A Guide To Java Stream API

Stream connects to the source of collections data structure and can performs specific operations on it. It was added in Java 8 under the Package name java.util.stream.

Introduction

What does it offers

It can Efficiently process large amounts of data.
Supports Parallel operations, to leverage multi core processors.
Lazy handling of pipeline operations & avoids unnecessary intermediate computations.
It represents a sequence of elements and supports different kind of operations to perform computations upon those elements.

Code Example

List<String> myList = Arrays.asList("a1", "a2", "b1", "c2", "c1");
myList.stream()
    .filter(s -> s.startsWith("c"))
    .map(String::toUpperCase)
    .sorted()
    .forEach(System.out::println);

Code Analysis:

From the code, we have a list of string data - "a1", "a2", "b1", "c2", "c1".
Filtering string that starts with character "c"
converting it to uppercase i.e "C1"
Sorting the list
Printing out each elements

Its a general overview. Lets understand more on streams creation, initialization, operations and execution.

1. Creating Streams

// Initializing array of String
String[] arr = new String[]{"a", "b", "c"};
// Coverting the array into stream
Stream<String> stream = Arrays.stream(arr);

// Or can also

// Initializing the stream
Stream<String> streamOfArray = Stream.of("a", "b", "c");

2. Stream Operations

forEach:
forEach() it loops over the stream elements. Lets say we have List<Product> productList = [ .. ] .

productsList.stream()
	.forEach(p -> p.setDiscount(true));

Map:
map() produces a new stream after applying a function to each element of the original stream. The new stream could be of different type.

List<Double> newEmployeeList = employeesList.stream()
	.map((employee) -> employee.getSalary())
	.collect(Collectors.toList());

Filter:
filter() produces a new stream of the elements that satisfy the given condition.

List<Employee> highSalEmpList = employeesList.stream()
	.filter((employee) -> employee.getSalary() > 50000)
	.collect(Collectors.toList());

flatMap:
For the complex data structures like-
Stream<List<String>>
flatMap() helps us to flatten the data structure. Lets say we have structure like this - [ [1,2,3],[4,5,6],[7,8,9] ] which has "two levels". In simple - Flattening means transforming it as : [ 1,2,3,4,5,6,7,8,9 ]

List<List<String>> namesNested = Arrays.asList(
	Arrays.asList("Jeff", "Bezos"),
	Arrays.asList("Bill", "Gates"),
	Arrays.asList("Mark", "Zuckerberg"));

List<String> namesFlatStream = namesNested.stream()
	.flatMap(Collection::stream)
	.collect(Collectors.toList());

Matching:
anyMatch(), allMatch(), noneMatch().
Lets say we have a collection of a color pencils.

List<String> colorPencils = Arrays.asList("greenPencil", "greyPencil", "blackPencil", "bluePencil", "redPencil", "greenPencil", "bluePencil");
boolean isGreenPencilAvailable = colorPencils.stream()
		.anyMatch(element -> element.contains("greenPencil")); // true

boolean isAllPencilsGreen = colorPencils.stream()
		.allMatch(element -> element.contains("greenPencil")); // false

boolean isGreenPencilsNotPresent = colorPencils.stream()
		.noneMatch(element -> element.contains("greenPencil")); // false

Specialized Operations:
Operation like sum(), average(), range(). Let's say we have List<Employee> empList = [ .. ]

Double avgSal = empList.stream()
	.mapToDouble(Employee::getSalary)
	.average()
	.orElseThrow(NoSuchElementException::new);

Reduction Operations:
(Identity, Accumulator, Combiner).

// with Identity and Accumulator
List<Integer> numbers = Arrays.asList(1, 2, 3, 4, 5, 6);
int result = numbers.stream()
	.reduce(0, (subtotal, element) -> subtotal + element);

Code Analysis:

reduce ( startingValue, binaryOperator/accumulator-fuction)
startingValue = 0, is the identity, also the default result if stream is empty and only initialized at first
subtotal is the accumulator storing the final value after each operation.
1st iteration: since startingValue = 0 than (subtotal/accumulator = 0, element = 1). arguments setted (subtotal, element)
operation: -> subtotal + element 0 + 1 = 1, now returning 1. subtotal = 1
2nd iteration: (subtotal = 1, element = 2). Operation: 1 + 2 = 3
3nd iteration: (subtotal = 3, element = 3). Operation: 3 + 3 = 6
Final result = 5

This was a example using identity and accumulator.
With Identity, Accumulator and Combiner - three arguments is used in parallel processing. Combiner works with parallel stream only, otherwise there is nothing to combine.

// with Identity, Accumulator and Combiner
List<Integer> list2 = Arrays.asList(5, 6, 7);
int res = list2.parallelStream()
	.reduce(1, (s1, s2) -> s1 * s2, (p, q) -> p * q);
// output 210

Collect:
Collect is used to get stuff out of the stream once we are done with all the processing.

List<Employee> employees = empList.stream()
	.collect(Collectors.toList());
Set<Employee> employees = empList.stream()
	.collect(Collectors.toSet());

Joining:
Collectors.joining() will insert the delimiter between the two String elements of the stream. Lets say we have List<Employee> empList = [ .. ]

String empNames = empList.stream()
	.map(Employee::getName)
	.collect(Collectors.joining(", "))
	.toString();

3. Order of Execution in stream operation

Stream.of("d2", "a2", "b1", "b3", "c")
	.filter(s -> {
				    System.out.println("filter: " + s);
					return true;
			    });

When executing this code snippet, nothing is printed to the console. That is because intermediate operations will only be executed when a terminal operation is present.

Stream.of("d2", "a2", "b1", "b3", "c")
	.filter(s -> {
				    System.out.println("filter: " + s);
					return true;
			    })
	.forEach(s -> System.out.println("forEach: " + s))

// output
filter: d2
forEach: d2
filter: a2
forEach: a2
filter: b1
forEach: b1
filter: b3
forEach: b3
filter: c
forEach: c

The order of the execution is very important to understand in stream operations.

Stream.of("d2", "a2", "b1", "b3", "c")
	.filter(s -> {
					System.out.println("filter: " + s);
					return s.startsWith("a");
			    })
	.sorted((s1, s2) -> {
						    System.out.printf("sort: %s; %s\n", s1, s2);
							return s1.compareTo(s2);
			            })
    .map(s -> {
                System.out.println("map: " + s);
                return s.toUpperCase();
            })
    .forEach(s -> System.out.println("forEach: " + s));

// output
filter: d2
filter: a2
filter: b1
filter: b3
filter: c
map: a2
forEach: A2

For more info See:

A Guide To Java Stream API

Introduction

1. Creating Streams

2. Stream Operations

3. Order of Execution in stream operation

Previous Article

Next Article