Partner – Microsoft – NPI EA (cat = Baeldung)
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Azure Container Apps is a fully managed serverless container service that enables you to build and deploy modern, cloud-native Java applications and microservices at scale. It offers a simplified developer experience while providing the flexibility and portability of containers.

Of course, Azure Container Apps has really solid support for our ecosystem, from a number of build options, managed Java components, native metrics, dynamic logger, and quite a bit more.

To learn more about Java features on Azure Container Apps, visit the documentation page.

You can also ask questions and leave feedback on the Azure Container Apps GitHub page.

Partner – Microsoft – NPI EA (cat= Spring Boot)
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Azure Container Apps is a fully managed serverless container service that enables you to build and deploy modern, cloud-native Java applications and microservices at scale. It offers a simplified developer experience while providing the flexibility and portability of containers.

Of course, Azure Container Apps has really solid support for our ecosystem, from a number of build options, managed Java components, native metrics, dynamic logger, and quite a bit more.

To learn more about Java features on Azure Container Apps, you can get started over on the documentation page.

And, you can also ask questions and leave feedback on the Azure Container Apps GitHub page.

Partner – Orkes – NPI EA (cat=Spring)
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Modern software architecture is often broken. Slow delivery leads to missed opportunities, innovation is stalled due to architectural complexities, and engineering resources are exceedingly expensive.

Orkes is the leading workflow orchestration platform built to enable teams to transform the way they develop, connect, and deploy applications, microservices, AI agents, and more.

With Orkes Conductor managed through Orkes Cloud, developers can focus on building mission critical applications without worrying about infrastructure maintenance to meet goals and, simply put, taking new products live faster and reducing total cost of ownership.

Try a 14-Day Free Trial of Orkes Conductor today.

Partner – Orkes – NPI EA (tag=Microservices)
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Modern software architecture is often broken. Slow delivery leads to missed opportunities, innovation is stalled due to architectural complexities, and engineering resources are exceedingly expensive.

Orkes is the leading workflow orchestration platform built to enable teams to transform the way they develop, connect, and deploy applications, microservices, AI agents, and more.

With Orkes Conductor managed through Orkes Cloud, developers can focus on building mission critical applications without worrying about infrastructure maintenance to meet goals and, simply put, taking new products live faster and reducing total cost of ownership.

Try a 14-Day Free Trial of Orkes Conductor today.

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.

Get started with mocking and improve your application tests using our Mockito guide:

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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:

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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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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:

>> Learn Spring Security

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.

Get started with Spring Data JPA through the guided reference course:

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Partner – MongoDB – NPI EA (tag=MongoDB)
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Traditional keyword-based search methods rely on exact word matches, often leading to irrelevant results depending on the user's phrasing.

By comparison, using a vector store allows us to represent the data as vector embeddings, based on meaningful relationships. We can then compare the meaning of the user’s query to the stored content, and retrieve more relevant, context-aware results.

Explore how to build an intelligent chatbot using MongoDB Atlas, Langchain4j and Spring Boot:

>> Building an AI Chatbot in Java With Langchain4j and MongoDB Atlas

Partner – LambdaTest – NPI EA (cat=Testing)
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Accessibility testing is a crucial aspect to ensure that your application is usable for everyone and meets accessibility standards that are required in many countries.

By automating these tests, teams can quickly detect issues related to screen reader compatibility, keyboard navigation, color contrast, and other aspects that could pose a barrier to using the software effectively for people with disabilities.

Learn how to automate accessibility testing with Selenium and the LambdaTest cloud-based testing platform that lets developers and testers perform accessibility automation on over 3000+ real environments:

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eBook – Java Streams – NPI (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

1. Overview

Java Stream API provides various methods to operate and work with a sequence of elements. However, it’s not easy if we want to process only part of the stream, e.g., every N-th element. This might be useful if we’re processing a stream of raw data representing a CSV file or database table and would like to process only specific columns.

We’ll address two kinds of streams: finite and infinite. The first case can be resolved by converting a Stream into a List, which allows indexing. On the other side, infinite streams would require a different approach. In this tutorial, we’ll learn how to address this challenge using various techniques.

2. Tests Setup

We’ll use parametrized tests to check the correctness of our solutions. There’ll be a couple of cases with respective N-th elements and expected results:

Arguments.of(
  Stream.of("Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday"),
  List.of("Wednesday", "Saturday"), 3),
Arguments.of(
  Stream.of("Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday"),
  List.of("Friday"), 5),
Arguments.of(
  Stream.of("Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday"),
  List.of("Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday"), 1)

Now, we can dive into different methods of processing the N-th element from a stream.

3. Using filter()

In the first approach, we can create a separate stream containing only the indexes of the elements we would like to process. We can use a filter(Predicate) to create such an array:

void givenListSkipNthElementInListWithFilterTestShouldFilterNthElement(Stream<String> input, List<String> expected, int n) {
    final List<String> sourceList = input.collect(Collectors.toList());
    final List<String> actual = IntStream.range(0, sourceList.size())
      .filter(s -> (s + 1) % n == 0)
      .mapToObj(sourceList::get)
      .collect(Collectors.toList());
    assertEquals(expected, actual);
}

This approach will work if we want to operate on a data structure that allows indexed accesses, such as a List. The needed elements can be collected to a new List or processed with forEach(Consumer).

4. Using iterate()

This approach is similar to the previous one and requires a data structure with indexed accesses. However, instead of filtering out indexes we don’t need, we’ll generate only the indexes we would like to use in the beginning:

void givenListSkipNthElementInListWithIterateTestShouldFilterNthElement(Stream<String> input, List<String> expected, int n) {
    final List<String> sourceList = input.collect(Collectors.toList());
    int limit = sourceList.size() / n;
    final List<String> actual = IntStream.iterate(n - 1, i -> (i + n))
      .limit(limit)
      .mapToObj(sourceList::get)
      .collect(Collectors.toList());
    assertEquals(expected, actual);
}

In this case, we’re using IntStream.iterate(int, IntUnaryOperator), which allows us to create an integer sequence with step.

5. Using subList()

This approach uses Stream.iterate and is similar to the previous one, but it creates a stream of Lists, each starting at the nk-th index:

void givenListSkipNthElementInListWithSublistTestShouldFilterNthElement(Stream<String> input, List<String> expected, int n) {
    final List<String> sourceList = input.collect(Collectors.toList());
    int limit = sourceList.size() / n;
    final List<String> actual = Stream.iterate(sourceList, s -> s.subList(n, s.size()))
      .limit(limit)
      .map(s -> s.get(n - 1))
      .collect(Collectors.toList());
    assertEquals(expected, actual);
}

We should take the first element of each of these Lists to get the needed result.

6. Using a Custom Collector

As a more advanced and transparent solution, we can implement a custom Collector that collects only the needed elements:

class SkippingCollector {
    private static final BinaryOperator<SkippingCollector> IGNORE_COMBINE = (a, b) -> a;
    private final int skip;
    private final List<String> list = new ArrayList<>();
    private int currentIndex = 0;
    private SkippingCollector(int skip) {
        this.skip = skip;
    }

    private void accept(String item) {
        int index = ++currentIndex % skip;
        if (index == 0) {
            list.add(item);
        }
    }
    private List<String> getResult() {
        return list;
    }

    public static Collector<String, SkippingCollector, List<String>> collector(int skip) {
        return Collector.of(() -> new SkippingCollector(skip),
          SkippingCollector::accept, 
          IGNORE_COMBINE, 
          SkippingCollector::getResult);
    }
}

This approach is more complex and requires some coding. At the same time, this solution doesn’t allow parallelization and technically may fail even on sequential streams because combining is an implementation detail that might change in future releases:

public static List<String> skipNthElementInStreamWithCollector(Stream<String> sourceStream, int n) {
    return sourceStream.collect(SkippingCollector.collector(n));
}

However, it’s possible to use Spliterators to make this approach work for parallel streams, but it should have a good reason for this.

7. Simple Loop

All the previous solutions would work, but overall, they’re unnecessarily complex and often misguiding. The best way to resolve the problem is often with the simplest implementation possible. This is how we can use a for loop to achieve the same:

void givenListSkipNthElementInListWithForTestShouldFilterNthElement(Stream<String> input, List<String> expected, int n) {
    final List<String> sourceList = input.collect(Collectors.toList());
    List<String> result = new ArrayList<>();
    for (int i = n - 1; i < sourceList.size(); i += n) {
        result.add(sourceList.get(i));
    }
    final List<String> actual = result;
    assertEquals(expected, actual);
}

However, sometimes, we need to work with a Stream directly, and this won’t allow us to access elements directly by their indexes. In this case, we can use an Iterator with a while loop:

void givenListSkipNthElementInStreamWithIteratorTestShouldFilterNthElement(Stream<String> input, List<String> expected, int n) {
    List<String> result = new ArrayList<>();
    final Iterator<String> iterator = input.iterator();
    int count = 0;
    while (iterator.hasNext()) {
        if (count % n == n - 1) {
            result.add(iterator.next());
        } else {
            iterator.next();
        }
        ++count;
    }
    final List<String> actual = result;
    assertEquals(expected, actual);
}

These solutions are cleaner and more straightforward to understand while resolving the same problem.

8. Conclusion

Java Stream API is a powerful tool that helps to make the code more declarative and readable. Additionally, streams can achieve a better performance by utilizing parametrization. However, the desire to use streams everywhere might not be the best way to approach this API.

Although mental gymnastics of applying stream operation in the cases where they’re not ideally suitable might be fun, it might also result in “clever code.” Often, the simplest structure, like loops, can achieve the same result with less and more understandable code.

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:

>> Explore a clean Baeldung

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

Partner – Microsoft – NPI EA (cat = Baeldung)
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Azure Container Apps is a fully managed serverless container service that enables you to build and deploy modern, cloud-native Java applications and microservices at scale. It offers a simplified developer experience while providing the flexibility and portability of containers.

Of course, Azure Container Apps has really solid support for our ecosystem, from a number of build options, managed Java components, native metrics, dynamic logger, and quite a bit more.

To learn more about Java features on Azure Container Apps, visit the documentation page.

You can also ask questions and leave feedback on the Azure Container Apps GitHub page.

Partner – Microsoft – NPI EA (cat = Spring Boot)
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Azure Container Apps is a fully managed serverless container service that enables you to build and deploy modern, cloud-native Java applications and microservices at scale. It offers a simplified developer experience while providing the flexibility and portability of containers.

Of course, Azure Container Apps has really solid support for our ecosystem, from a number of build options, managed Java components, native metrics, dynamic logger, and quite a bit more.

To learn more about Java features on Azure Container Apps, visit the documentation page.

You can also ask questions and leave feedback on the Azure Container Apps GitHub page.

Partner – Orkes – NPI EA (cat = Spring)
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Modern software architecture is often broken. Slow delivery leads to missed opportunities, innovation is stalled due to architectural complexities, and engineering resources are exceedingly expensive.

Orkes is the leading workflow orchestration platform built to enable teams to transform the way they develop, connect, and deploy applications, microservices, AI agents, and more.

With Orkes Conductor managed through Orkes Cloud, developers can focus on building mission critical applications without worrying about infrastructure maintenance to meet goals and, simply put, taking new products live faster and reducing total cost of ownership.

Try a 14-Day Free Trial of Orkes Conductor today.

Partner – Orkes – NPI EA (tag = Microservices)
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Modern software architecture is often broken. Slow delivery leads to missed opportunities, innovation is stalled due to architectural complexities, and engineering resources are exceedingly expensive.

Orkes is the leading workflow orchestration platform built to enable teams to transform the way they develop, connect, and deploy applications, microservices, AI agents, and more.

With Orkes Conductor managed through Orkes Cloud, developers can focus on building mission critical applications without worrying about infrastructure maintenance to meet goals and, simply put, taking new products live faster and reducing total cost of ownership.

Try a 14-Day Free Trial of Orkes Conductor today.

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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Partner – MongoDB – NPI EA (tag=MongoDB)
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Traditional keyword-based search methods rely on exact word matches, often leading to irrelevant results depending on the user's phrasing.

By comparison, using a vector store allows us to represent the data as vector embeddings, based on meaningful relationships. We can then compare the meaning of the user’s query to the stored content, and retrieve more relevant, context-aware results.

Explore how to build an intelligent chatbot using MongoDB Atlas, Langchain4j and Spring Boot:

>> Building an AI Chatbot in Java With Langchain4j and MongoDB Atlas

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