Java Streams: A Modern Way to Process Data

Introduced in Java 8, the Stream API brings a functional approach to processing collections. With streams, you can perform operations like filtering, mapping, and reducing in a concise and readable way.

🔍 What is a Stream?

A Stream represents a sequence of elements and supports sequential and parallel aggregate operations.

List<String> names = Arrays.asList("Alice", "Bob", "Charlie");

names.stream()
     .filter(name -> name.startsWith("A"))
     .forEach(System.out::println);

Output: Alice

⚙️ Common Operations

1. filter()

Filters elements based on a condition:

List<Integer> nums = Arrays.asList(1, 2, 3, 4, 5);
nums.stream()
    .filter(n -> n % 2 == 0)
    .forEach(System.out::println);

2. map()

Transforms each element:

List<String> names = Arrays.asList("Java", "Python", "Go");

names.stream()
     .map(String::toUpperCase)
     .forEach(System.out::println);

3. reduce()

Reduces the stream to a single value:

int sum = Stream.of(1, 2, 3, 4)
                .reduce(0, Integer::sum);

System.out.println(sum);

Output: 10

🔁 Collecting Results

You can collect stream results into collections:

List<String> filtered = names.stream()
                             .filter(n -> n.length() > 3)
                             .collect(Collectors.toList());

🚀 Parallel Streams

Process elements in parallel using multiple threads:

list.parallelStream()
    .filter( ... )
    .map( ... )
    .collect(Collectors.toList());

Use with care — not always faster depending on workload and thread management.

✅ Summary

• Streams make code cleaner and easier to read.
• They enable functional-style operations on collections.
• Use map, filter, reduce, collect for powerful transformations.

Java Streams = less boilerplate, more power. Try them in your next project!