Java客户端Jedis 对Redis的的八种调用方式(事务、管道、分布式)介绍及测试

信息发布:soゝso 发布日期:2016-08-22 16:34 热度:582 分享到:

Redis  是一个著名的key-value存储中间件,而作为其官方推荐的 java  版客户端 jedis  也非常强大和稳定,支持事务、管道及有 jedis  自身实现的分布式。

在这里对 jedis  关于事务、管道和分布式的调用方式做一个简单的介绍和对比:

一、普通同步方式

最简单和基础的调用方式。

@Test
public void test1Normal() {
    Jedis jedis = new Jedis("localhost");
    long start = System.currentTimeMillis();
    for (int i = 0; i < 100000; i++) {
        String result = jedis.set("n" + i, "n" + i);
    }
    long end = System.currentTimeMillis();
    System.out.println("Simple SET: " + ((end - start)/1000.0) + " seconds");
    jedis.disconnect();
}

很简单吧,每次set之后都可以返回结果,标记是否成功。

二、事务方式(Transactions)

redis  的事务很简单,他主要目的是保障,一个client发起的事务中的命令可以连续的执行,而中间不会插入其他client的命令。

看下面例子:

@Test
public void test2Trans() {
    Jedis jedis = new Jedis("localhost");
    long start = System.currentTimeMillis();
    Transaction tx = jedis.multi();
    for (int i = 0; i < 100000; i++) {
        tx.set("t" + i, "t" + i);
    }
    List<Object> results = tx.exec();
    long end = System.currentTimeMillis();
    System.out.println("Transaction SET: " + ((end - start)/1000.0) + " seconds");
    jedis.disconnect();
}

我们调用jedis.watch(…)方法来监控key,如果调用后key值发生变化,则整个事务会执行失败。另外,事务中某个操作失败,并不会回滚其他操作。这一点需要注意。还有,我们可以使用discard()方法来取消事务。

三、管道(Pipelining)

有时,我们需要采用异步方式,一次发送多个指令,不同步等待其返回结果。这样可以取得非常好的执行效率。这就是管道,调用方法如下:

@Test
public void test3Pipelined() {
    Jedis jedis = new Jedis("localhost");
    Pipeline pipeline = jedis.pipelined();
    long start = System.currentTimeMillis();
    for (int i = 0; i < 100000; i++) {
        pipeline.set("p" + i, "p" + i);
    }
    List<Object> results = pipeline.syncAndReturnAll();
    long end = System.currentTimeMillis();
    System.out.println("Pipelined SET: " + ((end - start)/1000.0) + " seconds");
    jedis.disconnect();
}

四、管道中调用事务

就Jedis提供的方法而言,是可以做到在管道中使用事务,其代码如下:

@Test
public void test4combPipelineTrans() {
    jedis = new Jedis("localhost"); 
    long start = System.currentTimeMillis();
    Pipeline pipeline = jedis.pipelined();
    pipeline.multi();
    for (int i = 0; i < 100000; i++) {
        pipeline.set("" + i, "" + i);
    }
    pipeline.exec();
    List<Object> results = pipeline.syncAndReturnAll();
    long end = System.currentTimeMillis();
    System.out.println("Pipelined transaction: " + ((end - start)/1000.0) + " seconds");
    jedis.disconnect();
}

但是经测试(见本文后续部分),发现其效率和单独使用事务差不多,甚至还略微差点。

五、分布式直连同步调用

@Test
public void test5shardNormal() {
    List<JedisShardInfo> shards = Arrays.asList(
            new JedisShardInfo("localhost",6379),
            new JedisShardInfo("localhost",6380));

    ShardedJedis sharding = new ShardedJedis(shards);

    long start = System.currentTimeMillis();
    for (int i = 0; i < 100000; i++) {
        String result = sharding.set("sn" + i, "n" + i);
    }
    long end = System.currentTimeMillis();
    System.out.println("Simple@Sharing SET: " + ((end - start)/1000.0) + " seconds");

    sharding.disconnect();
}

这个是分布式直接连接,并且是同步调用,每步执行都返回执行结果。类似地,还有异步管道调用。

六、分布式直连异步调用

@Test
public void test6shardpipelined() {
    List<JedisShardInfo> shards = Arrays.asList(
            new JedisShardInfo("localhost",6379),
            new JedisShardInfo("localhost",6380));

    ShardedJedis sharding = new ShardedJedis(shards);

    ShardedJedisPipeline pipeline = sharding.pipelined();
    long start = System.currentTimeMillis();
    for (int i = 0; i < 100000; i++) {
        pipeline.set("sp" + i, "p" + i);
    }
    List<Object> results = pipeline.syncAndReturnAll();
    long end = System.currentTimeMillis();
    System.out.println("Pipelined@Sharing SET: " + ((end - start)/1000.0) + " seconds");

    sharding.disconnect();
}

七、分布式连接池同步调用

如果,你的分布式调用代码是运行在线程中,那么上面两个直连调用方式就不合适了,因为直连方式是非线程安全的,这个时候,你就必须选择连接池调用。

@Test
public void test7shardSimplePool() {
    List<JedisShardInfo> shards = Arrays.asList(
            new JedisShardInfo("localhost",6379),
            new JedisShardInfo("localhost",6380));

    ShardedJedisPool pool = new ShardedJedisPool(new JedisPoolConfig(), shards);

    ShardedJedis one = pool.getResource();

    long start = System.currentTimeMillis();
    for (int i = 0; i < 100000; i++) {
        String result = one.set("spn" + i, "n" + i);
    }
    long end = System.currentTimeMillis();
    pool.returnResource(one);
    System.out.println("Simple@Pool SET: " + ((end - start)/1000.0) + " seconds");

    pool.destroy();
}

上面是同步方式,当然还有异步方式。

八、分布式连接池异步调用

@Test
public void test8shardPipelinedPool() {
    List<JedisShardInfo> shards = Arrays.asList(
            new JedisShardInfo("localhost",6379),
            new JedisShardInfo("localhost",6380));

    ShardedJedisPool pool = new ShardedJedisPool(new JedisPoolConfig(), shards);

    ShardedJedis one = pool.getResource();

    ShardedJedisPipeline pipeline = one.pipelined();

    long start = System.currentTimeMillis();
    for (int i = 0; i < 100000; i++) {
        pipeline.set("sppn" + i, "n" + i);
    }
    List<Object> results = pipeline.syncAndReturnAll();
    long end = System.currentTimeMillis();
    pool.returnResource(one);
    System.out.println("Pipelined@Pool SET: " + ((end - start)/1000.0) + " seconds");
    pool.destroy();
}

九、需要注意的地方

事务和管道都是异步模式。在事务和管道中不能同步查询结果。比如下面两个调用,都是不允许的:

     Transaction tx = jedis.multi();
     for (int i = 0; i < 100000; i++) {
         tx.set("t" + i, "t" + i);
     }
     System.out.println(tx.get("t1000").get());  //不允许

     List<Object> results = tx.exec();

     …
     …

     Pipeline pipeline = jedis.pipelined();
     long start = System.currentTimeMillis();
     for (int i = 0; i < 100000; i++) {
         pipeline.set("p" + i, "p" + i);
     }
     System.out.println(pipeline.get("p1000").get()); //不允许

     List<Object> results = pipeline.syncAndReturnAll();

事务和管道都是异步的,个人感觉,在管道中再进行事务调用,没有必要,不如直接进行事务模式。

分布式中,连接池的性能比直连的性能略好(见后续测试部分)。

分布式调用中不支持事务。

因为事务是在服务器端实现,而在分布式中,每批次的调用对象都可能访问不同的机器,所以,没法进行事务。

十、测试

运行上面的代码,进行测试,其结果如下:

Simple SET: 5.227 seconds

Transaction SET: 0.5 seconds
Pipelined SET: 0.353 seconds
Pipelined transaction: 0.509 seconds

Simple@Sharing SET: 5.289 seconds
Pipelined@Sharing SET: 0.348 seconds

Simple@Pool SET: 5.039 seconds
Pipelined@Pool SET: 0.401 seconds

另外,经测试分布式中用到的机器越多,调用会越慢。上面是2片,下面是5片:

Simple@Sharing SET: 5.494 seconds
Pipelined@Sharing SET: 0.51 seconds
Simple@Pool SET: 5.223 seconds
Pipelined@Pool SET: 0.518 seconds

下面是10片:

Simple@Sharing SET: 5.9 seconds
Pipelined@Sharing SET: 0.794 seconds
Simple@Pool SET: 5.624 seconds
Pipelined@Pool SET: 0.762 seconds

下面是100片:

Simple@Sharing SET: 14.055 seconds
Pipelined@Sharing SET: 8.185 seconds
Simple@Pool SET: 13.29 seconds
Pipelined@Pool SET: 7.767 seconds

分布式中,连接池方式调用不但线程安全外,根据上面的测试数据,也可以看出连接池比直连的效率更好。

十一、完整的测试代码

package com.example.nosqlclient;

import java.util.Arrays;
import java.util.List;

import org.junit.AfterClass;
import org.junit.BeforeClass;
import org.junit.Test;

import redis.clients.jedis.Jedis;
import redis.clients.jedis.JedisPoolConfig;
import redis.clients.jedis.JedisShardInfo;
import redis.clients.jedis.Pipeline;
import redis.clients.jedis.ShardedJedis;
import redis.clients.jedis.ShardedJedisPipeline;
import redis.clients.jedis.ShardedJedisPool;
import redis.clients.jedis.Transaction;

import org.junit.FixMethodOrder;
import org.junit.runners.MethodSorters;

@FixMethodOrder(MethodSorters.NAME_ASCENDING)
public class TestJedis {

    private static Jedis jedis;
    private static ShardedJedis sharding;
    private static ShardedJedisPool pool;

    @BeforeClass
    public static void setUpBeforeClass() throws Exception {
        List<JedisShardInfo> shards = Arrays.asList(
                new JedisShardInfo("localhost",6379),
                new JedisShardInfo("localhost",6379)); //使用相同的ip:port,仅作测试


        jedis = new Jedis("localhost"); 
        sharding = new ShardedJedis(shards);

        pool = new ShardedJedisPool(new JedisPoolConfig(), shards);
    }

    @AfterClass
    public static void tearDownAfterClass() throws Exception {
        jedis.disconnect();
        sharding.disconnect();
        pool.destroy();
    }

    @Test
    public void test1Normal() {
        long start = System.currentTimeMillis();
        for (int i = 0; i < 100000; i++) {
            String result = jedis.set("n" + i, "n" + i);
        }
        long end = System.currentTimeMillis();
        System.out.println("Simple SET: " + ((end - start)/1000.0) + " seconds");
    }

    @Test
    public void test2Trans() {
        long start = System.currentTimeMillis();
        Transaction tx = jedis.multi();
        for (int i = 0; i < 100000; i++) {
            tx.set("t" + i, "t" + i);
        }
        //System.out.println(tx.get("t1000").get());

        List<Object> results = tx.exec();
        long end = System.currentTimeMillis();
        System.out.println("Transaction SET: " + ((end - start)/1000.0) + " seconds");
    }

    @Test
    public void test3Pipelined() {
        Pipeline pipeline = jedis.pipelined();
        long start = System.currentTimeMillis();
        for (int i = 0; i < 100000; i++) {
            pipeline.set("p" + i, "p" + i);
        }
        //System.out.println(pipeline.get("p1000").get());
        List<Object> results = pipeline.syncAndReturnAll();
        long end = System.currentTimeMillis();
        System.out.println("Pipelined SET: " + ((end - start)/1000.0) + " seconds");
    }

    @Test
    public void test4combPipelineTrans() {
        long start = System.currentTimeMillis();
        Pipeline pipeline = jedis.pipelined();
        pipeline.multi();
        for (int i = 0; i < 100000; i++) {
            pipeline.set("" + i, "" + i);
        }
        pipeline.exec();
        List<Object> results = pipeline.syncAndReturnAll();
        long end = System.currentTimeMillis();
        System.out.println("Pipelined transaction: " + ((end - start)/1000.0) + " seconds");
    }

    @Test
    public void test5shardNormal() {
        long start = System.currentTimeMillis();
        for (int i = 0; i < 100000; i++) {
            String result = sharding.set("sn" + i, "n" + i);
        }
        long end = System.currentTimeMillis();
        System.out.println("Simple@Sharing SET: " + ((end - start)/1000.0) + " seconds");
    }

    @Test
    public void test6shardpipelined() {
        ShardedJedisPipeline pipeline = sharding.pipelined();
        long start = System.currentTimeMillis();
        for (int i = 0; i < 100000; i++) {
            pipeline.set("sp" + i, "p" + i);
        }
        List<Object> results = pipeline.syncAndReturnAll();
        long end = System.currentTimeMillis();
        System.out.println("Pipelined@Sharing SET: " + ((end - start)/1000.0) + " seconds");
    }

    @Test
    public void test7shardSimplePool() {
        ShardedJedis one = pool.getResource();

        long start = System.currentTimeMillis();
        for (int i = 0; i < 100000; i++) {
            String result = one.set("spn" + i, "n" + i);
        }
        long end = System.currentTimeMillis();
        pool.returnResource(one);
        System.out.println("Simple@Pool SET: " + ((end - start)/1000.0) + " seconds");
    }

    @Test
    public void test8shardPipelinedPool() {
        ShardedJedis one = pool.getResource();

        ShardedJedisPipeline pipeline = one.pipelined();

        long start = System.currentTimeMillis();
        for (int i = 0; i < 100000; i++) {
            pipeline.set("sppn" + i, "n" + i);
        }
        List<Object> results = pipeline.syncAndReturnAll();
        long end = System.currentTimeMillis();
        pool.returnResource(one);
        System.out.println("Pipelined@Pool SET: " + ((end - start)/1000.0) + " seconds");
    }
}


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