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:
[root@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。
文章来源:http://www.blogways.net/blog/2013/06/02/jedis-demo.html
相关推荐
前段时间细节的了解了Jedis的使用,Jedis是redis的java版本的客户端实现。 本文做个总结,主要分享如下内容: 【pipeline】【分布式的id生成器】【分布式锁【watch】【multi】】【redis分布式】 好了,一个一个来。 ...
一个java项目和两个web项目,实现dubbo的分布式接口和调用,配置了redispool池和jedis的调用,整个项目采用spring整合,aop记录日志;
SpringBoot集成Jedis框架-实现Redis调用; SpringBoot集成Lettuce框架-实现Redis调用; SpringBoot集成Redisson框架-实现Redis调用; 分布式服务框架Dubbo-基于注解配置的方式; 分布式服务框架Dubbo-基于XML配置的方式;...
│ Java面试题78:redis存储对象的方式.mp4 │ Java面试题79:redis数据淘汰机制.mp4 │ Java面试题80:java访问redis级redis集群?.mp4 │ Java面试题81:微信公众号分类和微信开发原理.mp4 │ Java面试题82:怎么...
tomcat8-redis-cluster概要 1.原理: 原理就是继承tomcat的manager接口,接管session的持久化...必须手动的调用session的setAttribute方法,才能同步到你的存储里面,因为分布式session的应用可能不在同一个jvm上面
tomcat7-redis-cluster概要 1.原理: 原理就是继承tomcat的manager接口,接管session的持久化...必须手动的调用session的setAttribute方法,才能同步到你的存储里面,因为分布式session的应用可能不在同一个jvm上面
SpringBoot集成Jedis框架-实现Redis调用; SpringBoot集成Lettuce框架-实现Redis调用; SpringBoot集成Redisson框架-实现Redis调用; Dubbo相关实例 分布式服务框架Dubbo-基于注解配置的方式; 分布式服务框架Dubbo-基于...
│ 06.jedis客户端在spring中的配置.avi │ 07.测试spring中的JedisClient.avi │ 08.缓存同步-服务发布.avi │ 09.后台调用缓存同步服务.avi │ 10.solr单机版安装.avi │ 11.中文分析器配置.avi │ 12.导入数据-...
redis存储jedis nginx路由web和admin服务器 http调用unirest supervisor进程监控 maven exec运行进程 自定义二进制协议 消息加密 |----------------------------| | nginx | |____________________________| |---...
大数据开发中常用组件封装zookeeper名字服务,配置管理,组员管理互斥锁,...esudf建立外部表mysqldruid 连接池canal 模拟主从复制,同步redisspring-redisjava-redis单机分布式锁 jedis.set(lockKey, requestId, SET_
-- Redis客户端 --> <groupId>redis.clients <artifactId>jedis ${jedis.version} <!-- solr客户端 --> <groupId>org.apache.solr <artifactId>solr-solrj ${solrj.version} ${...