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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Working on getting your persistence layer right with Spring?

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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:

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

1. Overview

In this article, we’ll look at different ways to search an array for a specified value.

We’ll also compare how these perform using JMH (the Java Microbenchmark Harness) to determine which method works best.

2. Setup

For our examples, we’ll use an array that contains randomly generated Strings for each test:

String[] seedArray(int length) {
    String[] strings = new String[length];
    Random value = new Random();
    for (int i = 0; i < length; i++) {
        strings[i] = String.valueOf(value.nextInt());
    }
    return strings;
}

To reuse the array in each benchmark, we’ll declare an inner class to hold the array and the count so we can declare its scope for JMH:

@State(Scope.Benchmark)
public static class SearchData {
    static int count = 1000;
    static String[] strings = seedArray(1000);
}

Three commonly used methods for searching an array are as a List, a Set, or with a loop that examines each member until it finds a match.

Let’s start with three methods that implement each algorithm:

boolean searchList(String[] strings, String searchString) {
    return Arrays.asList(SearchData.strings)
      .contains(searchString);
}

boolean searchSet(String[] strings, String searchString) {
    Set<String> stringSet = new HashSet<>(Arrays.asList(SearchData.strings));
    
    return stringSet.contains(searchString);
}

boolean searchLoop(String[] strings, String searchString) {
    for (String string : SearchData.strings) {
        if (string.equals(searchString))
        return true;
    }
    
    return false;
}

We’ll use these class annotations to tell JMH to output average time in microseconds and run for five warmup iterations to ensure that our tests are reliable:

@BenchmarkMode(Mode.AverageTime)
@Warmup(iterations = 5)
@OutputTimeUnit(TimeUnit.MICROSECONDS)

And run each test in a loop:

@Benchmark
public void searchArrayLoop() {
    for (int i = 0; i < SearchData.count; i++) {
        searchLoop(SearchData.strings, "T");
    }
}

@Benchmark
public void searchArrayAllocNewList() {
    for (int i = 0; i < SearchData.count; i++) {
        searchList(SearchData.strings, "T");
    }
}

@Benchmark
public void searchArrayAllocNewSet() {
    for (int i = 0; i < SearchData.count; i++) {
        searchSet(SearchData.strings, "S");
    }
}

When we run with 1000 searches for each method, our results look something like this:

SearchArrayTest.searchArrayAllocNewList  avgt   20    937.851 ±  14.226  us/op
SearchArrayTest.searchArrayAllocNewSet   avgt   20  14309.122 ± 193.844  us/op
SearchArrayTest.searchArrayLoop          avgt   20    758.060 ±   9.433  us/op

The loop search is more efficient than others. But this is at least partly because of how we’re using collections.

We’re creating a new List instance with each call to searchList() and a new List and a new HashSet with each call to searchSet(). Creating these objects creates an additional cost that looping through the array doesn’t.

4. More Efficient Search

What happens when we create single instances of List and Set and then reuse them for each search?

Let’s give it a try:

public void searchArrayReuseList() {
    List asList = Arrays.asList(SearchData.strings);
    for (int i = 0; i < SearchData.count; i++) {
        asList.contains("T");
    }
}

public void searchArrayReuseSet() {
    Set asSet = new HashSet<>(Arrays.asList(SearchData.strings));
    for (int i = 0; i < SearchData.count; i++) {
        asSet.contains("T");
    }
}

We’ll run these methods with the same JMH annotations as above, and include the results for the simple loop for comparison.

We see very different results:

SearchArrayTest.searchArrayLoop          avgt   20    758.060 ±   9.433  us/op
SearchArrayTest.searchArrayReuseList     avgt   20    837.265 ±  11.283  us/op
SearchArrayTest.searchArrayReuseSet      avgt   20     14.030 ±   0.197  us/op

While searching the List is marginally faster than before, Set drops to less than 1 percent of the time required for the loop!

Now that we’ve removed the time required for creating new Collections from each search, these results make sense.

Searching a hash table, the structure underlying a HashSet, has a time complexity of 0(1), while an array, which underlies the ArrayList is 0(n).

Another method for searching an array is a binary search. While very efficient, a binary search requires that the array is sorted in advance.

Let’s sort the array and try the binary search:

@Benchmark
public void searchArrayBinarySearch() {
    Arrays.sort(SearchData.strings);
    for (int i = 0; i < SearchData.count; i++) {
        Arrays.binarySearch(SearchData.strings, "T");
    }
}
SearchArrayTest.searchArrayBinarySearch  avgt   20     26.527 ±   0.376  us/op

Binary search is very fast, although less efficient than the HashSet: the worst case performance for a binary search is 0(log n), which places its performance between that of an array search and a hash table.

6. Conclusion

We’ve seen several methods of searching through an array.

Based on our results, a HashSet works best for searching through a list of values. However, we need to create them in advance and store them in the Set.

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 Jackson – NPI EA – 3 (cat = Jackson)