測試結果顯示：阻塞佇列和併發佇列在高併發情況下，效能相差不大。

 public class ConcurrentQueueTest { private static int COUNT = 100000; private static int THREAD_NUM = 10; private static CyclicBarrierThread cyclicBarrierThread = new CyclicBarrierThread(); private static ConcurrentLinkedQueue conQueue = new ConcurrentLinkedQueue(); private static LinkedBlockingQueue linkQueue = new LinkedBlockingQueue(); static class ConcurrentLinkedQueueProducer extends Test { public ConcurrentLinkedQueueProducer(String id, CyclicBarrier barrier, long count, int threadNum, ExecutorService executor) { super(id, barrier, count, threadNum, executor); } @Override protected void test() { conQueue.add(1); } } static class LinkedBlockingQueueProducer extends Test { public LinkedBlockingQueueProducer(String id, CyclicBarrier barrier, long count, int threadNum, ExecutorService executor) { super(id, barrier, count, threadNum, executor); } @Override protected void test() { conQueue.add(1); } } static class CyclicBarrierThread extends Thread { @Override public void run() { conQueue.clear(); linkQueue.clear(); } } public static void test(String id, long count, int threadNum, ExecutorService executor) { final CyclicBarrier barrier = new CyclicBarrier(threadNum + 1, cyclicBarrierThread); System.out.println("=============================="); System.out.println("count = " + count + "/t" + "Thread Count = " + threadNum); concurrentTotalTime += new ConcurrentLinkedQueueProducer( "ConcurrentLinkedQueueProducer", barrier, COUNT, threadNum, executor).startTest(); linkedBlockingTotalTime += new LinkedBlockingQueueProducer( "LinkedBlockingQueueProducer ", barrier, COUNT, threadNum, executor).startTest(); totalThreadCount += threadNum; executor.shutdownNow(); System.out.println("=============================="); } static long concurrentTotalTime = 0; static long linkedBlockingTotalTime = 0; static long totalThreadCount = 0; public static void main(String[] args) throws InterruptedException { for (int i = 1; i < 20; i++) { ExecutorService executor = Executors.newFixedThreadPool(THREAD_NUM * i); test("", COUNT, 10 * i, executor); } System.out.println("ConcurrentLinkedQueue Avg Time = " + concurrentTotalTime / totalThreadCount); System.out.println("LinkedBlockingQueue Avg Time = " + linkedBlockingTotalTime / totalThreadCount); } }

結果，執行100，000次的併發入隊操作，併發佇列需要49毫秒，阻塞佇列需要53毫秒，比阻塞佇列平均快4毫秒。這種平均值的演算法可能不準確，因為隨著執行緒數量的增加，執行緒之間切換的開銷會逐漸增大。 ============================== count = 100000 Thread Count = 10 ConcurrentLinkedQueueProducer = 422 LinkedBlockingQueueProducer = 390 ============================== ============================== count = 100000 Thread Count = 20 ConcurrentLinkedQueueProducer = 782 LinkedBlockingQueueProducer = 828 ============================== ============================== count = 100000 Thread Count = 30 ConcurrentLinkedQueueProducer = 1468 LinkedBlockingQueueProducer = 1422 ============================== ============================== count = 100000 Thread Count = 40 ConcurrentLinkedQueueProducer = 2188 LinkedBlockingQueueProducer = 1297 ============================== ============================== count = 100000 Thread Count = 50 ConcurrentLinkedQueueProducer = 2609 LinkedBlockingQueueProducer = 2625 ============================== ============================== count = 100000 Thread Count = 60 ConcurrentLinkedQueueProducer = 3078 LinkedBlockingQueueProducer = 2969 ============================== ============================== count = 100000 Thread Count = 70 ConcurrentLinkedQueueProducer = 4046 LinkedBlockingQueueProducer = 3594 ============================== ============================== count = 100000 Thread Count = 80 ConcurrentLinkedQueueProducer = 4047 LinkedBlockingQueueProducer = 4078 ============================== ============================== count = 100000 Thread Count = 90 ConcurrentLinkedQueueProducer = 4469 LinkedBlockingQueueProducer = 5109 ============================== ============================== count = 100000 Thread Count = 100 ConcurrentLinkedQueueProducer = 5125 LinkedBlockingQueueProducer = 4922 ============================== ============================== count = 100000 Thread Count = 110 ConcurrentLinkedQueueProducer = 5531 LinkedBlockingQueueProducer = 5969 ============================== ============================== count = 100000 Thread Count = 120 ConcurrentLinkedQueueProducer = 5172 LinkedBlockingQueueProducer = 6188 ============================== ============================== count = 100000 Thread Count = 130 ConcurrentLinkedQueueProducer = 7187 LinkedBlockingQueueProducer = 6594 ============================== ============================== count = 100000 Thread Count = 140 ConcurrentLinkedQueueProducer = 6937 LinkedBlockingQueueProducer = 7782 ============================== ============================== count = 100000 Thread Count = 150 ConcurrentLinkedQueueProducer = 6921 LinkedBlockingQueueProducer = 8875 ============================== ============================== count = 100000 Thread Count = 160 ConcurrentLinkedQueueProducer = 8047 LinkedBlockingQueueProducer = 9250 ============================== ============================== count = 100000 Thread Count = 170 ConcurrentLinkedQueueProducer = 8235 LinkedBlockingQueueProducer = 9656 ============================== ============================== count = 100000 Thread Count = 180 ConcurrentLinkedQueueProducer = 9062 LinkedBlockingQueueProducer = 9719 ============================== ============================== count = 100000 Thread Count = 190 ConcurrentLinkedQueueProducer = 9422 LinkedBlockingQueueProducer = 9609 ============================== ConcurrentLinkedQueue Avg Time = 49 LinkedBlockingQueue Avg Time = 53