Fork/Join framework: Atomic variables can be used to collect results from subtasks in a thread-safe manner.
Avoid using atomic variables:
- When maintaining complex state across threads: If your state consists of multiple variables that need to be updated together atomically, you’ll need to use other synchronization mechanisms, such as a lock or a semaphore.
- When synchronization is needed: Atomic variables don’t provide synchronization or mutual exclusion; they only ensure atomicity for single operations. If you need to ensure that a block of code is executed by only one thread at a time, you’ll need to use a synchronized block or method.
Remember, choosing the right concurrency control mechanism depends on the specific needs and constraints of your application, and atomic variables are just one tool among many in the toolbox.