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"); } }