在這里對jedis關(guān)于事務(wù)、管道和分布式的調(diào)用方式做一個(gè)簡單的介紹和對比：
一、普通同步方式
最簡單和基礎(chǔ)的調(diào)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(); }很簡單吧，每次set之后都可以返回結(jié)果，標(biāo)記是否成功。
二、事務(wù)方式(Transactions)
redis的事務(wù)很簡單，他主要目的是保障，一個(gè)client發(fā)起的事務(wù)中的命令可以連續(xù)的執(zhí)行，而中間不會(huì)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(); }我們調(diào)用jedis.watch(…)方法來監(jiān)控key，如果調(diào)用后key值發(fā)生變化，則整個(gè)事務(wù)會(huì)執(zhí)行失敗。另外，事務(wù)中某個(gè)操作失敗，并不會(huì)回滾其他操作。這一點(diǎn)需要注意。還有，我們可以使用discard()方法來取消事務(wù)。
三、管道(Pipelining)
有時(shí)，我們需要采用異步方式，一次發(fā)送多個(gè)指令，不同步等待其返回結(jié)果。這樣可以取得非常好的執(zhí)行效率。這就是管道，調(diào)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、管道中調(diào)用事務(wù)
就Jedis提供的方法而言，是可以做到在管道中使用事務(wù)，其代碼如下：
@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(); }但是經(jīng)測試（見本文后續(xù)部分），發(fā)現(xiàn)其效率和單獨(dú)使用事務(wù)差不多，甚至還略微差點(diǎn)。
五、分布式直連同步調(diào)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(); }這個(gè)是分布式直接連接，并且是同步調(diào)用，每步執(zhí)行都返回執(zhí)行結(jié)果。類似地，還有異步管道調(diào)用。
六、分布式直連異步調(diào)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、分布式連接池同步調(diào)用
如果，你的分布式調(diào)用代碼是運(yùn)行在線程中，那么上面兩個(gè)直連調(diào)用方式就不合適了，因?yàn)橹边B方式是非線程安全的，這個(gè)時(shí)候，你就必須選擇連接池調(diào)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，當(dāng)然還有異步方式。
八、分布式連接池異步調(diào)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
事務(wù)和管道都是異步模式。在事務(wù)和管道中不能同步查詢結(jié)果。比如下面兩個(gè)調(diào)用，都是不允許的：
Transaction tx = jedis.multi(); for (int i = 0; i < 100000; i++) { tx.set("t" + i, "t" + i); } System.out.println(tx.get("t1000").get()); //不允許 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()); //不允許 List<Object> results = pipeline.syncAndReturnAll();事務(wù)和管道都是異步的，個(gè)人感覺，在管道中再進(jìn)行事務(wù)調(diào)用，沒有必要，不如直接進(jìn)行事務(wù)模式。
分布式中，連接池的性能比直連的性能略好(見后續(xù)測試部分)。
分布式調(diào)用中不支持事務(wù)。
因?yàn)槭聞?wù)是在服務(wù)器端實(shí)現(xiàn)，而在分布式中，每批次的調(diào)用對象都可能訪問不同的機(jī)器，所以，沒法進(jìn)行事務(wù)。
十、測試
運(yùn)行上面的代碼，進(jìn)行測試，其結(jié)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，經(jīng)測試分布式中用到的機(jī)器越多，調(diào)用會(huì)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，連接池方式調(diào)用不但線程安全外，根據(jù)上面的測試數(shù)據(jù)，也可以看出連接池比直連的效率更好。
十一、完整的測試代碼
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,僅作測試 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"); } }