WINDOWS 下， Redis 单机事务测试

WIN 10： i5 4440， 8GB

测试REDIS的事务速度

REDIS的WATCH机制实现事务是一个乐观锁形式（应该是SPIN LOCK的一种）。适用于并发度不是很高的场景，可以节约CPU资源（轻量级锁）。但是当竞争激烈的情况下，失败概率会大大提升，大量失败后的重试会耗费CPU资源。

测试的逻辑

1）读取计数器

2）JAVA端自增

3）设置回REDIS

此处不可用REDIS自带的incr函数，REDIS服务器端为单线程执行，所以服务器端只执行一个incr指令的情况下，其实可以看作原子操作, 服务器端直接执行1-2秒就可以了，当然取决于电脑。

计数器计算到10万为止。（线程增多，那么每个线程负载计算量就减少）

package one;

import java.text.NumberFormat;
import java.util.concurrent.CountDownLatch;

import redis.clients.jedis.Jedis;
import redis.clients.jedis.Transaction;

public class TransactionContentionTest extends ConnectionBuilder {
    private static final int CONTENTION_LEVEL = 5;
    private static final int TOTAL = 20000;
    private static final NumberFormat nf = NumberFormat.getPercentInstance();

    public static void main(String[] args) throws Exception {
        nf.setMinimumFractionDigits(2);
        buildPool();
        CountDownLatch latch = new CountDownLatch(CONTENTION_LEVEL);
        Thread[] threads = new Thread[CONTENTION_LEVEL];
        ContentionClient[] clients = new ContentionClient[CONTENTION_LEVEL];
        Jedis jedis = pool.getResource();
        jedis.set("TestCounter", "0");
        jedis.close();
        for (int i = 0; i < CONTENTION_LEVEL; i++) {
            ContentionClient client = new ContentionClient();
            client.setTotal(TOTAL);
            client.setCounterName("TestCounter");
            client.setJedis(pool.getResource());
            client.setLatch(latch);
            clients[i] = client;
            threads[i] = new Thread(client);
        }
        long start = System.currentTimeMillis();
        for (int i = 0; i < CONTENTION_LEVEL; i++) {
            threads[i].start();
        }
        latch.await();
        long end = System.currentTimeMillis();
        System.out.println("Elapse:" + (end - start) + " ms");
        for (int i = 0; i < CONTENTION_LEVEL; i++) {
            Double failRate = (double) clients[i].getFailCount() / TOTAL;
            System.out.println(i + " Fail Rate:" + nf.format(failRate));
            clients[i].getJedis().close();
        }
        close();
    }

    static class ContentionClient implements Runnable {
        private Jedis jedis;
        private String counterName;
        private int total;
        private long failCount = 0;

        public CountDownLatch getLatch() {
            return latch;
        }

        public void setLatch(CountDownLatch latch) {
            this.latch = latch;
        }

        private CountDownLatch latch;

        public Jedis getJedis() {
            return jedis;
        }

        public void setJedis(Jedis jedis) {
            this.jedis = jedis;
        }

        public String getCounterName() {
            return counterName;
        }

        public void setCounterName(String counterName) {
            this.counterName = counterName;
        }

        public int getTotal() {
            return total;
        }

        public void setTotal(int total) {
            this.total = total;
        }

        public long getFailCount() {
            return failCount;
        }

        public void setFailCount(long failCount) {
            this.failCount = failCount;
        }

        @Override
        public void run() {
            while (total > 0) {
                jedis.watch(counterName);
                Integer counter = Integer.parseInt(jedis.get(counterName));
                Transaction tx = jedis.multi();
                counter++;
                tx.set(counterName, counter.toString());
                if (tx.exec() == null) {
                    jedis.unwatch();
                    failCount++;
                } else {
                    total--;
                }
            }
            latch.countDown();
        }
    }
}

分别测试多组数据

用乐观锁机制并发度稍微高一点的情况，资源耗费非常严重。

毕竟用的是WINDOWS和家用机，测试的数据，没有参考价值。