阅读目录
- 一、普通同步方式
- 二、事务方式(Transactions)
- 三、管道(Pipelining)
- 四、管道中调用事务
- 五、分布式直连同步调用
- 六、分布式直连异步调用
- 七、分布式连接池同步调用
- 八、分布式连接池异步调用
- 九、需要注意的地方
- 十、测试
- 十一、完整的测试代码
- jedis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，
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@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：
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@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
long
end = System.currentTimeMillis();
System.out.println(
"Transaction SET: "
+ ((end - start)/
1000.0
) +
" seconds"
);
jedis.disconnect();
}
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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：
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@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
long
end = System.currentTimeMillis();
System.out.println(
"Pipelined SET: "
+ ((end - start)/
1000.0
) +
" seconds"
);
jedis.disconnect();
}
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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：
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@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
long
end = System.currentTimeMillis();
System.out.println(
"Pipelined transaction: "
+ ((end - start)/
1000.0
) +
" seconds"
);
jedis.disconnect();
}
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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
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@Test
public
void
test5shardNormal() {
List
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();
}
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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
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@Test
public
void
test6shardpipelined() {
List
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
long
end = System.currentTimeMillis();
System.out.println(
"Pipelined@Sharing SET: "
+ ((end - start)/
1000.0
) +
" seconds"
);
sharding.disconnect();
}
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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。
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@Test
public
void
test7shardSimplePool() {
List
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();
}
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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
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@Test
public
void
test8shardPipelinedPool() {
List
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
long
end = System.currentTimeMillis();
pool.returnResource(one);
System.out.println(
"Pipelined@Pool SET: "
+ ((end - start)/
1000.0
) +
" seconds"
);
pool.destroy();
}
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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：
12345678910111213141516171819Transaction tx = jedis.multi();for(inti =0; i <100000; i++) {tx.set("t"+ i,"t"+ i);}System.out.println(tx.get("t1000").get());//不允许List……Pipeline pipeline = jedis.pipelined();longstart = System.currentTimeMillis();for(inti =0; i <100000; i++) {pipeline.set("p"+ i,"p"+ i);}System.out.println(pipeline.get("p1000").get());//不允许List -
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：
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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
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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：
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Simple
@Sharing
SET:
5.494
seconds
Pipelined
@Sharing
SET:
0.51
seconds
Simple
@Pool
SET:
5.223
seconds
Pipelined
@Pool
SET:
0.518
seconds
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下面是10片：
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Simple
@Sharing
SET:
5.9
seconds
Pipelined
@Sharing
SET:
0.794
seconds
Simple
@Pool
SET:
5.624
seconds
Pipelined
@Pool
SET:
0.762
seconds
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下面是100片：
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Simple
@Sharing
SET:
14.055
seconds
Pipelined
@Sharing
SET:
8.185
seconds
Simple
@Pool
SET:
13.29
seconds
Pipelined
@Pool
SET:
7.767
seconds
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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。
回到顶部
十一、完整的测试代码
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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
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
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
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
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
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
long
end = System.currentTimeMillis();
pool.returnResource(one);
System.out.println(
"Pipelined@Pool SET: "
+ ((end - start)/
1000.0
) +
" seconds"
);
}
}
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From: http://www.open-open.com/lib/view/open1410485827242.html