1 背景
由于股票撮合中,我们使用zset构建到价成交,故这里对rangebyscore命令进行原位压力测试
redis线程池如何定,为什么开10个disruptor消费线程(redis连接):
1)io密集型4核2(n+1);
2)从第2点本地压测结果看,10线程已80%满足最高qps;
3)disruptor太多线程不好
2 首先压一波本地
压测设备:mac 2016 12'
2.1 docker
redis-benchmark -h 127.0.0.1 -p 63790 -c 100 -n 10000 script load "redis.call('zrangebyscore','sh111111','3','9')"
java benchmark | java 代码 | redis命令行 | |
1 | 807 | 729 | 866 |
10 | 3115 | 3115 | 3187 |
50 | 4467 | 4235 | 4640 |
100 | 4375 | 4417 | 5238 |
500 | 5747 |
*java benchmark与java代码都存在从池拿连接的操作
2.2 native
redis-benchmark -h 127.0.0.1 -p 6379 -c 1 -n 10000 script load "redis.call('zrangebyscore','sh111111','3','9')"
java benchmark | java 代码 | redis命令行 | |
1 | 11729 | 6050 | 10131 |
10 | 28597 | 18653 | 21000 |
50 | 31943 | 29056 | 23584 |
100 | 29476 | 28438 | 24875 |
500 | 24937 |
那么我们看到局域网及docker的测试,可能经过网卡后,10线程qps为3k,这个值与官方宣称的10w相去甚远,所以我看下往上其它人的压测结果
3 其它参考:
3.1 openresty-redis在不同网络环境下QPS对比讲解
http://blog.sina.cn/dpool/blog/s/blog_6145ed810102vefe.html?from=groupmessage&isappinstalled=0
redis相对openresty网络环境redis(requests per second)openresty(requests per second)
本地52631.58
局域网3105.59 与我docker测试水平相当
公网(纽约节点)169.95
3.2 memcache、redis、tair性能对比测试报告
http://blog.sina.cn/dpool/blog/s/blog_6145ed810102vefe.html?from=groupmessage&isappinstalled=0
以单线程通过各缓存客户端get调用向服务端获取数据,比较10000操作所消耗的时间
redis 1k对象 1260qps
并发1000个线程通过缓存软件的客户get调用向服务端获取数据,每个线程完成10000次的操作
redis 1k对象 11430qps 这个数据比我测试的要大三倍
4 阿里云redis qps 10线程,4.7万qps
https://zhuanlan.zhihu.com/p/78034665?utm_source=wechat_session&utm_medium=social&utm_oi=1003056052560101376&from=singlemessage&isappinstalled=0&wechatShare=1&s_s_i=Nxnfuuur16PoKq5S8w%2Bv7CqmqZ5fwF2fxQZXH9O4%2FPM%3D&s_r=1
阿里云社区版
社区 标准版双副本 1g主从 redis5.0 号称8w qps(集群256分片2560w qps),企业版24w(集群6144w):https://help.aliyun.com/document_detail/26350.html
施压机 :4 vCPU 8 GiB (I/O优化)ecs.c6.xlarge 10Mbps (峰值)
5 后话,为什么redis 多线程客户端获得更大qps,大到什么程度
以一个例子说明,假设:
一次命令时间(borrow|return resource + Jedis执行命令(含网络) )的平均耗时约为1ms,一个连接的QPS大约是1000 业务期望的QPS是50000 那么理论上需要的资源池大小是50000 / 1000 = 50个。但事实上这是个理论值,还要考虑到要比理论值预留一些资源,通常来讲maxTotal可以比理论值大一些。
但这个值不是越大越好,一方面连接太多占用客户端和服务端资源,另一方面对于Redis这种高QPS的服务器,一个大命令的阻塞即使设置再大资源池仍然会无济于事。
https://cloud.tencent.com/developer/article/1425158
注意,redis多线程qps并不像理论的那样,多个线程qps=单个线程*线程数(有点像负载均衡),因为线程之间相互切换吞吐量相互制约,成非线性关系
6 性能监控:
参考1 https://www.cnblogs.com/cheyunhua/p/9068029.html 设置redis最大内存,类似于java内存的xmx
参考2 https://blog.csdn.net/z644041867/article/details/77965521 性能监控指标
redis-cli info | grep -w "connected_clients" |awk -F':' '{print $2}'
redis-cli info | grep -w "used_memory_rss_human" |awk -F':' '{print $2}' 类似于java内存jmx监控的commited和used
redis-cli info | grep -w "used_memory_peak_human" |awk -F':' '{print $2}'
redis-cli info | grep -w "instantaneous_ops_per_sec" |awk -F':' '{print $2}'
redis-benchmark -h 127.0.0.1 -p 6379 -c 1 -n 1000000 script load "redis.call('zrangebyscore','sh111111','3','9')"
^Cript load redis.call('zrangebyscore','sh111111','3','9'): 10026.05
JoycedeMacBook:redis-5.0.5 joyce$ redis-cli info | grep -w "instantaneous_ops_per_sec" |awk -F':' '{print $2}' 0 JoycedeMacBook:redis-5.0.5 joyce$ redis-cli info | grep -w "instantaneous_ops_per_sec" |awk -F':' '{print $2}' 9666 JoycedeMacBook:redis-5.0.5 joyce$ redis-cli info | grep -w "instantaneous_ops_per_sec" |awk -F':' '{print $2}' 9473 JoycedeMacBook:redis-5.0.5 joyce$ redis-cli info | grep -w "instantaneous_ops_per_sec" |awk -F':' '{print $2}' 10249 JoycedeMacBook:redis-5.0.5 joyce$ redis-cli info | grep -w "instantaneous_ops_per_sec" |awk -F':' '{print $2}' 10590 JoycedeMacBook:redis-5.0.5 joyce$ redis-cli info | grep -w "instantaneous_ops_per_sec" |awk -F':' '{print $2}' 10486 JoycedeMacBook:redis-5.0.5 joyce$ redis-cli info | grep -w "instantaneous_ops_per_sec" |awk -F':' '{print $2}' 10421 JoycedeMacBook:redis-5.0.5 joyce$ redis-cli info | grep -w "instantaneous_ops_per_sec" |awk -F':' '{print $2}' 10450 JoycedeMacBook:redis-5.0.5 joyce$ redis-cli info | grep -w "instantaneous_ops_per_sec" |awk -F':' '{print $2}' 10673 JoycedeMacBook:redis-5.0.5 joyce$ redis-cli info | grep -w "instantaneous_ops_per_sec" |awk -F':' '{print $2}' 10707 JoycedeMacBook:redis-5.0.5 joyce$ redis-cli info | grep -w "instantaneous_ops_per_sec" |awk -F':' '{print $2}' 10655 JoycedeMacBook:redis-5.0.5 joyce$ redis-cli info | grep -w "instantaneous_ops_per_sec" |awk -F':' '{print $2}' 10530 JoycedeMacBook:redis-5.0.5 joyce$ redis-cli info | grep -w "instantaneous_ops_per_sec" |awk -F':' '{print $2}' 10570 JoycedeMacBook:redis-5.0.5 joyce$ redis-cli info | grep -w "instantaneous_ops_per_sec" |awk -F':' '{print $2}' 10396 JoycedeMacBook:redis-5.0.5 joyce$ redis-cli info | grep -w "instantaneous_ops_per_sec" |awk -F':' '{print $2}' 9595 JoycedeMacBook:redis-5.0.5 joyce$ redis-cli info | grep -w "instantaneous_ops_per_sec" |awk -F':' '{print $2}' 9010 JoycedeMacBook:redis-5.0.5 joyce$ redis-cli info | grep -w "instantaneous_ops_per_sec" |awk -F':' '{print $2}' 9414
7 测试代码:
package redis; import com.alibaba.fastjson.JSON; import com.alibaba.fastjson.JSONObject; import com.google.protobuf.InvalidProtocolBufferException; import ip.IpPool; import org.apache.commons.pool2.impl.GenericObjectPool; import org.apache.commons.pool2.impl.GenericObjectPoolConfig; import org.openjdk.jmh.annotations.*; import org.openjdk.jmh.runner.Runner; import org.openjdk.jmh.runner.RunnerException; import org.openjdk.jmh.runner.options.Options; import org.openjdk.jmh.runner.options.OptionsBuilder; import org.redisson.Redisson; import org.redisson.api.RBucket; import org.redisson.api.RedissonClient; import org.redisson.config.Config; import redis.clients.jedis.Jedis; import redis.clients.jedis.JedisPool; import redis.clients.jedis.JedisPoolConfig; import serial.MyBaseBean; import serial.MyBaseProto; import java.util.Set; import java.util.concurrent.CountDownLatch; import java.util.concurrent.TimeUnit; /** * Created by joyce on 2019/10/24. */ @BenchmarkMode(Mode.Throughput)//基准测试类型 @OutputTimeUnit(TimeUnit.SECONDS)//基准测试结果的时间类型 @Threads(10)//测试线程数量(IO密集) @State(Scope.Thread)//该状态为每个线程独享 public class YaliRedis { private static JedisPool jedisPool; private static final int threadCount = 10; @Setup public static void init() { JedisPoolConfig config = new JedisPoolConfig(); config.setMaxTotal(800); config.setMaxIdle(800); jedisPool = new JedisPool(config,"localhost",63790,2000,"test"); // Jedis jedis = jedisPool.getResource(); // String test = jedis.get("testkey"); // System.out.println(test); // Set<String> set = jedis.zrangeByScore("sh111111", 3,9); // System.out.println(set.size()); // jedis.close(); } @TearDown public static void destroy() { jedisPool.close(); } public static void main(String[] args) throws Exception { // initData(); if(false) { Options opt = new OptionsBuilder().include(YaliRedis.class.getSimpleName()).forks(1).warmupIterations(1) .measurementIterations(3).build(); new Runner(opt).run(); } else { init(); final int perThread = 10000; CountDownLatch countDownLatchMain = new CountDownLatch(threadCount); CountDownLatch countDownLatchSub = new CountDownLatch(1); for(int i=0; i<threadCount; ++i) { new Thread(new Runnable() { @Override public void run() { try { countDownLatchSub.await(); Set<String> set = null; for(int j=0; j<perThread; ++j) set = testZSet(); System.out.println(set.size()); } catch (Exception e) { e.printStackTrace(); } finally { countDownLatchMain.countDown(); } } }).start(); } long st = (System.currentTimeMillis()); countDownLatchSub.countDown(); countDownLatchMain.await(); System.out.println(System.currentTimeMillis() - st); System.out.println(threadCount * perThread * 1000 / (System.currentTimeMillis() - st)); } } @Benchmark public static Set<String> testZSet() { Jedis jedis = null; jedis = jedisPool.getResource(); Set<String> set = jedis.zrangeByScore("sh111111", 3,9); jedis.close(); return set; } // @Benchmark public static void test() { Jedis jedis = null; jedis = jedisPool.getResource(); jedis.get("testkey"); jedis.close(); } // @Benchmark public static void testJson() { Jedis jedis = null; jedis = jedisPool.getResource(); String xx = jedis.get("testjson"); JSONObject userJson = JSONObject.parseObject(xx); MyBaseBean user = JSON.toJavaObject(userJson,MyBaseBean.class); jedis.close(); } // @Benchmark public static void testPb() { Jedis jedis = null; jedis = jedisPool.getResource(); byte [] bytes = jedis.get("testpb".getBytes()); try { MyBaseProto.BaseProto baseProto = MyBaseProto.BaseProto.parseFrom(bytes); } catch (InvalidProtocolBufferException e) { e.printStackTrace(); } jedis.close(); } public static void initData() { Jedis jedis = new Jedis("localhost", 63790); jedis.auth("test"); for(int i=1; i<=9; ++i) { jedis.zadd("sh111111", i, String.valueOf(i*100)); } } }
8 备用:
1 redis-benchmark. + ( java bench jedis ) 1)redis 本机 redis-benchmark -h 127.0.0.1 -p 6379 -c 1000 -n 10000 script load "redis.call('zrangebyscore','sh111111','3','9)" 1 th 10000 (11500) 50 th 24000 (33000) 100 th 25000 (30000) 500 th 26000 (20000) 1000 th 24000 2)docker redis-benchmark -h 127.0.0.1 -p 63790 -c 100 -n 10000 script load "redis.call('zrangebyscore','sh111111','3','9)" 1 th 640 (700) 50 th 3900 (3300) 100 th 4400 (3800) 500 th 6000 (4500). 约80% 1000 th 5300