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.

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!

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
                .filter(person -> "Mark".equals(person.getName()))

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
                .flatMap(mayHaveCars -> mayHaveCars.isPresent() ? mayHaveCars.get().stream() : Stream.empty())

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

Collection allPeopleCars = people
                .flatMap(mayHaveCars -> mayHaveCars.map(Collection::stream).orElse(Stream.empty()))

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
                .flatMap(mayHaveCars -> mayHaveCars.map(Collection::stream).orElseGet(Stream::empty))

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

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

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;

    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

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.

Converting a Map to a List in Java 8, Groovy and Ruby

Some days ago I was developing a task on a Gradle project and I faced with a situation where I had to convert a Map < String, List < String >> to List < Pair >, each pair containing the key and one element from the List<String>.

I decided to compare the solution in three different languages: Java 8 (using lambdas and the Streams API), Groovy and Ruby to see how concise and expressive they would be. Then, I created the Groovy code and it looked like this:

#!/usr/bin/env groovy

def map = ["a" : ["1", "2", "3"], "b" : ["4", "5", "6"], "c" : ["7"]]

println map.collectMany { key, values -> values.collect {value -> [key, value]}}

Running the above code, the result is below:

[[a, 1], [a, 2], [a, 3], [b, 4], [b, 5], [b, 6], [c, 7]]

The Ruby version looked like this:

#!/usr/bin/env ruby

map = { "a" => ["1", "2", "3"], "b" => ["4", "5", "6"], "c" => ["7"] }

p map.collect {|key, values| values.map {|value| [key, value] } }.flatten(1)

The Ruby program generated the following output:

[["a", "1"], ["a", "2"], ["a", "3"], ["b", "4"], ["b", "5"], ["b", "6"], ["c", "7"]]

Below is the Java 8 version, using lambdas, Streams and the Collectors API:

        Map> values = new HashMap<>();
        values.put("a", Arrays.asList("1", "2", "3"));
        values.put("b", Arrays.asList("4", "5", "6"));
        values.put("c", Collections.singletonList("7"));

        final List result = values
                        (pairs, entry) -> pairs.addAll(entry
                                .map(value -> new Pair(entry.getKey(), value))

private static class Pair {

    private final String first;
    private final String second;

    public Pair(String first, String second) {
        this.first = first;
        this.second = second;

    public String toString() {
        return "Pair{first='" + first + "', second='" + second + "'}";

Running the Java 8 version produced the following output:

[Pair{first='a', second='1'}, Pair{first='a', second='2'}, 
Pair{first='a', second='3'}, Pair{first='b', second='4'}, 
Pair{first='b', second='5'}, Pair{first='b', second='6'}, 
Pair{first='c', second='7'}]

The Groovy and Ruby version are very expressive and concise. Note the use of the collectMany method on the Groovy version and the use of the flatten method on the Ruby version to flatten the result list into a single list of pairs.
The Java 8 version made use of the collect method of the Stream API, to collect the results in a list of Pair instances, each one holding the key and value of each element from the List< String >.

What do you think about this comparison? Leave your comments here!