Java Concurrency Patterns: Mastering Multithreading and Asynchronous Techniques

Java Concurrency Patterns

Mastering Multithreading and Asynchronous Techniques

Copyright © 2024 by NOB TREX L.L.C.

All rights reserved. No part of this publication may be reproduced, distributed, or transmitted in any form or by any means, including photocopying, recording, or other electronic or mechanical methods, without the prior written permission of the publisher, except in the case of brief quotations embodied in critical reviews and certain other noncommercial uses permitted by copyright law.

Contents

1 Introduction to Java Concurrency

1.1 Concurrency in Java

1.2 Concurrency vs. Parallelism

1.3 Challenges of Concurrent Programming

1.4 Benefits of Using Concurrency

1.5 Basic Concepts: Processes and Threads

1.6 The Java Memory Model

1.7 Thread Lifecycle and States

1.8 Creating Threads in Java

1.9 Using Runnable to Create Threads

1.10 Daemon vs User Threads

1.11 Thread Priorities in Java

2 Understanding Threads and Runnable

2.1 Introduction to Threads

2.2 Creating Threads with the Thread Class

2.3 Implementing the Runnable Interface

2.4 Thread vs Runnable: When to Use Which?

2.5 Starting and Stopping Threads

2.6 Thread Interruption

2.7 Handling Exceptions in Threads

2.8 Thread Communication: Wait, Notify, and NotifyAll

2.9 Thread Coordination with join()

2.10 Thread States and Life Cycle

2.11 Advanced Runnable Concepts

3 Synchronization and Locks

3.1 Understanding Synchronization

3.2 Synchronized Methods

3.3 Synchronized Blocks

3.4 Understanding Locks in Java

3.5 Reentrant Locks

3.6 ReadWrite Locks

3.7 Fairness in Locks

3.8 Locks vs. Synchronized Blocks

3.9 Avoiding Deadlocks in Java Applications

3.10 Starvation and Livelock

3.11 Best Practices with Synchronization and Locks

4 Concurrent Collections and Classes

4.1 Overview of Concurrent Collections

4.2 Using ConcurrentHashMap

4.3 Understanding CopyOnWriteArrayList and CopyOnWriteArraySet in Java’s Concurrent Collections

4.4 Blocking Queues and Their Usage

4.5 ConcurrentLinkedQueue and ConcurrentLinkedDeque

4.6 ConcurrentSkipListMap and

ConcurrentSkipListSet

4.7 Synchronizers: Semaphore, CyclicBarrier, and CountDownLatch

4.8 Exchanger in Concurrent Programming

4.9 Comparing Concurrent Collections with Synchronized Collections

4.10 Atomic Variables and Their Importance

4.11 Achieving Thread Safety with Concurrent Classes

5 Executor Framework and Thread Pools

5.1 Introduction to Executor Framework

5.2 Creating and Configuring Executors

5.3 Using ThreadPoolExecutor

5.4 ScheduledExecutors for Timed and Periodic Tasks

5.5 Shutting Down Executors Properly

5.6 Handling Rejected Tasks

5.7 Customizing Thread Behaviors in Thread Pools

5.8 Work Stealing Pool and Fork/Join Framework

5.9 Choosing the Right Executor and Configuration

5.10 Common Pitfalls in Using Executors

5.11 Monitoring and Performance of Thread Pools

6 Futures and Callable

6.1 Understanding Futures and Callables

6.2 Creating Callable Tasks

6.3 Submitting Callable Tasks to an Executor Service

6.4 Retrieving Results with Future

6.5 Managing Timeouts in Concurrent Programming

6.6 Handling Exceptions with Future and Callable

6.7 Exploring FutureTask for Efficient Pre-load Computations

6.8 Cancelling Callable Tasks

6.9 Completable Futures Introduction

6.10 Combining and Composing Futures for Data Dependency

6.11 Asynchronous Computation Patterns with Futures

6.12 Best Practices with Futures and Callable

7 CompletableFuture and Asynchronous Programming

7.1 Introduction to CompletableFuture

7.2 Creating a CompletableFuture

7.3 Completing a CompletableFuture Manually

7.4 Running Asynchronous Computations with runAsync

7.5 Applying Functions Asynchronously with thenApply

7.6 Combining CompletableFutures with thenCombine

7.7 Handling Errors and Recovering from Failures

7.8 Asynchronous Programming Patterns with CompletableFuture

7.9 Using thenAccept and thenRun for Async Actions

7.10 Applying Multiple Futures Together

7.11 Testing and Debugging CompletableFutures

7.12 Best Practices in Asynchronous Programming with CompletableFuture

8 The Reactive Streams API

8.1 Introduction to Reactive Streams

8.2 Understanding the Publisher-Subscriber Model

8.3 Creating Publishers and Subscribers

8.4 Backpressure: Managing Data Flow

8.5 Using the Processor to Transform Data

8.6 Building Reactive APIs with Reactive Streams

8.7 Integrating Reactive Streams with CompletableFuture

8.8 Utilizing Third-party Libraries for Reactive Streams

8.9 Testing Reactive Streams

8.10 Error Handling in Reactive Streams

8.11 Performance Considerations in Reactive Programming

9 Best Practices and Testing Concurrent Applications

9.1 Best Practices in Concurrency

9.2 Writing Thread-Safe Code

9.3 Utilizing Immutable Objects and Classes

9.4 Concurrency Design Patterns

9.5 Avoiding Deadlocks, Starvation, and Livelock

9.6 Memory Management in Concurrent Applications

9.7 Testing Concurrent Applications

9.8 Tools for Debugging Concurrent Applications

9.9 Profiling and Performance Tuning

9.10 Scalability Considerations

9.11 Maintaining and Refactoring Legacy Concurrent Code

10 Performance Considerations and Troubleshooting

10.1 Understanding Performance in Concurrent Applications

10.2 Measuring and Analyzing Performance in Java Concurrent Applications

10.3 Identifying Bottlenecks

10.4 Optimization Techniques for Concurrency

10.5 Memory and CPU Optimization

10.6 Choosing the Right Concurrency Model

10.7 Effective Use of Thread Pools

10.8 Troubleshooting Common Issues in Concurrent Java Applications

10.9 Using Profiling Tools for Java Applications

10.10 Handling Race Conditions and Deadlocks

10.11 Performance Testing and Benchmarks

Preface

Welcome to Java Concurrency Patterns: Mastering Multithreading and Asynchronous Techniques. This book is meticulously crafted to serve as a comprehensive guide to mastering the intricacies of Java Concurrency, addressing multithreading, synchronization, and asynchronous programming.

The primary objective of this book is to provide software developers, particularly those with a foundation in Java, a deep and practical understanding of concurrency models and patterns in Java. Hand in hand with theories, the reader will explore a wealth of real-world examples and code to demonstrate the powerful capabilities as well as the complexities involved when crafting concurrent applications.

The substance of this book encompasses all foundational and advanced topics related to Java concurrency. Starting with the basics of threads and synchronization, it moves towards more complex topics such as the executor framework, futures, and reactive streams API. Special emphasis is given to practical aspects such as thread safety, performance considerations, and reactive programming. This is not just a theoretical reference but a practical guide that answers how as much as it does why.

Target readership includes intermediate to advanced Java developers seeking to improve or refine their skills in concurrent programming. Also, the book serves system architects and senior developers who design and build complex systems and need to understand how concurrency can affect and bolster system architecture and design.

It is expected that by the end of this book, the reader will be well-equipped to design, implement, test, and maintain efficient and effective concurrent applications in Java. Armed with this knowledge, developers will not only be able to increase the performance of existing applications but also leverage multithreading and asynchronous features in Java to their full potential.

Chapter 1

Introduction to Java Concurrency

Java concurrency is an essential facet of building modern applications, particularly important in the realms where performance and scalability are crucial. Concurrency allows multiple threads to run simultaneously, drastically improving the efficiency of applications by utilizing multiple cores of the processor effectively. This chapter explores the fundamental concepts such as threads, the Java Memory Model, and thread lifecycle, providing the foundational knowledge required to understand more complex concurrency topics.

1.1

Concurrency in Java

Concurrency is a pivotal concept in Java programming, facilitating simultaneous execution of multiple tasks within a single application. This feature is vital for crafting efficient and responsive applications that maximize CPU resource utilization, particularly advantageous in the current multi-core processor landscape.

Concurrency incorporates executing multiple operations in overlapping timeframes—though not necessarily simultaneously, which is the essence of parallelism. Instead, concurrent operations share system resources and time, often giving the illusion of parallel execution because of effective time management strategies like context switching by the Java Runtime Environment (JRE).

In Java, the manifestation of concurrency is predominantly through threads. These threads, or lightweight processes, each harbor a distinct execution path through the program, allowing for concurrent execution that appears simultaneous due to the rapid context switching conducted by the JRE.

Advantages of Concurrency:

Enhanced Responsiveness: Decoupling lengthy operations from the main thread aids in maintaining fluid user interfaces, thus elevating user interaction experiences.

Optimal Resource Use: Effective usage of system architecture, particularly exploiting multi-core processors for true parallel execution of threads.

Heightened Throughput: The ability to manage more tasks concurrently is a boon for server-side applications that handle numerous client requests simultaneously.

Concurrency Models in Java: Java endorses various concurrency models, each tailored to specific programming scenarios:

Thread-Based: The cornerstone of Java concurrency, where tasks are represented and managed as individual threads.

Event-Driven: Predicated on responding to events, this model is prevalent in UIs and network programming, managing tasks asynchronously.

Java provides extensive support for these models through the comprehensive java.util.concurrent package, the ExecutorService framework, and the basic java.lang.Thread class. These tools and API layers simplify thread management and address synchronization and concurrent data access.

Concurrency vs. Parallelism: Though often conflated, concurrency and parallelism articulate distinct scenarios:

Concurrency: Focuses on overlapping task execution timelines, offering the semblance of simultaneous operation.

Parallelism: Involves actual simultaneous execution, achievable on multi-threading hardware.

Challenges of Concurrency: Despite its advantages, concurrency introduces complexities:

Design Complexity: Crafting concurrent programs demands rigorous design to manage the shared resources effectively without conflict.

Thread Safety: Ensuring error-free operation when multiple threads interact with shared data is paramount.

Debugging Difficulty: The elusive nature of issues like deadlocks and race conditions in concurrent execution complicates debugging processes.

Through Java’s robust concurrency support mechanisms, developers are equipped to create applications that are both efficient and responsive, while managing the intrinsic complexities of concurrent programming. Mastery of concurrency fundamentals and effective implementation strategies are indispensable for any proficient Java developer.

1.2

Concurrency vs. Parallelism

Understanding the notions of concurrency and parallelism is imperative for any software developer to optimize application design for better performance and efficiency, particularly in Java. Though these paradigms are often mentioned together, they each play distinct roles in improving system throughput and response times. Here, we dive deep into each concept to better understand their usage and advantages in programming, especially within Java frameworks.

Concurrency and Parallelism are two terms frequently encountered in the realm of computing but they are not synonymous. Concurrency involves handling multiple tasks at once and is driven by the need to perform several operations asynchronously. Tasks in a concurrent setup might not run at the same exact instant, but they progress simultaneously. This approach is beneficial in situations like IO-bound tasks where operations might need to wait for external processes such as network responses or disk input/output before proceeding.

Parallelism refers to performing multiple operations simultaneously, leveraging the capability of multi-core architectures to process different tasks or parts of the same task on separate cores directly at the same time. This is particularly advantageous for CPU-intensive tasks where dividing a task into smaller sub-tasks that run on different cores can substantially reduce the completion time.

Java’s implementation of concurrency is centered around its robust threading model, where the Java Virtual Machine (JVM) plays a crucial role in managing threads. Below is an example to demonstrate simple thread creation in Java:

1

public

class

SimpleThreadExample

extends

Thread

{

2

public

void

run

()

{

3

System

.

out

.

println

(

"

Thread

running

"

)

;

4

}

5

6

public

static

void

main

(

String

[]

args

)

{

7

SimpleThreadExample

thread

=

new

SimpleThreadExample

()

;

8

thread

.

start

()

;

9

}

10

}

In the example above, a new thread is spawned, and it executes independently of the main program thread. The JVM handles scheduling of threads and allocates CPU resources to running threads.

For parallelism in Java, one can utilize the Fork/Join framework which allows dividing a task into smaller parts, processing them in parallel, and then combining the results. Here is a minimal example of using the Fork/Join framework:

1

import

java

.

util

.

concurrent

.

RecursiveTask

;

2

3

public

class

SumTask

extends

RecursiveTask

<

Long

>

{

4

private

final

long

[]

numbers

;

5

private

final

int

start