Parallel Streams

In Java 8, the Stream API introduced the concept of parallel streams, which allows us to harness the power of multi-threading in order to process stream elements in parallel and improve performance.

Traditionally, stream operations are performed sequentially, where each element is processed one by one. However, when dealing with large datasets or computationally intensive operations, processing elements sequentially may result in slower performance.

By utilizing parallel streams, we can divide the stream into multiple chunks and process each chunk in parallel on separate threads. This enables us to take advantage of multi-core processors and distribute the workload, potentially reducing the overall processing time.

To create a parallel stream, we simply need to call the parallelStream() method instead of the stream() method. Here's a code example:

1List<Integer> numbers = Arrays.asList(1, 2, 3, 4, 5);
2
3int sum = numbers.parallelStream()
4                .reduce(0, Integer::sum);
5
6System.out.println(sum); // Output: 15

In this example, we have a list of integers and we use the parallelStream() method to create a parallel stream. We then use the reduce() method to calculate the sum of the elements in the stream, with an initial value of 0. Finally, we print the result.

Keep in mind that not all operations are suitable for parallel processing, as some operations may have dependencies or produce non-deterministic results. It's important to evaluate the requirements and characteristics of your specific use case to determine whether parallel streams can provide performance benefits.

Feel free to modify the list of numbers and see the result!

By leveraging parallel streams, we can effectively utilize multi-threading capabilities to improve the performance of stream operations in Java 8.

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import java.util.Arrays;

import java.util.List;

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public class Main {

​

    public static void main(String[] args) {

        List<Integer> numbers = Arrays.asList(1, 2, 3, 4, 5);

​

        int sum = numbers.parallelStream()

                .reduce(0, Integer::sum);

​

        System.out.println(sum);

    }

​

}