http://itindex.net/detail/50647-redis-java-客户端

isgood

redis是一个著名的key-value存储系统，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.bijian.study;

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;

@SuppressWarnings("unused")
@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("192.168.128.129", 6379), new JedisShardInfo("192.168.128.129",6379)); // 使用相同的ip:port,仅作测试

jedis = new Jedis("192.168.128.129");
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");
}
}
运行结果：

  

Simple SET: 24.316 seconds
Transaction SET: 2.641 seconds
Pipelined SET: 1.016 seconds
Pipelined transaction: 1.484 seconds
Simple@Sharing SET: 29.287 seconds
Pipelined@Sharing SET: 1.953 seconds
Simple@Pool SET: 31.537 seconds
Pipelined@Pool SET: 1.156 seconds
直接查看redis数据库：

[iyunv@localhost bin]# /usr/local/redis/bin/redis-cli
127.0.0.1:6379> dbsize
(integer) 800000
127.0.0.1:6379>


PS：如上实例是基于jedis-2.1.0.jar、commons-pool-1.6.jar、junit-4.11.jar、hamcrest-core-1.3.jar运行的。

http://itindex.net/detail/50647-redis-java-客户端