Master Java Stream API: From Basics to Advanced Operations

Stream Introduction

Java 8 introduced a new Stream API. Unlike I/O streams, it behaves like an Iterable collection but with distinct characteristics.

Streams enhance collection functionality, focusing on convenient and efficient aggregation or bulk data operations.

By specifying operations—e.g., filtering strings longer than 10 characters or extracting first letters—Stream implicitly traverses elements and performs the transformations.

Why Use Streams

Functional programming makes code express business intent rather than implementation details, resulting in more readable, maintainable, reliable, and less error‑prone code.

Example Data Source

Filter

Used to traverse data and test each element. The filter method accepts a lambda expression as its predicate.

Map

Map creates a one‑to‑one transformation of each element, a commonly used operation that is simple to apply.

FlatMap

FlatMap is similar to map but supports deeper, one‑to‑many transformations, allowing each input element to be mapped to multiple output elements.

Method signatures:

<r> Stream<r> map(Function<? super T, ? extends R> mapper);

<r> Stream<r> flatMap(Function<? super T, ? extends Stream<? extends R>> mapper);

FlatMap handles scenarios where the mapping results in a collection of collections, flattening them into a single stream.

Reduce

Reduce performs aggregation similar to recursion, such as summing numbers or concatenating strings.

Collect

Collect creates common data structures from a stream, such as lists, sets, or maps, and also supports custom collectors.

Typical collectors include toList(), toSet(), and toMap().

Optional

Optional is a new data type designed to replace null, addressing many complaints about null handling. It is widely usable, including in lambda expressions.

Key methods: Optional.of(T) – creates an Optional for a non‑null value, otherwise throws an exception. Optional.ofNullable(T) – creates an Optional that may contain null. isPresent() – checks if a value is present (equivalent to != null). ifPresent(Consumer<? super T>) – executes the given lambda if the value is non‑null.

Concurrency

Replace stream() with parallelStream() or parallel() to enable parallel processing.

Performance depends on data size, source structure, boxing, CPU core count, and per‑element processing time.

Debugging

Streams are chained (e.g., list.stream().filter(...).map(...).collect(...)), with intermediate operations being lazy and terminal operations triggering evaluation.

Use peek() to inspect elements without terminating the stream.

Original source: https://www.jianshu.com/p/9fe8632d0bc2