来源: http://blog.fens.me/nodejs-core-cluster/
从零开始nodejs系列文章,将介绍如何利Javascript做为服务端脚本,通过Nodejs框架web开发。Nodejs框架是基于V8的引擎,是目前速度最快的Javascript引擎。chrome浏览器就基于V8,同时打开20-30个网页都很流畅。Nodejs标准的web开发框架Express,可以帮助我们迅速建立web站点,比起PHP的开发效率更高,而且学习曲线更低。非常适合小型网站,个性化网站,我们自己的Geek网站!!
关于作者
- 张丹(Conan), 程序员Java,R,PHP,Javascript
- weibo:@Conan_Z
- blog: http://blog.fens.me
- email: bsspirit@gmail.com
转载请注明出处:
http://blog.fens.me/nodejs-core-cluster/
前言
大家都知道nodejs是一个单进程单线程的服务器引擎,不管有多么的强大硬件,只能利用到单个CPU进行计算。所以,有人开发了第三方的cluster,让node可以利用多核CPU实现并行。
随着nodejs的发展,让nodejs上生产环境,就必须是支持多进程多核处理!在V0.6.0版本,Nodejs内置了cluster的特性。自此,Nodejs终于可以作为一个独立的应用开发解决方案,映入大家眼帘了。
目录
- cluster介绍
- cluster的简单使用
- cluster的工作原理
- cluster的API
- master和worker的通信
- 用cluster实现负载均衡(Load Balance) — win7失败
- 用cluster实现负载均衡(Load Balance) — ubuntu成功
- cluster负载均衡策略的测试
1. cluster介绍
cluster是一个nodejs内置的模块,用于nodejs多核处理。cluster模块,可以帮助我们简化多进程并行化程序的开发难度,轻松构建一个用于负载均衡的集群。
2. cluster的简单使用
我的系统环境
- win7 64bit
- Nodejs:v0.10.5
- Npm:1.2.19
在win的环境中,我们通过cluster启动多核的node提供web服务。
新建工程目录:
~ D:\workspace\javascript>mkdir nodejs-cluster && cd nodejs-cluster
新建文件:app.js
~ vi app.js
var cluster = require('cluster');
var http = require('http');
var numCPUs = require('os').cpus().length;
if (cluster.isMaster) {
console.log("master start...");
// Fork workers.
for (var i = 0; i < numCPUs; i++) {
cluster.fork();
}
cluster.on('listening',function(worker,address){
console.log('listening: worker ' + worker.process.pid +', Address: '+address.address+":"+address.port);
});
cluster.on('exit', function(worker, code, signal) {
console.log('worker ' + worker.process.pid + ' died');
});
} else {
http.createServer(function(req, res) {
res.writeHead(200);
res.end("hello world\n");
}).listen(0);
}
在控制台启动node程序
~ D:\workspace\javascript\nodejs-cluster>node app.js
master start...
listening: worker 2368, Address: 0.0.0.0:57132
listening: worker 1880, Address: 0.0.0.0:57132
listening: worker 1384, Address: 0.0.0.0:57132
listening: worker 1652, Address: 0.0.0.0:57132
master是总控节点,worker是运行节点。然后根据CPU的数量,启动worker。我本地是双核双通道的CPU,所以被检测为4核,启动了4个worker。
3. cluster的工作原理
每个worker进程通过使用child_process.fork()函数,基于IPC(Inter-Process Communication,进程间通信),实现与master进程间通信。
当worker使用server.listen(...)函数时 ,将参数序列传递给master进程。如果master进程已经匹配workers,会将传递句柄给工人。如果master没有匹配好worker,那么会创建一个worker,再传递并句柄传递给worker。
在边界条件,有3个有趣的行为:
注:下面server.listen(),是对底层“http.Server-->net.Server”类的调用。
- 1. server.listen({fd: 7}):在master和worker通信过程,通过传递文件,master会监听“文件描述为7”,而不是传递“文件描述为7”的引用。
- 2. server.listen(handle):master和worker通信过程,通过handle函数进行通信,而不用进程联系
- 3. server.listen(0):在master和worker通信过程,集群中的worker会打开一个随机端口共用,通过socket通信,像上例中的57132
当多个进程都在 accept() 同样的资源的时候,操作系统的负载均衡非常高效。Node.js没有路由逻辑,worker之间没有共享状态。所以,程序要设计得简单一些,比如基于内存的session。
因为workers都是独力运行的,根据程序的需要,它们可以被独立删除或者重启,worker并不相互影响。只要还有workers存活,则master将继续接收连接。Node不会自动维护workers的数目。我们可以建立自己的连接池。
4. cluster的API
官网地址:http://nodejs.org/api/cluster.html#cluster_cluster
cluster对象
cluster的各种属性和函数
- cluster.setttings:配置集群参数对象
- cluster.isMaster:判断是不是master节点
- cluster.isWorker:判断是不是worker节点
- Event: 'fork': 监听创建worker进程事件
- Event: 'online': 监听worker创建成功事件
- Event: 'listening': 监听worker向master状态事件
- Event: 'disconnect': 监听worker断线事件
- Event: 'exit': 监听worker退出事件
- Event: 'setup': 监听setupMaster事件
- cluster.setupMaster([settings]): 设置集群参数
- cluster.fork([env]): 创建worker进程
- cluster.disconnect([callback]): 关闭worket进程
- cluster.worker: 获得当前的worker对象
- cluster.workers: 获得集群中所有存活的worker对象
worker对象
worker的各种属性和函数:可以通过cluster.workers, cluster.worket获得。
- worker.id: 进程ID号
- worker.process: ChildProcess对象
- worker.suicide: 在disconnect()后,判断worker是否自杀
- worker.send(message, [sendHandle]): master给worker发送消息。注:worker给发master发送消息要用process.send(message)
- worker.kill([signal='SIGTERM']): 杀死指定的worker,别名destory()
- worker.disconnect(): 断开worker连接,让worker自杀
- Event: 'message': 监听master和worker的message事件
- Event: 'online': 监听指定的worker创建成功事件
- Event: 'listening': 监听master向worker状态事件
- Event: 'disconnect': 监听worker断线事件
- Event: 'exit': 监听worker退出事件
5. master和worker的通信
实现cluster的API,让master和worker相互通信。
新建文件: cluster.js
~ vi cluster.js
var cluster = require('cluster');
var http = require('http');
var numCPUs = require('os').cpus().length;
if (cluster.isMaster) {
console.log('[master] ' + "start master...");
for (var i = 0; i < numCPUs; i++) {
var wk = cluster.fork();
wk.send('[master] ' + 'hi worker' + wk.id);
}
cluster.on('fork', function (worker) {
console.log('[master] ' + 'fork: worker' + worker.id);
});
cluster.on('online', function (worker) {
console.log('[master] ' + 'online: worker' + worker.id);
});
cluster.on('listening', function (worker, address) {
console.log('[master] ' + 'listening: worker' + worker.id + ',pid:' + worker.process.pid + ', Address:' + address.address + ":" + address.port);
});
cluster.on('disconnect', function (worker) {
console.log('[master] ' + 'disconnect: worker' + worker.id);
});
cluster.on('exit', function (worker, code, signal) {
console.log('[master] ' + 'exit worker' + worker.id + ' died');
});
function eachWorker(callback) {
for (var id in cluster.workers) {
callback(cluster.workers[id]);
}
}
setTimeout(function () {
eachWorker(function (worker) {
worker.send('[master] ' + 'send message to worker' + worker.id);
});
}, 3000);
Object.keys(cluster.workers).forEach(function(id) {
cluster.workers[id].on('message', function(msg){
console.log('[master] ' + 'message ' + msg);
});
});
} else if (cluster.isWorker) {
console.log('[worker] ' + "start worker ..." + cluster.worker.id);
process.on('message', function(msg) {
console.log('[worker] '+msg);
process.send('[worker] worker'+cluster.worker.id+' received!');
});
http.createServer(function (req, res) {
res.writeHead(200, {"content-type": "text/html"});
res.end('worker'+cluster.worker.id+',PID:'+process.pid);
}).listen(3000);
}
控制台日志:
~ D:\workspace\javascript\nodejs-cluster>node cluster.js
[master] start master...
[worker] start worker ...1
[worker] [master] hi worker1
[worker] start worker ...2
[worker] [master] hi worker2
[master] fork: worker1
[master] fork: worker2
[master] fork: worker3
[master] fork: worker4
[master] online: worker1
[master] online: worker2
[master] message [worker] worker1 received!
[master] message [worker] worker2 received!
[master] listening: worker1,pid:6068, Address:0.0.0.0:3000
[master] listening: worker2,pid:1408, Address:0.0.0.0:3000
[master] online: worker3
[worker] start worker ...3
[worker] [master] hi worker3
[master] message [worker] worker3 received!
[master] listening: worker3,pid:3428, Address:0.0.0.0:3000
[master] online: worker4
[worker] start worker ...4
[worker] [master] hi worker4
[master] message [worker] worker4 received!
[master] listening: worker4,pid:6872, Address:0.0.0.0:3000
[worker] [master] send message to worker1
[worker] [master] send message to worker2
[worker] [master] send message to worker3
[worker] [master] send message to worker4
[master] message [worker] worker1 received!
[master] message [worker] worker2 received!
[master] message [worker] worker3 received!
[master] message [worker] worker4 received!
6. 用cluster实现负载均衡(Load Balance) -- win7失败
新建文件: server.js
~ vi server.js
var cluster = require('cluster');
var http = require('http');
var numCPUs = require('os').cpus().length;
if (cluster.isMaster) {
console.log('[master] ' + "start master...");
for (var i = 0; i < numCPUs; i++) {
cluster.fork();
}
cluster.on('listening', function (worker, address) {
console.log('[master] ' + 'listening: worker' + worker.id + ',pid:' + worker.process.pid + ', Address:' + address.address + ":" + address.port);
});
} else if (cluster.isWorker) {
console.log('[worker] ' + "start worker ..." + cluster.worker.id);
http.createServer(function (req, res) {
console.log('worker'+cluster.worker.id);
res.end('worker'+cluster.worker.id+',PID:'+process.pid);
}).listen(3000);
}
启动服务器:
~ D:\workspace\javascript\nodejs-cluster>node server.js
[master] start master...
[worker] start worker ...1
[worker] start worker ...2
[master] listening: worker1,pid:1536, Address:0.0.0.0:3000
[master] listening: worker2,pid:5920, Address:0.0.0.0:3000
[worker] start worker ...3
[master] listening: worker3,pid:7156, Address:0.0.0.0:3000
[worker] start worker ...4
[master] listening: worker4,pid:2868, Address:0.0.0.0:3000
worker4
worker4
worker4
worker4
worker4
worker4
worker4
worker4
用curl工具访问
C:\Users\Administrator>curl localhost:3000
worker4,PID:2868
C:\Users\Administrator>curl localhost:3000
worker4,PID:2868
C:\Users\Administrator>curl localhost:3000
worker4,PID:2868
C:\Users\Administrator>curl localhost:3000
worker4,PID:2868
C:\Users\Administrator>curl localhost:3000
worker4,PID:2868
C:\Users\Administrator>curl localhost:3000
worker4,PID:2868
C:\Users\Administrator>curl localhost:3000
worker4,PID:2868
C:\Users\Administrator>curl localhost:3000
worker4,PID:2868
我们发现了cluster在win中的bug,只用到worker4。果断切换到Linux测试。
7. 用cluster实现负载均衡(Load Balance) -- ubuntu成功
Linux的系统环境
- Linux: Ubuntu 12.04.2 64bit Server
- Node: v0.11.2
- Npm: 1.2.21
构建项目:不多解释
~ cd :/home/conan/nodejs/
~ mkdir nodejs-cluster && cd nodejs-cluster
~ vi server.js
var cluster = require('cluster');
var http = require('http');
var numCPUs = require('os').cpus().length;
if (cluster.isMaster) {
console.log('[master] ' + "start master...");
for (var i = 0; i < numCPUs; i++) {
cluster.fork();
}
cluster.on('listening', function (worker, address) {
console.log('[master] ' + 'listening: worker' + worker.id + ',pid:' + worker.process.pid + ', Address:' + address.address + ":" + address.port);
});
} else if (cluster.isWorker) {
console.log('[worker] ' + "start worker ..." + cluster.worker.id);
http.createServer(function (req, res) {
console.log('worker'+cluster.worker.id);
res.end('worker'+cluster.worker.id+',PID:'+process.pid);
}).listen(3000);
}
启动服务器
conan@conan-deskop:~/nodejs/nodejs-cluster$ node server.js
[master] start master...
[worker] start worker ...1
[master] listening: worker1,pid:2925, Address:0.0.0.0:3000
[worker] start worker ...3
[master] listening: worker3,pid:2931, Address:0.0.0.0:3000
[worker] start worker ...4
[master] listening: worker4,pid:2932, Address:0.0.0.0:3000
[worker] start worker ...2
[master] listening: worker2,pid:2930, Address:0.0.0.0:3000
worker4
worker2
worker1
worker3
worker4
worker2
worker1
用curl工具访问
C:\Users\Administrator>curl 192.168.1.20:3000
worker4,PID:2932
C:\Users\Administrator>curl 192.168.1.20:3000
worker2,PID:2930
C:\Users\Administrator>curl 192.168.1.20:3000
worker1,PID:2925
C:\Users\Administrator>curl 192.168.1.20:3000
worker3,PID:2931
C:\Users\Administrator>curl 192.168.1.20:3000
worker4,PID:2932
C:\Users\Administrator>curl 192.168.1.20:3000
worker2,PID:2930
C:\Users\Administrator>curl 192.168.1.20:3000
worker1,PID:2925
在Linux环境中,cluster是运行正确的!!!
8. cluster负载均衡策略的测试
我们在Linux下面,完成测试,用过测试软件: siege
安装siege
~ sudo apt-get install siege
启动node cluster
~ node server.js > server.log
运行siege启动命令,每秒50个并发请求。
~ sudo siege -c 50 http://localhost:3000
HTTP/1.1 200 0.00 secs: 16 bytes ==> /
HTTP/1.1 200 0.00 secs: 16 bytes ==> /
HTTP/1.1 200 0.00 secs: 16 bytes ==> /
HTTP/1.1 200 0.01 secs: 16 bytes ==> /
HTTP/1.1 200 0.00 secs: 16 bytes ==> /
HTTP/1.1 200 0.00 secs: 16 bytes ==> /
HTTP/1.1 200 0.00 secs: 16 bytes ==> /
HTTP/1.1 200 0.01 secs: 16 bytes ==> /
HTTP/1.1 200 0.00 secs: 16 bytes ==> /
HTTP/1.1 200 0.00 secs: 16 bytes ==> /
HTTP/1.1 200 0.00 secs: 16 bytes ==> /
HTTP/1.1 200 0.02 secs: 16 bytes ==> /
HTTP/1.1 200 0.00 secs: 16 bytes ==> /
HTTP/1.1 200 0.02 secs: 16 bytes ==> /
HTTP/1.1 200 0.01 secs: 16 bytes ==> /
HTTP/1.1 200 0.01 secs: 16 bytes ==> /
.....
^C
Lifting the server siege... done. Transactions: 3760 hits
Availability: 100.00 %
Elapsed time: 39.66 secs
Data transferred: 0.06 MB
Response time: 0.01 secs
Transaction rate: 94.81 trans/sec
Throughput: 0.00 MB/sec
Concurrency: 1.24
Successful transactions: 3760
Failed transactions: 0
Longest transaction: 0.20
Shortest transaction: 0.00
FILE: /var/siege.log
You can disable this annoying message by editing
the .siegerc file in your home directory; change
the directive 'show-logfile' to false.
我们统计结果,执行3760次请求,消耗39.66秒,每秒处理94.81次请求。
查看server.log文件,
~ ls -l
total 64
-rw-rw-r-- 1 conan conan 756 9月 28 15:48 server.js
-rw-rw-r-- 1 conan conan 50313 9月 28 16:26 server.log
~ tail server.log
worker4
worker1
worker2
worker4
worker1
worker2
worker4
worker3
worker2
worker1
最后,用R语言分析一下:server.log
~ R
> df<-read.table(file="server.log",skip=9,header=FALSE)
> summary(df)
V1
worker1:1559
worker2:1579
worker3:1570
worker4:1535
我们看到,请求被分配到worker数据量相当。所以,cluster的负载均衡的策略,应该是随机分配的。
好了,我们又学了一个很有用的技能!利用cluster可以构建出多核应用,充分的利用多CPU带业的性能吧!!