LRU缓存的实现之性能测试

最新推荐文章于 2025-06-11 10:20:47 发布

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最新推荐文章于 2025-06-11 10:20:47 发布

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分类专栏： concurrent 文章标签： performance thread J#

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本文介绍了一个使用Java进行的并发性能测试案例，通过50个线程对10,000条随机数据进行读写操作，展示了如何设置线程池并记录性能指标。

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针对上一篇文章，这里给出性能测试：10000条随机数据，50个线程读写。

package lru;

import java.util.Random;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;

public class Performance{
	static final int loop = 10000;
	static final int threadCount = 50;
	static OjadbMap<Integer, Integer> lruMap = new OjadbMap<Integer, Integer>(loop);
	static ExecutorService exec = Executors.newFixedThreadPool(threadCount);
	static long nn = 0;
	static int check=0;

	public static void main(String[] args) throws InterruptedException {
		Performance p = new Performance();
		p.start();
	}

	private void start() throws InterruptedException {
		loops();
		Thread.sleep(7500);
		System.out.println(check+" spend time=" + nn);
		System.out.println(" every milli-seconds=" + (check / nn));
		lruMap=null;
		exec.shutdown();
	}

	private void loops() {
		for (int i = 0; i < threadCount; i++) {
			exec.execute(new Thread("thread-" + i){
				@Override
				public void run() {
					final long begin = System.currentTimeMillis();
					Random r = new Random();
					for (int j = 0; j < loop; j++) {
						check++;
						int n = r.nextInt(100);
						if (null == lruMap.get(n)) {
							lruMap.put(n, j);
						} else {
						}
					}
					final long end = System.currentTimeMillis();
					final long elapsed = end - begin;
					nn = nn + elapsed;
				}
			});
		}
	}
}