Last Updated on March 18th, 2024

Data Processing is the dominant part of a Software Application. As a developer, we can’t think of developing an application without data processing logics. However, almost every Java Application uses the Collections API to store and process data. Using Collections API, it is not so easy to write the codes for even some common data processing operations such as filtering, sorting, matching, finding, mapping etc. That’s why Java API designers have come up with Stream API in Java 8 to implement more complex data processing logics with the least number of lines of code.

So, in this article, we are going to learn Stream API in Java 8 and how to work with the complex data processing operations in an easy way. We will start with the fundamentals of Stream API in Java 8 and then move forward with the common operations that saves developer effort while implementing data processing logics. Let’s continue learning ‘Stream API in Java 8’ and its related concepts step by step.

What is the prerequisite to learn Stream API in Java 8? 

The stream API in Java 8 makes extensive use of built-in (predefined) functional interfaces that are part of the java.util.function package. So, we suggest you to have a clear understanding of the built-in (predefined) functional interfaces in advance before attempting to learn Stream API in Java 8. Moreover, it is expected that you have knowledge of the Lambda Expressions which is also a part of new feature introduced in Java 8.

What is Stream API in Java 8?

A stream in Java 8 is a sequence of data. It helps us in performing various operations with the data. This data can be obtained from several sources such as Collections, Arrays or I/O channels. There are two types of Stream: Sequential and Parallel. We can perform sequential operations when we obtain a stream using the stream() method, and parallel operations with parallelStream() method.

Furthermore, in order to support these operations on the data obtained from various collections, the Collection interface has been added with the two new methods stream() and parallelStream() in Java 8. Since interfaces such as List, Set, Deque, and Queue extend the Collection interface, we can get a stream or a parallel stream from the collection classes that implement these interfaces. For example, we can get a stream from an ArrayList object.

The most common source of streams is collection objects such as sets, maps, and lists. However, note that we can even use the streams API independent of the collections.

What are the Characteristics of Stream API?

1) We can create a stream from a source, perform operations on it and produce the result. The source may be a collection or an array or an I/O resource. The Stream does never modify the source.
2) Remember that Streams doesn’t store the data. We can’t add or remove elements from streams. Therefore, we can’t call them the data structures. They do only operations on the data.
3) Stream’s operations are primarily divided into two categories: Intermediate operations & Terminal operations.
4) Stream works on a concept of ‘Pipeline of Operations’. A pipeline of operations consists of three things : a source, zero or more intermediate operations and a terminal operation.

5) In order to gain the performance while processing the large amount of data, Stream has a concept of parallel processing without writing any multi threaded code.
6) All elements of a stream are not populated at a time. They are lazily populated as per demand because intermediate operations are not evaluated until terminal operation is invoked.
7) Generally, we can’t use the same stream more than once. If we use the stream first time, it is said to be consumed.

What are the ways of creating a Stream in Java?

There are several ways to create a Stream in Java. Let’s learn them one by one.

1) Using Stream.of() method 

The Stream.of() method takes a variable argument list of elements: static <T> Stream<T> of(T… values)

Stream<String> streamOfStrings =  Stream.of("Sunday", "Monday", "Wednesday", "Friday");

Stream<Integer> streamOfIntegers = Stream.of(1, 2, 3, 4, 5, 6, 7, 8, 9);

Integer[] array = {1, 2, 3, 4, 5, 6, 7, 8, 9};
Stream<Integer> streamOfArrayOfIntegers = Stream.of(array);

2) Stream from a Collection using stream() & parallelStream() methods 

java.util.Collection interface has stream() and parallelStream() methods to create sequential and parallel streams respectively. These methods return a stream of elements over the collection on which it is invoked.

List<String> list = Arrays.asList("https://","javatechonline", "dot", "com"); //creating a list
//OR
List<String> list = List.of("https://","javatechonline", "dot", "com"); //creating a list using of() of JDK 9

Stream<String> streamofStrings = list.stream(); // creating a sequential stream (used most of the time)
Stream<String> streamofStrings = list.parallelStream(); // creating a parallel stream

3) Stream from an Array using Arrays.stream()

We can also create a stream from an Array using stream() method of java.util.Arrays class which accepts an array as argument as shown below.

String[] arr= new String[] { "a", "b", "c" };

Stream<String> streamOfStrings = Arrays.stream(arr);

The Stream.of() and Arrays.stream() are two commonly used methods for creating a sequential stream from a specified array. Both these methods return a Stream when called with a non-primitive type T.

4) Stream using Stream.builder()

We can create a Stream using builder() method. In order to get a stream builder, invoke the static builder() method. This method returns an object of type java.util.stream.Stream.Builder. This builder object is then used to add elements to the stream using add method and then create the stream using build() method as shown below.

Builder<String> builder = Stream.<String>builder(); // creating a builder
builder.add("a").add("b").add("c"); // adding elements
Stream<String> s = builder.build(); // creating stream

Stream<String> s = Stream.<String>builder().add("a").add("b").add("c").build(); 

Stream<String>  emptyStream = Stream.empty();

Random random = new Random();
Stream<Integer> stream = 
                 Stream.generate(
                   () -> {return random.nextInt(100);} // generating random numbers between 0 and 99
                 ).limit(5);

Stream<Integer> streamOfOddNumbers = Stream.iterate(1, n -> n + 2);

Stream<String> streamOfStrings  = Files.lines(Paths.get(filePath));   // Generating Stream from a File

streamOfStrings.forEach((line) -> System.out.println(line));          // Printing contents of the File

Stream<String> streamWithCharset = Files.lines(path, Charset.forName("UTF-8"));

static IntStream range(int startInclusive, int endExclusive)
static IntStream rangeClosed(int startInclusive, int endInclusive)
static LongStream range(long startInclusive, long endExclusive)
static LongStream rangeClosed(long startInclusive, long endInclusive)

How to convert from a Stream to a Collection?

We can convert from a Stream to a Collection using one of the static methods in the Collectors class.

Example#1: Converting a Stream of strings to a List

List<String> strings = Stream.of("this", "is", "a", "list", "of", "strings")
                        .collect(Collectors.toList());

Example#2: Converting a Stream of int to a List of Integer

List<Integer> ints = IntStream.of(1, 2, 3, 4, 5, 6)
                      .collect(Collectors.toList()); // does not compile

However, we have multiple ways to make it work as shown below.

1) Using the boxed method : boxed() method converts int to Integer. We can use the boxed method on Stream to convert the IntStream to a Stream<Integer> as shown below:

List<Integer> ints = IntStream.of(1, 2, 3, 4, 5, 6)
                     .boxed()
                     .collect(Collectors.toList());

2) Using the mapToObj method : The mapToObj() method converts each element from a primitive to an instance of the wrapper class as below:

List<Integer> ints = IntStream.of(1, 2, 3, 4, 5, 6)
                     .mapToObj(Integer::valueOf) 
                     .collect(Collectors.toList());

Just as mapToInt, mapToLong, and mapToDouble parse streams of objects into the associated primitives, the mapToObj method from IntStream, LongStream, and Double Stream converts primitives to instances of the associated wrapper classes. The argument to mapToObj in this example uses the Integer constructor.

In JDK 9, the Integer(int val) constructor is deprecated for performance reasons. The recommendation is to use Integer.valueOf(int) instead.

Example#3: Converting an IntStream to an int array

int[] intArray = IntStream.of(1, 2, 3, 4, 5, 6).toArray();
// OR
int[] intArray = IntStream.of(1, 2, 3, 4, 5, 6).toArray(int[]::new);

Here, the first demo uses the default form of toArray, which returns Object[]. The second uses an IntFunction<int[]> as a generator, which creates an int[] of the proper size and populates it.

What are the major operations supported by Stream API?

The Stream API in Java 8 primarily categorizes two types of operations: Intermediate Operations and Terminal Operations

Intermediate Operations

When an operation on a stream further produces another stream as a result, we call it an intermediate operation. As intermediate operations return another stream as a result, they can be chained together to form a pipeline of operations. As the word ‘intermediate’ suggest, these operations doesn’t give end result. They just convert one stream to another stream. For example: map(), filter(), distinct(), sorted(), limit(), skip()

Terminal Operations

The operations which return non-stream values such as primitive or object are called terminal operations. Furthermore, unlike terminal operations, we can’t chain them together. They produce the end result. Once a terminal operation completes, the Stream is no longer valid. Hence, we can’t use that stream again. For example : forEach(), toArray(), reduce(), collect(), min(), max(), count(), anyMatch(), allMatch(), noneMatch(), findFirst(), findAny()

Note: Stream processing consists of a series of zero or more intermediate operations followed by a terminal operation. Each intermediate operation returns a new stream. The terminal operation returns something other than a stream.

What is Stream Pipeline?

Stream API in Java 8 works with a concept of Stream Pipeline. There are three parts to a Stream Pipeline.

Source: Where the stream comes from.

Intermediate Operations: Transforms the stream into another one. There can be as few or as many intermediate operations as you’d like. Since streams use lazy evaluation, the intermediate operations do not run until the terminal operation runs.

Terminal Operations: Actually produces a result. Since streams can be used only once, the stream is no longer valid after a terminal operation completes.

Pipeline of operations may contain any number of intermediate operations, but there has to be only one terminal operation, that too at the end of pipeline. Moreover, Intermediate operations are lazily loaded. When you call intermediate operations, they are actually not executed. They are just stored in the memory and executed when the terminal operation is called on the stream.

How to print a Stream?

When our code doesn’t work as expected, either we add a println() statement or go with setting a breakpoint to see the values of an object. Since intermediate operations don’t return something until needed, printing is not a straightforward process with the streams. Therefore, we need to apply some particular approaches to print the values. You will find that you have less requirement to print out the values of a stream as you get more practice with stream pipelines. However, while learning, printing is really helpful in order to debug the expected results using stream API in Java 8.

Below are some approaches to print streams:

1) s.forEach(System.out::println);

2) System.out.println(s.collect(Collectors.toList()));

3) s.limit(4).forEach(System.out::println);

4) s.peek(System.out::println).count(); 

Notice that only one of the approaches (third as described above) works for an infinite stream. It limits the number of elements in the stream before printing. If you try the others with an infinite stream, they will run until you kill the program.

Also, notice that if you want to use stream after printing, you can use approach number 4 as described above. This means that you cannot use the stream anymore after printing if you use other approaches.

How to use Stream Intermediate Operations?

Let’s start learning intermediate operations one by one under stream API in Java 8.

filter( )

Method signature:  Stream<T> filter(Predicate<? super T> predicate)

When to use filter( )? 

If you want to return a stream from another stream that satisfies a given condition.

Example

This operation is very handy and powerful because we can pass any Predicate to it. For example, this filters all elements that begin with the letter ‘m’:

Stream<String> s = Stream.of("lion", "cat", "monkey", "cow", "horse");
 s.filter(x -> x.startsWith("c")).forEach(System.out::print); 

Output

catcow

distinct( )

Method signature:  Stream<T> distinct()

When to use distinct( )? 

If you want to return a stream from another stream with duplicate values removed.

Example

For example, observe the below code:

Stream<String> s = Stream.of("cat", "cat", "monkey", "cow", "cat");
 s.distinct().forEach(System.out::print); 

Output

catmonkeycow

limit( ) and skip( )

Method signature: Stream<T> limit(int maxSize)
                              Stream<T> skip(int n)

When to use limit( ) and skip( )? 

If you want to make your stream smaller. Also, if you want to make a finite stream out of an infinite stream.

Example

Since both methods have a common characteristics, we will use them in a single example. Needless to say, using stream API in Java 8, we can use any number of intermediate operations in a Stream. The following code creates an infinite stream of numbers counting from 1. The skip() operation returns an infinite stream starting with the numbers counting from 10, as it skips the first nine elements because of skip(9). The limit() call takes the first six of those. Now we have a finite stream with six elements:

Stream<Integer> s = Stream.iterate(1, n -> n + 1); 
 s.skip(9).limit(6).forEach(System.out::print);  

Output

101112131415 

map( ) vs flatMap( ) 

Method signatures:     <R> Stream<R> map(Function<? super T,? extends R> mapper)
                                    <R> Stream<R> flatMap(Function<? super T,? extends Stream<? extends R>> mapper)

When to use map( ) and flatMap( )? 

If you want to transform the elements of a stream in some way. Use map() if you want to transform each element into a single value. Use flatMap() if you want to transform each element to multiple values and also compress/flatten the resulting stream.

map() is used when you want a one-to-one transformation, where each input element is mapped to exactly one output element. The result of map() is a stream of values, not a stream of streams. On the other hand, flatMap() is used when each element in the input stream can be mapped to zero, one, or multiple elements in the output stream. It’s specifically useful when you have a stream of collections or a stream of streams, and you want to flatten it into a single stream.

What is the difference between map( ) and flatMap( )? 

The additional word ‘flat’ in flatMap() method indicates the flattening, which is the additional task done by flatMap(). However below is the list of common differences between them.

map( )

1) It works on stream of values.
2) It performs the only transformation.
3) It produces a single value for each input value.

flatMap( )

1) It works on a stream of stream of values.
2) It performs transformation as well as flattening.
3) It produces multiple values for each input value.

Example

For example, let’s assume that we have a List of Programmers where each Programmer consists of two fields. One is its name and another one is its known skills which in another List. Below code demonstrates the concept using Stream API in Java 8.

public class Programmer {
   private String name;
   private List<String> skills;

   //getters, setters, AllArgsConstructor
}

List<Programmer> listOfProgrammers = List.of(
     new Programmer("Programmer1", List.of("Java", "Python", "Angular")),
     new Programmer("Programmer2", List.of("Ruby", "Angular", "Java")),
     new Programmer("Programmer3", List.of("React", "Spring", "Angular")) 
);

Suppose we have to extract name of each Programmer, that we can do by using map() method as shown below.

// Extracting the name of all Programmers using stream API in Java 8

listOfProgrammers.stream()
      .map(Programmer::getName)
      .collect(Collectors.toList())
      .forEach(System.out::println);

Output after applying map( )

Programmer1
Programmer2
Programmer3

Now, let’s use flatMap() to extract distinct skills out of all programmers as below. In the below piece of code, p -> p.getSkills() is a mapper function which is producing multiple values for each single input. i.e there are multiple skills for each Programmer. flatMap() is flattening those multiple values into a single stream. As we are collecting that stream into Set, we are getting only unique skills out of all Programmers.

listOfProgrammers.stream()
      .flatMap(p -> p.getSkills().stream())
      .collect(Collectors.toSet())
      .forEach(System.out::println);

Output after applying flatMap( )

Java
Spring
Ruby
React
Angular
Python

sorted( )

Method signature:  Stream<T> sorted()
Stream<T> sorted(Comparator<? super T> comparator)

When to use sorted( )? 

When we need to return a stream with the elements sorted. Just like sorting arrays, Java uses natural ordering unless we specify a comparator.

Example

Using First method signature, we can sort the stream in default order. However, second method signature allows us to pass a Comparator and sort the stream as per your need. For example, below code snippet demonstrate the concept using stream API in Java 8.

Stream<String> streamOfStrings = Stream.of("Sunday", "Monday", "Wednesday", "Friday");
 streamOfStrings.sorted().forEach(System.out::print);

Below code sorts the stream in reverse order.

streamOfStrings.sorted(Comparator.reverseOrder()).forEach(System.out::print);

Output

FridayMondaySundayWednesday

WednesdaySundayMondayFriday

In order to get the examples of other ways of sorting in Java, kindly visit our separate article on sorting.

peek() 

Method signature: Stream<T> peek(Consumer<? super T> action)

When to use peek( )? 

Sometimes we need to perform some operations on each element of the stream before any terminal operation is applied. In fact, peek() performs the specified operation on each element of the stream and returns a new stream that we can further use. It is useful for debugging because it allows us to perform a stream operation without actually changing the stream. The most common use for peek() is to output the contents of the stream before any terminal operation is applied.

Example

For example, observe the method below how it prints the values between the various intermediate operations using stream API in Java 8.

public int triplesDivisibleBy2Sum(int start, int end) {
    return IntStream.rangeClosed(start, end)
     .peek(n -> System.out.println("original element : " +n))         //prints value before multiplying by 3
     .map(n -> n * 3)
     .peek(n -> System.out.println("Tripled element : " +n))          //prints value before filtering
     .filter(n -> n % 2 == 0)
     .peek(n -> System.out.println("Divisible By 2 element : " +n))   //prints value after filtering but before summing
     .sum();
}

Output

If we call the above method passing parameters as : triplesDivisibleBy2Sum(10, 15); will display the output as below.

original element : 10
Tripled element : 30
Divisible By 2 element : 30
original element : 11
Tripled element : 33
original element : 12
Tripled element : 36
Divisible By 2 element : 36
original element : 13
Tripled element : 39
original element : 14
Tripled element : 42
Divisible By 2 element : 42
original element : 15
Tripled element : 45

How to use Stream Terminal Operations?

Let’s learn terminal operations one by one from easier to complex in sequence under stream API in Java 8.

count( )

Method signature: long count()

When to use count( )? 

When you want to determine the number of elements in a finite stream.

Example

For example, let’s call a count() method on a finite stream using stream API in Java 8 as shown below:

Stream<String> s = Stream.of("Cow", "Tiger", "Elephant"); 
System.out.println(s.count()); 

Output

3

min( ) and max( )

Method signature: Optional<T> min(<? super T> comparator)
                              Optional<T> max(<? super T> comparator)

When to use min( ) and max( )? 

when you want to find the smallest or largest value in a finite stream. As the method signature represents, the min() and max() methods allow us to pass a custom comparator and find the smallest or largest value in a finite stream according to that sort order. Like count(), min() and max() works on a finite stream. Also like count(), both methods are reductions because they return a single value after looking at the entire stream.

Example

This example finds the programming language with the fewest letters in its name using stream API in Java 8. Notice that the code returns an Optional rather than the value. We use the Optional method and a method reference to print out the minimum only if one is found.

Stream s = Stream.of("Java", "Python", "Scala"); 
Optional min = s.min((s1, s2) -> s1.length() — s2.length()); 
min.ifPresent(System.out::println); 

Output

Java

findAny( ) and findFirst( )

Method signature: Optional<T> findAny()
                              Optional<T> findFirst()

When to use findAny( ) and findFirst( )? 

You wish to find the first element in a stream that satisfies a particular condition then use findFirst(). The findFirst() and findAny() methods in Stream return an Optional describing the first element of a stream. Neither takes an argument, implying that any mapping or filtering operations have already been done.

The findAny() method returns an Optional describing some element of the stream, or an empty Optional if the stream is empty. In a non-parallel operation, findAny() will most likely return the first element in the Stream, but there is no guarantee for this. For maximum performance when processing the parallel operation, the result cannot be reliably determined.

Example

For example, given a list of integers, to find the first even number, apply an even number filter and then use findFirst() using stream API in Java 8, as in example below.

Optional firstEvenNumber = Stream.of(9, 5, 8, 7, 4, 9, 2, 11, 3)
                            .filter(n -> n % 2 == 0)
                            .findFirst();
System.out.println(firstEvenNumber);

Output

Optional[8]

Furthermore, if the stream is empty, the return value is an empty Optional (see Example below). For example, below code snippet uses findFirst() on an empty stream.

Optional firstNumberDivisibleBy5 = Stream.of(9, 5, 8, 7, 4, 9, 2, 11, 10, 3)
                                    .filter(n -> n > 10)             
                                    .filter(n -> n % 5 == 0)    //empty stream in this line
                                    .findFirst();
System.out.println(firstNumberDivisibleBy5); 

Output

Optional.empty

anyMatch( ), allMatch( ), and noneMatch( )

Method signature: boolean anyMatch(Predicate <? super T> predicate)
boolean allMatch(Predicate <? super T> predicate)
boolean noneMatch(Predicate <? super T> predicate) 

When to use anyMatch( ), allMatch( ), and noneMatch( )? 

When you wish to determine if any elements in a stream match a Predicate, or if all match, or if none match, then use the methods anyMatch(), allMatch(), and noneMatch() respectively.

Example

For example, observe the code snippet as shown below using stream API in Java 8.

List<String> listOfSkills = Arrays.asList("Core Java", "Spring Boot", "Hibernate", "Angular"); 

Predicate<String> pred = x -> x.startsWith("S"); 
System.out.println(listOfSkills.stream().anyMatch(pred));         // true 
System.out.println(listOfSkills.stream().allMatch(pred));         // false 
System.out.println(listOfSkills.stream().noneMatch(pred));        // false

The above program shows that we can reuse the same predicate, but we need a different stream each time. anyMatch() returns true because one of the four elements match. allMatch() returns false because three of them doesn’t match. noneMatch() also returns false because one matches.

Output

true
false
false

forEach( )

Method signature: void forEach(Consumer<? super T> action) 

When to use forEach( )? 

Needless to mention, when we want to iterate the elements of a stream. Notice that this is the only terminal operation with a return type of void. Moreover, note that you can call forEach() directly on a Collection or on a Stream. Stream API in Java 8 cannot use a traditional for loop to run because they don’t implement the Iterable interface.

Example

Below code example demonstrates the concept using Stream API in Java 8.

Stream<String> streamofSkills = Stream.of("Java", "Python", "Angular");
 streamofSkills.forEach(System.out::println);

Output

Java
Python
Angular

collect( )

Please note that the collect() method doesn’t belong to the Collectors class. It is defined in Stream class and that’s the reason you can call it on Stream after doing any filtering or mapping operations. However, it accepts a Collector to accumulate elements of Stream into a specified Collection.

Furthermore, the Collectors class provides various methods like toList(), toSet(), toMap(), and toConcurrentMap() to collect the result of Stream into List, Set, Map, and ConcurrentMap respectively. Additionally, it also provides a special toCollection() method that we can use to collect Stream elements into a specified Collection like ArrayList, Vector, LinkedList, HashSet etc.

Method signature: <R> R collect(Supplier<R> supplier,  BiConsumer<R, ? super T> accumulator, BiConsumer<R, R> combiner)
                              <R, A> R collect(Collector<? super T,  A, R> collector)

When to use collect( )? 

Most of the time, when you want to convert a stream back to a Collection which you got after applying various operations such as filter(), map() etc. It allows you to accumulate the result into a choice of containers you want like a list, set, map etc.

Example

For example, the below code snippet uses the Stream.collect() method where we will collect the result of the stream pipeline in a List. You can collect the result of a Stream processing pipeline in a list by using the Collectors.toList() method. Just pass the Collectors.toList() to collect() method as shown below using Stream API in Java 8:

Stream<String> streamOfSkills = Stream.of("Java", "Scala", "Python", "Spring");
 streamOfSkills
    .filter(x -> x.startsWith("S"))
    .collect(Collectors.toList())     //Collecting the result of a stream into a List
    .forEach(System.out::println);

Output

Scala
Spring

Let’s take an example of stream to convert it into a collection of your choice like ArrayList, HashSet, LinkedList etc. For example, let’s assume the same stream from previous example.

streamOfSkills
 .filter(x -> x.length() > 3)
 .collect(Collectors.toCollection(ArrayList::new))    //Collecting the result of a stream into a List of our choice
 .forEach(System.out::println);

Output

Python
Scala
Spring

reduce()

The reduce() method combines a stream into a single object. As we can tell from the name, it is a reduction.

Method signature:  T reduce(T identity, BinaryOperator<T> accumulator)
                               Optional<T> reduce(BinaryOperator<T> accumulator)
                               <U> U reduce(U identity,  BiFunction<U, ? super T, U> accumulator,  BinaryOperator<U> combiner)

Identity: An element that is the initial value of the reduction operation and the default result if the stream is empty

Accumulator:  A function that takes two parameters: a partial result of the reduction operation and the next element of the stream

Combiner: A function that we use to combine the partial result of the reduction operation when the reduction is parallelized or when there’s a mismatch between the types of the accumulator arguments and the types of the accumulator implementation

When to use reduce( )? 

When you wish to produce one single result from a sequence of elements, by repeatedly applying a combining operation to the elements in the sequence.

Example#1

For example, let’s observe the below code snippet and understand the reduce() in a better way under stream API in Java 8.

List<String> letters = Arrays.asList("j", "a", "v", "a", "t", "e", "c", "h", "o", "n", "l", "i", "n", "e"); 
String result = letters .stream()
    .reduce(" ", (partialString, element) -> partialString + element);
System.out.println(result);

In the example above, ” ” is the identity. It indicates the initial value of the reduction operation and also the default result when the stream of String values is empty. Likewise, the lambda expression “(partialString, element) -> partialString + element” is the accumulator as it takes the partial concatenation of String values and the next element in the stream.

Of course, we can also change it to the expression that uses a method reference like as below using Stream API in Java 8:

String result = letters.stream().reduce(" ", String::concat);

Output

javatechonline

Example#2

Likewise, let’s observe an example of Stream of Integers as below using Stream API in Java 8:

BinaryOperator op = (a, b) -> a * b; 
Stream empty = Stream.empty(); 
Stream oneElement = Stream.of(3); 
Stream threeElements = Stream.of(3, 4, 5); 
empty.reduce(op).ifPresent(System.out::print); // no output 
oneElement.reduce(op).ifPresent(System.out::print); // 3 
threeElements.reduce(op).ifPresent(System.out::print); // 60

♥ If you are looking for a coding practice on Steam API in Java 8 or interview questions preparation, kindly visit Stream API Interview Questions & Answers.

Also, if you want to know about the improvements of Stream API in Java 9, kindly visit a separate article on Stream Java 9 Improvements.

Conclusion

After going through all the theoretical & example part of ‘Stream API in Java 8’, finally, we should be able to work on the concept of Stream API in Java 8. Similarly, we expect from you to further extend these examples and implement them in your project accordingly. I hope you might be convinced by the article ‘Stream API in Java 8’. You may go through Oracle official documentation for further details. In addition, If there is any update in the future, we will also update the article accordingly. Moreover, Feel free to provide your comments in the comments section below.