Java Streams

advanced

Part of Advanced Java

Theory

The Streams API (introduced in Java 8) enables functional-style operations on sequences of data. A stream represents a pipeline of operations.

Stream Pipeline

A stream pipeline has three stages: source, intermediate operations, and terminal operation.

list.stream()          // Source
    .filter(n -> n > 5)   // Intermediate (lazy)
    .map(n -> n * 2)      // Intermediate (lazy)
    .forEach(System.out::println); // Terminal (eager)

Intermediate operations return a new stream and are lazy — they don't execute until a terminal operation is invoked.

map / filter / reduce

map — transforms each element (e.g., String::length)
filter — selects elements matching a predicate
reduce — aggregates elements into a single result

int sum = numbers.stream()
    .filter(n -> n > 0)
    .reduce(0, Integer::sum);

Collectors

Collectors accumulate stream elements into collections or other data structures:

List<String> list = stream.collect(Collectors.toList());
Set<String> set = stream.collect(Collectors.toSet());
String joined = stream.collect(Collectors.joining(", "));
Map<Integer, List<String>> grouped = stream
    .collect(Collectors.groupingBy(String::length));

Optional

Optional<T> is a container that may or may not contain a value. It helps avoid NullPointerException:

Optional<String> opt = Optional.ofNullable(getName());
opt.ifPresent(System.out::println);
String result = opt.orElse("default");

Parallel Streams

Call .parallelStream() or .parallel() to process elements concurrently. Use when operations are independent and the dataset is large.

Parallel Stream Example

java

Practical Examples

Example: Comprehensive Stream Pipeline

java

Exercises

Process Student Scores

easy

Given a list of student scores (integers), use streams to: filter passing scores (>= 60), double them, sort descending, and collect to a list. Also compute the average of passing scores using Optional.

Expected Output:

Passing doubled: [184, 176, 156, 142, 126]\nAverage: 78.4