并行执行CompletableFuture处理大型列表：优化性能的实用指南

import com.google.common.collect.Lists;
import java.util.List;
import java.util.concurrent.CompletableFuture;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.stream.Collectors;

public class CompletableFutureParallel {

    public static void main(String[] args) {
        int noOfCores = Runtime.getRuntime().availableProcessors();
        ExecutorService service = Executors.newFixedThreadPool(noOfCores - 1);
        List<Integer> list = List.of(1, 2, 3, 4, 5, 6, 7, 8, 9, 10); // 示例数据

        // 将任务提交到线程池
        List<CompletableFuture<List<Integer>>> completableFutureList = Lists.partition(list, 2).stream()
                .map(item -> CompletableFuture.supplyAsync(() -> executeListPart(item), service))
                .collect(Collectors.toList());

        // 等待所有任务完成
        completableFutureList.forEach(CompletableFuture::join);

        // 收集结果
        List<Integer> result = completableFutureList.stream()
                .map(CompletableFuture::join) // 再次join，确保获取到结果
                .flatMap(List::stream)
                .collect(Collectors.toList());

        System.out.println("Result: " + result);

        service.shutdown();
    }

    // 模拟耗时操作
    private static List<Integer> executeListPart(List<Integer> item) {
        try {
            Thread.sleep(1000); // 模拟处理时间
        } catch (InterruptedException e) {
            Thread.currentThread().interrupt();
        }
        System.out.println("Processing: " + item + " in thread: " + Thread.currentThread().getName());
        return item.stream().map(i -> i * 2).collect(Collectors.toList()); // 示例操作
    }
}

CompletableFuture<Void> allFutures = CompletableFuture.allOf(completableFutureList.toArray(new CompletableFuture[0]));
allFutures.join();