eBook – Guide Spring Cloud – NPI EA (cat=Spring Cloud)
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Let's get started with a Microservice Architecture with 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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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:

>> 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 – 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 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

In this article, we will be looking at a java.util.Stream API and we’ll see how we can use that construct to operate on an infinite stream of data/elements.

The possibility of working on the infinite sequence of elements is predicated on the fact that streams are built to be lazy.

This laziness is achieved by a separation between two types of the operations that could be executed on streams: intermediate and terminal operations.

2. Intermediate and Terminal Operations

All Stream operations are divided into intermediate and terminal operations and are combined to form stream pipelines.

A stream pipeline consists of a source (such as a Collection, an array, a generator function, an I/O channel, or infinite sequence generator); followed by zero or more intermediate operations and a terminal operation.

2.1. Intermediate Operations

Intermediate operations are not executed until some terminal operation is invoked.

They’re composed forming a pipeline of a Stream execution. The intermediate operation can be added to a Stream pipeline by methods:

  • filter()
  • map()
  • flatMap()
  • distinct()
  • sorted()
  • peek()
  • limit()
  • skip()

All Intermediate operations are lazy, so they’re not executed until a result of a processing is actually needed.

Basically, intermediate operations return a new stream. Executing an intermediate operation does not actually perform any operation, but instead creates a new stream that, when traversed, contains the elements of the initial stream that match the given predicate.

As such, traversal of the Stream doesn’t begin until the terminal operation of the pipeline is executed.

That is very important property, specifically important for infinite streams – because it allows us to create streams that will be actually invoked only when a Terminal operation is called.

2.2. Terminal Operations

Terminal operations may traverse the stream to produce a result or a side effect.

After the terminal operation is performed, the stream pipeline is considered consumed, and can no longer be used. In almost all cases, terminal operations are eager, completing their traversal of the data source and processing of the pipeline before returning.

The eagerness of a terminal operation is important concerning infinite streams because at the moment of processing we need to think carefully if our Stream is properly bounded by, for example, a limit() transformation. Terminal operations are:

  • forEach()
  • forEachOrdered()
  • toArray()
  • reduce()
  • collect()
  • min()
  • max()
  • count()
  • anyMatch()
  • allMatch()
  • noneMatch()
  • findFirst()
  • findAny()

Each of these operations will trigger execution of all intermediate operations.

3. Infinite Streams

Now that we understand these two concepts – Intermediate and Terminal operations – we’re able to write an infinite stream that leverage laziness of Streams.

Let’s say that we want to create an infinite stream of elements from zero that will be incremented by two. Then we need to limit that sequence before calling terminal operation.

It is crucial to use a limit() method before executing a collect() method that is a terminal operation, otherwise our program will run indefinitely:

// given
Stream<Integer> infiniteStream = Stream.iterate(0, i -> i + 2);

// when
List<Integer> collect = infiniteStream
  .limit(10)
  .collect(Collectors.toList());

// then
assertEquals(collect, Arrays.asList(0, 2, 4, 6, 8, 10, 12, 14, 16, 18));

We created an infinite stream using an iterate() method. Then we called a limit() transformation and a collect() terminal operation. Then in our resulting List, we will have first 10 elements of an infinite sequence due to a laziness of a Stream.

4. Infinite Stream of a Custom Type of Elements

Let’s say that we want to create an infinite stream of random UUIDs.

The first step to achieving this using Stream API is to create a Supplier of those random values:

Supplier<UUID> randomUUIDSupplier = UUID::randomUUID;

When we define a supplier we can create an infinite stream using a generate() method:

Stream<UUID> infiniteStreamOfRandomUUID = Stream.generate(randomUUIDSupplier);

Then we could take a couple of elements from that stream. We need to remember to use a limit() method if we want our program to finish in a finite time:

List<UUID> randomInts = infiniteStreamOfRandomUUID
  .skip(10)
  .limit(10)
  .collect(Collectors.toList());

We use a skip() transformation to discard first 10 results and take the next 10 elements. We can create an infinite stream of any custom type elements by passing a function of a Supplier interface to a generate() method on a Stream.

6. Do-While – the Stream Way

Let’s say that we have a simple do..while loop in our code:

int i = 0;
while (i < 10) {
    System.out.println(i);
    i++;
}

We are printing i counter ten times. We can expect that such construct can be easily written using Stream API and ideally, we would have a doWhile() method on a stream.

Unfortunately, there is no such method on a stream and when we want to achieve functionality similar to standard do-while loop we need to use a limit() method:

Stream<Integer> integers = Stream
  .iterate(0, i -> i + 1);
integers
  .limit(10)
  .forEach(System.out::println);

We achieved same functionality like an imperative while loop with less code, but call to the limit() function is not as descriptive as it would be if we had a doWhile() method on a Stream object.

5. Conclusion

This article explains how we can use the Stream API to create infinite streams. These, when used together with transformations such as limit() – can make some scenarios quite a bit easier to understand and implement.

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.

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?

Explore the eBook

Course – LS – NPI EA (cat=REST)

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

>> CHECK OUT THE COURSE

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 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)