Java Streams Performance Issue when Processing Large Collections with Parallel Processing
I need some guidance on I'm encountering a significant performance issue when trying to process large collections using Java Streams with parallel processing... I have a collection of around 1 million integers, and I'm trying to compute the sum of the squares of even numbers. When I switch to parallel streams, I notice that the performance actually degrades instead of improving, which is the opposite of what I expected. Here's the code I'm using: ```java import java.util.List; import java.util.stream.Collectors; import java.util.stream.IntStream; public class ParallelStreamExample { public static void main(String[] args) { List<Integer> numbers = IntStream.rangeClosed(1, 1_000_000) .boxed() .collect(Collectors.toList()); long startTime = System.currentTimeMillis(); long sum = numbers.parallelStream() .filter(n -> n % 2 == 0) .map(n -> n * n) .reduce(0, Integer::sum); long endTime = System.currentTimeMillis(); System.out.println("Sum of squares: " + sum); System.out.println("Time taken: " + (endTime - startTime) + " ms"); } } ``` When I run this, the output time taken is around 1500 ms, while the sequential version takes about 800 ms. Here’s the sequential version for comparison: ```java long startTimeSeq = System.currentTimeMillis(); long sumSeq = numbers.stream() .filter(n -> n % 2 == 0) .map(n -> n * n) .reduce(0, Integer::sum); long endTimeSeq = System.currentTimeMillis(); System.out.println("Sequential Sum of squares: " + sumSeq); System.out.println("Sequential Time taken: " + (endTimeSeq - startTimeSeq) + " ms"); ``` I've tried adjusting the size of the collection and even tested it on different machines, but the results remain the same. I suspect it might be related to the overhead of managing threads or perhaps the nature of the operations being performed. Could someone provide insights into why parallel streams are underperforming here? Are there specific scenarios where using parallel streams is not beneficial, especially for this type of operation? My development environment is Windows 11. I'd love to hear your thoughts on this.