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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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:

>> Flexible Pub/Sub Messaging With Spring Boot and Dapr

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

In this tutorial, we’ll discuss the differences between Collections.synchronizedMap() and ConcurrentHashMap.

Additionally, we’ll look at the performance outputs of the read and write operations for each.

2. The Differences

Collections.synchronizedMap() and ConcurrentHashMap both provide thread-safe operations on collections of data.

The Collections utility class provides polymorphic algorithms that operate on collections and return wrapped collections. Its synchronizedMap() method provides thread-safe functionality.

As the name implies, synchronizedMap() returns a synchronized Map backed by the Map that we provide in the parameter. To provide thread-safety, synchronizedMap() allows all accesses to the backing Map via the returned Map.

ConcurrentHashMap was introduced in JDK 1.5 as an enhancement of HashMap that supports high concurrency for retrievals as well as updates. HashMap isn’t thread-safe, so it might lead to incorrect results during thread contention.

The ConcurrentHashMap class is thread-safe. Therefore, multiple threads can operate on a single object with no complications.

In ConcurrentHashMap, read operations are non-blocking, whereas write operations take a lock on a particular segment or bucket. The default bucket or concurrency level is 16, which means 16 threads can write at any instant after taking a lock on a segment or bucket.

2.1. ConcurrentModificationException

For objects like HashMap, performing concurrent operations is not allowed. Therefore, if we try to update a HashMap while iterating over it, we will receive a ConcurrentModificationException. This will also occur when using synchronizedMap():

@Test(expected = ConcurrentModificationException.class)
public void whenRemoveAndAddOnHashMap_thenConcurrentModificationError() {
    Map<Integer, String> map = new HashMap<>();
    map.put(1, "baeldung");
    map.put(2, "HashMap");
    Map<Integer, String> synchronizedMap = Collections.synchronizedMap(map);
    Iterator<Entry<Integer, String>> iterator = synchronizedMap.entrySet().iterator();
    while (iterator.hasNext()) {
        synchronizedMap.put(3, "Modification");
        iterator.next();
    }
}

However, this is not the case with ConcurrentHashMap:

Map<Integer, String> map = new ConcurrentHashMap<>();
map.put(1, "baeldung");
map.put(2, "HashMap");
 
Iterator<Entry<Integer, String>> iterator = map.entrySet().iterator();
while (iterator.hasNext()) {
    map.put(3, "Modification");
    iterator.next()
}
 
Assert.assertEquals(3, map.size());

2.2. null Support

Collections.synchronizedMap() and ConcurrentHashMap handle null keys and values differently.

ConcurrentHashMap doesn’t allow null in keys or values:

@Test(expected = NullPointerException.class)
public void allowNullKey_In_ConcurrentHasMap() {
    Map<String, Integer> map = new ConcurrentHashMap<>();
    map.put(null, 1);
}

However, when using Collections.synchronizedMap(), null support depends on the input Map. We can have one null as a key and any number of null values when Collections.synchronizedMap() is backed by HashMap or LinkedHashMap, whereas if we’re using TreeMap, we can have null values but not null keys.

Let’s assert that we can use a null key for Collections.synchronizedMap() backed by a HashMap:

Map<String, Integer> map = Collections
  .synchronizedMap(new HashMap<String, Integer>());
map.put(null, 1);
Assert.assertTrue(map.get(null).equals(1));

Similarly, we can validate null support in values for both Collections.synchronizedMap() and ConcurrentHashMap.

3. Performance Comparison

Let’s compare the performances of ConcurrentHashMap versus Collections.synchronizedMap(). In this case, we’re using the open-source framework Java Microbenchmark Harness (JMH) to compare the performances of the methods in nanoseconds.

We ran the comparison for random read and write operations on these maps. Let’s take a quick look at our JMH benchmark code:

@Benchmark
public void randomReadAndWriteSynchronizedMap() {
    Map<String, Integer> map = Collections.synchronizedMap(new HashMap<String, Integer>());
    performReadAndWriteTest(map);
}

@Benchmark
public void randomReadAndWriteConcurrentHashMap() {
    Map<String, Integer> map = new ConcurrentHashMap<>();
    performReadAndWriteTest(map);
}

private void performReadAndWriteTest(final Map<String, Integer> map) {
    for (int i = 0; i < TEST_NO_ITEMS; i++) {
        Integer randNumber = (int) Math.ceil(Math.random() * TEST_NO_ITEMS);
        map.get(String.valueOf(randNumber));
        map.put(String.valueOf(randNumber), randNumber);
    }
}

We ran our performance benchmarks using 5 iterations with 10 threads for 1,000 items. Let’s see the benchmark results:

Benchmark                                                     Mode  Cnt        Score        Error  Units
MapPerformanceComparison.randomReadAndWriteConcurrentHashMap  avgt  100  3061555.822 ±  84058.268  ns/op
MapPerformanceComparison.randomReadAndWriteSynchronizedMap    avgt  100  3234465.857 ±  60884.889  ns/op
MapPerformanceComparison.randomReadConcurrentHashMap          avgt  100  2728614.243 ± 148477.676  ns/op
MapPerformanceComparison.randomReadSynchronizedMap            avgt  100  3471147.160 ± 174361.431  ns/op
MapPerformanceComparison.randomWriteConcurrentHashMap         avgt  100  3081447.009 ±  69533.465  ns/op
MapPerformanceComparison.randomWriteSynchronizedMap           avgt  100  3385768.422 ± 141412.744  ns/op

The above results show that ConcurrentHashMap performs better than Collections.synchronizedMap().

4. When to Use

We should favor Collections.synchronizedMap() when data consistency is of utmost importance, and we should choose ConcurrentHashMap for performance-critical applications where there are far more write operations than there are read operations.

This is because the Collections.synchronizedMap() requires each thread to acquire a lock on the entire object for both read/write operations. By comparison, the ConcurrentHashMap allows threads to acquire locks on separate segments of the collection, and make modifications at the same time.

5. Conclusion

In this article, we’ve demonstrated the differences between ConcurrentHashMap and Collections.synchronizedMap(). We’ve also shown the performances of both of them using a simple JMH benchmark.

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:

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