Archive for category collectors

Writing your own custom Java stream collector

One of the common operations of the Collectors API introduced in Java 8 is the possibility to collect results into a result container like List, Set or Map. The following example uses the collect() method to generate a HashSet containing unique numbers:

Now suppose a given string and the need to compute some summaries on it, like the number of uppercase, lowercase, invalid chars and how many digits are present on that string.

Applying a reduce operation on each needed summary operation would result in more than one pass through the data, like this (here I am using the var keyword introduced in Java 10):

In the above code excerpt we are iterating three times through the string to compute the summaries. If we want to iterate just one time on the give string and get the desired results, we could fallback to the traditional imperative approach:

Despite the solution above, there is another one: writing your own custom stream collector. This custom collector can compute the number of uppercase, lowercase, invalid chars and how many digits are present on the given string, in a single pass through the data. It is possible to make it run in parallel with the Streams API as well.

The custom stream collector shown here uses the chars() method of the String class which returns an IntStream. The IntStream class contains a collect() method that computes a mutable reduction on the elements and returns its result in a container class.

The next example shows the container class code. It receives and accumulates each char of the String in the accept() method, thus categorizing it as a digit, uppercase char, lowercase char or as an invalid char.

The complete implementation of the collect() method which produces the result of the reduction in the CharSummaryStatistics class is shown below. As a new char arrives, it is categorized in the CharSummaryStatistics.accept() method. The CharSummaryStatistics.combine() method is used to merge partial results.

Have you ever written a custom Java stream collector? Please drop your comments here.

The complete source code can be found on GitHub.

As a reference for writing this post, this article is part of a series about Streams and it is a good reference for learning how to aggregate and collect with Streams. All the articles from this series about Streams can be found here.

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Jcombiner: Combinations of collections for Java

JCombiner is a framework to generate combinations of collections for Java. I have written it in Java 11 using Java 9 modules (JPMS) and Gradle as build tool. JUnit 5 and Mockito are used for unit testing and Jacoco for code coverage. Streams and the Collectors API are extensively used throughout the development of JCombiner project.

Jcombiner’s source code is available under GitHub.

Code examples of its usage can be found on GitHub here. More examples can be found on this module inside JCombiner.

Share your comments about this framework here! Please feel free to contribute to it, more features are welcome!

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Streams in JDK 8: The Good, the Bad, and the Ugly

Great session in JavaOne 2017 about Streams and lambdas introduced in JDK8.

The session shows many examples of Java code using forEach() with side effects and how to refactor them to a functional approach using streams and the Collectors API.

What are your experiences using Streams and lambdas in JDK 8? Are you correctly using the Collectors API?

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Java 8: Converting Optional Collection to the Streams API

Although Java 9 has already been released, this post is about converting an optional collection to the Streams API introduced in Java 8.

Suppose some person could have zero, one or more cars and it is represented by the Person class below (some code omitted).

public class Person {

    private String name;

    .
    .
    .

    public Optional> getCars() {
        return Optional.ofNullable(cars);
    }

    .
    .
    .

}

Now we create a list of people and we want to get Mark’s cars.

Person mark = new Person("Mark");

List people = ...

How can we do that using the Streams API, since the getCars() method return an Optional?

One possibility is to filter people’s list by Mark’s name, filter the Optional if it is present or not and map its wrapped value (our cars list):

Collection markCars = people
                .stream()
                .filter(person -> "Mark".equals(person.getName()))
                .findFirst()
                .map(Person::getCars)
                .filter(Optional::isPresent)
                .map(Optional::get)
                .orElse(Collections.emptyList());

At this moment we reached the reason of this blog post. And how can we get all people’s cars? The idea here is to use the flatMap() operation unwrapping the Optional to the collection’s stream when it is present or getting an empty stream when it isn’t present:

Collection allPeopleCars = people
                .stream()
                .map(Person::getCars)
                .flatMap(mayHaveCars -> mayHaveCars.isPresent() ? mayHaveCars.get().stream() : Stream.empty())
                .collect(Collectors.toList());

We can do better and replace the above solution to be more functional using method references:

Collection allPeopleCars = people
                .stream()
                .map(Person::getCars)
                .flatMap(mayHaveCars -> mayHaveCars.map(Collection::stream).orElse(Stream.empty()))
                .collect(Collectors.toList());

If you use IntelliJ IDEA as your favorite IDE, it has an inspection that helps replacing Optional.isPresent() with a functional expression:

Collection allPeopleCars = people
                .stream()
                .map(Person::getCars)
                .flatMap(mayHaveCars -> mayHaveCars.map(Collection::stream).orElseGet(Stream::empty))
                .collect(Collectors.toList());

P.S. In Java 9, the stream() method was added to the Optional API, so we can rewrite the above stream pipeline into the following one:

Collection allPeopleCars = people
                .stream()
                .map(Person::getCars)
                .flatMap(Optional::stream)
                .flatMap(Collection::stream)
                .collect(Collectors.toList());

In case you are interested, this post on the IntelliJ IDEA blog has some good tips when working with Java 8.

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About the Kotlin programming language

Kotlin is a statically typed language which is fully interoperable with Java.

Recently my friend Andre showed me Kotlin‘s nice syntax and I considered giving it a try.

In the meantime, my friend Leonnardo sent me this nice link which helps migrating from Java to Kotlin easily.

Let’s compare some syntax from Java and Kotlin and see the differences. Suppose we have some employees and we want to group them by their departments.

In Java we create an Employee class, build some employees and use the Streams API to group them by their departments:

public class Employee {

    private final String name;

    private final String department;

    public Employee(final String name, final String department) {
        this.name = name;
        this.department = department;
    }

    public String getName() {
        return name;
    }

    public String getDepartment() {
        return department;
    }

    @Override
    public String toString() {
        return "Employee(name=" + name + ", department=" + department + ")";
    }
}

final Employee mark = new Employee("Mark", "Accounting");
final Employee john = new Employee("John", "Management");
final Employee smith = new Employee("Smith", "Administrative");
final Employee paul = new Employee("Paul", "Accounting");

final List employees = Arrays.asList(mark, john, smith, paul);

final Map> employeesByDepartment = employees
                .stream()
                .collect(Collectors.groupingBy(Employee::getDepartment));

In Kotlin we create a data class Employee, build some employees and use the collection built-in groupBy method to group them by their departments:

data class Employee(val name: String, val department: String)

val mark = Employee("Mark", "Accounting")
val john = Employee("John", "Management")
val smith = Employee("Smith", "Administrative")
val paul = Employee("Paul", "Accounting")

val employees = listOf(mark, john, smith, paul)

val employeesByDepartment = employees.groupBy { it.department }

As you can see, Kotlin has some syntactic sugar that makes it less verbose than Java.

If you haven’t considered trying Kotlin yet, I think it is worth giving it a try.

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