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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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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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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.

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Course – LJB – NPI EA (cat = Core 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 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. Introduction

In this quick tutorial, we’ll examine various ways of calculating the sum of integers using the Stream API.

For the sake of simplicity, we’ll use integers in our examples; however, we can apply the same methods to longs and doubles as well.

Further reading:

Introduction to Java Streams

A quick and practical introduction to Java 8 Streams.

Guide to Stream.reduce()

Learn the key concepts of the Stream.reduce() operation in Java and how to use it to process sequential and parallel streams.

Guide to Java Collectors

The article discusses Java 8 Collectors, showing examples of built-in collectors, as well as showing how to build custom collector.

2. Using Stream.reduce()

Stream.reduce() is a terminal operation that performs a reduction on the elements of the stream.

It applies a binary operator (accumulator) to each element in the stream, where the first operand is the return value of the previous application, and the second one is the current stream element.

In the first method of using the reduce() method, the accumulator function is a lambda expression that adds two Integer values and returns an Integer value:

List<Integer> integers = Arrays.asList(1, 2, 3, 4, 5);
Integer sum = integers.stream()
  .reduce(0, (a, b) -> a + b);

In the same way, we can use an already existing Java method:

List<Integer> integers = Arrays.asList(1, 2, 3, 4, 5);
Integer sum = integers.stream()
  .reduce(0, Integer::sum);

Or we can define and use our custom method:

public class ArithmeticUtils {

    public static int add(int a, int b) {
        return a + b;
    }
}

Then we can pass this function as a parameter to the reduce() method:

List<Integer> integers = Arrays.asList(1, 2, 3, 4, 5);
Integer sum = integers.stream()
  .reduce(0, ArithmeticUtils::add);

3. Using Stream.collect()

The second method for calculating the sum of a list of integers is by using the collect() terminal operation:

List<Integer> integers = Arrays.asList(1, 2, 3, 4, 5);
Integer sum = integers.stream()
  .collect(Collectors.summingInt(Integer::intValue));

Similarly, the Collectors class provides summingLong() and summingDouble() methods to calculate the sums of longs and doubles, respectively.

4. Using IntStream.sum()

The Stream API provides us with the mapToInt() intermediate operation, which converts our stream to an IntStream object.

This method takes a mapper as a parameter, which it uses to do the conversion, then we can call the sum() method to calculate the sum of the stream’s elements.

Let’s see a quick example of how we can use it:

List<Integer> integers = Arrays.asList(1, 2, 3, 4, 5);
Integer sum = integers.stream()
  .mapToInt(Integer::intValue)
  .sum();

In the same fashion, we can use the mapToLong() and mapToDouble() methods to calculate the sums of longs and doubles, respectively.

5. Using Stream#sum With Map

To calculate the sum of values of a Map<Object, Integer> data structure, first we create a stream from the values of that Map. Next we apply one of the methods we used previously.

For instance, by using IntStream.sum():

Integer sum = map.values()
  .stream()
  .mapToInt(Integer::valueOf)
  .sum();

6. Using Stream#sum With Objects

Let’s imagine that we have a list of objects and that we want to calculate the sum of all the values of a given field of these objects.

For example:

public class Item {

    private int id;
    private Integer price;

    public Item(int id, Integer price) {
        this.id = id;
        this.price = price;
    }

    // Standard getters and setters
}

Next let’s imagine that we want to calculate the total price of all the items of the following list:

Item item1 = new Item(1, 10);
Item item2 = new Item(2, 15);
Item item3 = new Item(3, 25);
Item item4 = new Item(4, 40);
        
List<Item> items = Arrays.asList(item1, item2, item3, item4);

In this case, in order to calculate the sum using the methods shown in previous examples, we need to call the map() method to convert our stream into a stream of integers.

As a result, we can use Stream.reduce(), Stream.collect(), and IntStream.sum() to calculate the sum:

Integer sum = items.stream()
  .map(x -> x.getPrice())
  .reduce(0, ArithmeticUtils::add);
Integer sum = items.stream()
  .map(x -> x.getPrice())
  .reduce(0, Integer::sum);
Integer sum = items.stream()
  .map(item -> item.getPrice())
  .reduce(0, (a, b) -> a + b);
Integer sum = items.stream()
  .map(x -> x.getPrice())
  .collect(Collectors.summingInt(Integer::intValue));
items.stream()
  .mapToInt(x -> x.getPrice())
  .sum();

7. Using Stream#sum With String

Let’s suppose that we have a String object containing some integers.

To calculate the sum of these integers, first we need to convert that String into an Array. Next we need to filter out the non-integer elements, and finally, convert the remaining elements of that array into numbers.

Let’s see all these steps in action:

String string = "Item1 10 Item2 25 Item3 30 Item4 45";

Integer sum = Arrays.stream(string.split(" "))
    .filter((s) -> s.matches("\\d+"))
    .mapToInt(Integer::valueOf)
    .sum();

8. Conclusion

In this article, we discussed several methods of how to calculate the sum of a list of integers by using the Stream API. We also used these methods to calculate the sum of values of a given field of a list of objects, the sum of the values of a map, and the numbers within a given String object.

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 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)