Java 17 Streams Performance Degradation with Large Data Sets Using Collectors.groupingBy()
I'm trying to implement I'm building a feature where I'm wondering if anyone has experience with I'm currently facing a significant performance issue when using Java 17 Streams for processing large datasets... My application processes a list of over 1 million records, and I'm trying to group them by a specific attribute using `Collectors.groupingBy()`. When I run my code, it takes an unexpectedly long time to complete, and I've tracked the bottleneck to this specific operation. Here's a simplified version of my code: ```java import java.util.List; import java.util.stream.Collectors; public class DataProcessor { public static void main(String[] args) { List<DataItem> items = generateLargeDataSet(); // This generates 1M items long startTime = System.currentTimeMillis(); var grouped = items.stream() .collect(Collectors.groupingBy(DataItem::getCategory)); long endTime = System.currentTimeMillis(); System.out.println("Processing time: " + (endTime - startTime) + " ms"); } } class DataItem { private String category; // Assume there are more fields and a constructor public String getCategory() { return category; } } ``` When I run this, the processing time is around 15 seconds, which seems excessive for grouping operations. I’ve tried increasing the parallelism by using `parallelStream()` instead, but it yields only marginal improvements and sometimes even a slowdown. I've also ensured that the `DataItem` objects are not holding any unnecessary references and have implemented proper equals and hashCode methods. My dataset is simple but large, and I can’t seem to find a way to optimize this further. Are there any best practices or alternative approaches to improve the performance of grouping in streams, especially for such large data sets? Any insights or suggestions would be greatly appreciated! My development environment is Windows 10. Has anyone else encountered this?