eBook – Guide Spring Cloud – NPI EA (cat=Spring Cloud)
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eBook – Mockito – NPI EA (tag = Mockito)
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Mocking is an essential part of unit testing, and the Mockito library makes it easy to write clean and intuitive unit tests for your Java code.

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eBook – Java Concurrency – NPI EA (cat=Java Concurrency)
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Handling concurrency in an application can be a tricky process with many potential pitfalls. A solid grasp of the fundamentals will go a long way to help minimize these issues.

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eBook – Reactive – NPI EA (cat=Reactive)
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Spring 5 added support for reactive programming with the Spring WebFlux module, which has been improved upon ever since. Get started with the Reactor project basics and reactive programming in Spring Boot:

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eBook – Java Streams – NPI EA (cat=Java Streams)
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Since its introduction in Java 8, the Stream API has become a staple of Java development. The basic operations like iterating, filtering, mapping sequences of elements are deceptively simple to use.

But these can also be overused and fall into some common pitfalls.

To get a better understanding on how Streams work and how to combine them with other language features, check out our guide to Java Streams:

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eBook – Jackson – NPI EA (cat=Jackson)
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Do JSON right with Jackson

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eBook – HTTP Client – NPI EA (cat=Http Client-Side)
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Get the most out of the Apache HTTP Client

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eBook – Maven – NPI EA (cat = Maven)
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Get Started with Apache Maven:

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eBook – Persistence – NPI EA (cat=Persistence)
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eBook – RwS – NPI EA (cat=Spring MVC)
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Building a REST API with Spring?

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Course – LS – NPI EA (cat=Jackson)
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Get started with Spring and Spring Boot, through the Learn Spring course:

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Course – RWSB – NPI EA (cat=REST)
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Explore Spring Boot 3 and Spring 6 in-depth through building a full REST API with the framework:

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Course – LSS – NPI EA (cat=Spring Security)
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Yes, Spring Security can be complex, from the more advanced functionality within the Core to the deep OAuth support in the framework.

I built the security material as two full courses - Core and OAuth, to get practical with these more complex scenarios. We explore when and how to use each feature and code through it on the backing project.

You can explore the course here:

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Course – LSD – NPI EA (tag=Spring Data JPA)
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Spring Data JPA is a great way to handle the complexity of JPA with the powerful simplicity of Spring Boot.

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Partner – Moderne – NPI EA (cat=Spring Boot)
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Refactor Java code safely — and automatically — with OpenRewrite.

Refactoring big codebases by hand is slow, risky, and easy to put off. That’s where OpenRewrite comes in. The open-source framework for large-scale, automated code transformations helps teams modernize safely and consistently.

Each month, the creators and maintainers of OpenRewrite at Moderne run live, hands-on training sessions — one for newcomers and one for experienced users. You’ll see how recipes work, how to apply them across projects, and how to modernize code with confidence.

Join the next session, bring your questions, and learn how to automate the kind of work that usually eats your sprint time.

Course – LJB – NPI EA (cat = Core Java)
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Code your way through and build up a solid, practical foundation of Java:

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Partner – LambdaTest – NPI EA (cat= Testing)
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Distributed systems often come with complex challenges such as service-to-service communication, state management, asynchronous messaging, security, and more.

Dapr (Distributed Application Runtime) provides a set of APIs and building blocks to address these challenges, abstracting away infrastructure so we can focus on business logic.

In this tutorial, we'll focus on Dapr's pub/sub API for message brokering. Using its Spring Boot integration, we'll simplify the creation of a loosely coupled, portable, and easily testable pub/sub messaging system:

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eBook – Java Concurrency – NPI (cat=Java Concurrency)
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Handling concurrency in an application can be a tricky process with many potential pitfalls. A solid grasp of the fundamentals will go a long way to help minimize these issues.

Get started with understanding multi-threaded applications with our Java Concurrency guide:

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1. Overview

The compiler, runtime, or processors may apply all sorts of optimizations. Although these optimizations are usually beneficial, typically without necessary synchronizations, they can cause subtle issues in the form of unexpected results.

Caching and reordering are optimizations that may surprise us in concurrent contexts when we don’t synchronize code correctly. Java and the JVM provide many ways to control memory order, and a volatile field is one of them.

This tutorial focuses on Java’s foundational but often misunderstood concept, the volatile field. First, we’ll start with some background about how the underlying computer architecture works, and then we’ll get familiar with memory order in Java. Further, we’ll understand the challenges of concurrency in multiprocessor shared architecture and how volatile fields help fix them.

2. Shared Multiprocessor Architecture

Processors are responsible for executing program instructions. Therefore, they must retrieve the program instructions and required data from RAM.

As CPUs can carry many instructions per second, fetching from RAM isn’t ideal for them. To improve this situation, processors use tricks like Out of Order Execution, Branch Prediction, Speculative Execution, and Caching.

This is where the following memory hierarchy comes into play:

cpu

As different cores execute more instructions and manipulate more data, they fill their caches with more relevant data and instructions. This will improve the overall performance at the expense of introducing cache coherence challenges.

We should think twice about what happens when one thread updates a cached value.

3. Cache Coherence Challenges

To expand more on cache coherence, we’ll borrow an example from the book Java Concurrency in Practice:

public class TaskRunner {

    private static int number;
    private static boolean ready;

    private static class Reader extends Thread {

        @Override
        public void run() {
            while (!ready) {
                Thread.yield();
            }

            System.out.println(number);
        }
    }

    public static void main(String[] args) {
        new Reader().start();
        number = 42;
        ready = true;
    }
}

The TaskRunner class maintains two simple variables. Its main method creates another thread that spins on the ready variable as long as it’s false. When the variable becomes true, the thread prints the number variable.

Many may expect this program to print 42 after a short delay; however, the delay may be much longer. It may even hang forever or print zero.

The cause of these anomalies is the lack of proper memory visibility and reordering. Let’s evaluate them in more detail.

3.1. Memory Visibility

This simple example has two application threads: the main and the reader threads. Let’s imagine a scenario in which the OS schedules those threads on two different CPU cores, where the:

  • main thread has a copy of the ready and number variables in its core cache
  • ready thread ends up with its copies, too
  • main thread updates the cached values

Most modern processors write requests that won’t be applied right after they’re issued. Processors tend to queue those writes in a special write buffer. After a while, they’ll apply those writes to the main memory all at once.

With all that being said, when the main thread updates the number and ready variables, there’s no guarantee about what the reader thread may see. In other words, the reader thread may immediately see the updated value, with some delay, or never at all.

This memory visibility may cause liveness issues in programs relying on visibility.

3.2. Reordering

To make matters even worse, the reader thread may see those writes in an order other than the actual program order. For instance, since we first update the number variable:

public static void main(String[] args) { 
    new Reader().start();
    number = 42; 
    ready = true; 
}

We may expect the reader thread to print 42. But it’s actually possible to see zero as the printed value.

Reordering is an optimization technique for performance improvements. Interestingly, different components may apply this optimization:

  • The processor may flush its write buffer in an order other than the program order
  • The processor may apply an out-of-order execution technique
  • The JIT compiler may optimize via reordering

4. volatile Memory Order

We can use volatile to tackle the issues with Cache Coherence.

To ensure that updates to variables propagate predictably to other threads, we should apply the volatile modifier to those variables.

This way, we can communicate with runtime and processor to avoid reordering any instruction involving the volatile variable. Also, processors understand that they should immediately flush any updates to these variables.

public class TaskRunner {

    private volatile static int number;
    private volatile static boolean ready;

    // same as before
}

This way, we communicate with runtime and processor to avoid reordering any instruction involving the volatile variable. Also, processors understand that they should immediately flush any updates to these variables.

5. volatile and Thread Synchronization

For multithreaded applications, we need to ensure a couple of rules for consistent behaviour:

  • Mutual Exclusion – only one thread executes a critical section at a time
  • Visibility – changes made by one thread to the shared data are visible to other threads to maintain data consistency

The synchronized methods and blocks provide both of the above properties at the cost of application performance.

The volatile field is quite a useful mechanism because it can help ensure the visibility aspect of the data change without providing mutual exclusion. Thus, it’s useful where we’re ok with multiple threads executing a block of code in parallel, but we need to ensure the visibility property.

6. The volatile Guarantee

A Java compiler is allowed to reorder program text instructions if, in a given thread, it does not affect the execution of that thread in isolation. A shared variable that includes the volatile modifier guarantees that, for each thread, the runtime and processor carry out the instructions related to the shared variable in the same order as they appear in the program text without applying any optimizations that may reorder the instructions. A shared variable that includes the volatile modifier guarantees that all threads see a consistent value for the shared variable. Any update to a volatile field updates the shared value of the field immediately. In other words, a different thread cannot get an inconsistent value of the shared variable after its value is updated.

It’s important to understand that volatile guarantees a consistent value of a shared variable; however, the absence of the volatile modifier doesn’t mean or guarantee that multiple threads always get an inconsistent value of the shared variable. In the absence of the volatile modifier, other threads may occasionally get an inconsistent value of the shared variable. Therefore, let’s not expect that by removing the volatile modifier in the example application TaskRunner, the application starts to print inconsistent values for a shared variable; however, it could happen.

7. Happens-Before Ordering

The memory visibility effects of volatile variables extend beyond the volatile variables themselves.

To make matters more concrete, suppose thread A writes to a volatile variable, and then thread B reads the same volatile variable. In such cases, the values that were visible to A before writing the volatile variable will be visible to B after reading the volatile variable:

happens before

Technically, any write to a volatile field happens before every subsequent read of the same field. This is the volatile variable rule of the Java Memory Model (JMM).

8. Piggybacking

Because of the strength of the happens-before memory ordering, sometimes we can piggyback on the visibility properties of another volatile variable. For instance, in our particular example, we just need to mark the ready variable as volatile:

public class TaskRunner {

    private static int number; // not volatile
    private volatile static boolean ready;

    // same as before
}

Anything prior to writing true to the ready variable is visible to anything after reading the ready variable. Therefore, the number variable piggybacks on the memory visibility enforced by the ready variable. Simply put, even though it’s not a volatile variable, it’s exhibiting a volatile behaviour.

Using these semantics, we can define only a few variables in our class as volatile and optimize the visibility guarantee.

9. Conclusion

In this article, we explored the volatile field keyword, its capabilities, and the improvements made to it, starting with Java 5.

The code backing this article is available on GitHub. Once you're logged in as a Baeldung Pro Member, start learning and coding on the project.
Baeldung Pro – NPI EA (cat = Baeldung)
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Baeldung Pro comes with both absolutely No-Ads as well as finally with Dark Mode, for a clean learning experience:

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Once the early-adopter seats are all used, the price will go up and stay at $33/year.

eBook – HTTP Client – NPI EA (cat=HTTP Client-Side)
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The Apache HTTP Client is a very robust library, suitable for both simple and advanced use cases when testing HTTP endpoints. Check out our guide covering basic request and response handling, as well as security, cookies, timeouts, and more:

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eBook – Java Concurrency – NPI EA (cat=Java Concurrency)
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Handling concurrency in an application can be a tricky process with many potential pitfalls. A solid grasp of the fundamentals will go a long way to help minimize these issues.

Get started with understanding multi-threaded applications with our Java Concurrency guide:

>> Download the eBook

eBook – Java Streams – NPI EA (cat=Java Streams)
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Since its introduction in Java 8, the Stream API has become a staple of Java development. The basic operations like iterating, filtering, mapping sequences of elements are deceptively simple to use.

But these can also be overused and fall into some common pitfalls.

To get a better understanding on how Streams work and how to combine them with other language features, check out our guide to Java Streams:

>> Join Pro and download the eBook

eBook – Persistence – NPI EA (cat=Persistence)
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Working on getting your persistence layer right with Spring?

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Course – LS – NPI EA (cat=REST)

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Get started with Spring Boot and with core Spring, through the Learn Spring course:

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Partner – Moderne – NPI EA (tag=Refactoring)
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Modern Java teams move fast — but codebases don’t always keep up. Frameworks change, dependencies drift, and tech debt builds until it starts to drag on delivery. OpenRewrite was built to fix that: an open-source refactoring engine that automates repetitive code changes while keeping developer intent intact.

The monthly training series, led by the creators and maintainers of OpenRewrite at Moderne, walks through real-world migrations and modernization patterns. Whether you’re new to recipes or ready to write your own, you’ll learn practical ways to refactor safely and at scale.

If you’ve ever wished refactoring felt as natural — and as fast — as writing code, this is a good place to start.

eBook – Java Concurrency – NPI (cat=Java Concurrency)
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Handling concurrency in an application can be a tricky process with many potential pitfalls. A solid grasp of the fundamentals will go a long way to help minimize these issues.

Get started with understanding multi-threaded applications with our Java Concurrency guide:

>> Download the eBook

eBook Jackson – NPI EA – 3 (cat = Jackson)