A brief discussion on how Nodejs performs multi-threading processing
This article will introduce to you how Nodejs performs multi-threading processing. It has certain reference value. Friends in need can refer to it. I hope it will be helpful to everyone.
Threads à gogo is a native module of nodejs. Using this module can enable nodejs to have multi-thread processing capabilities. [Recommended learning: "nodejs Tutorial"]
Installation method
npm install threads_a_gogo
Download test source code
git clone http://github.com/xk/node-threads-a-gogo.git
Import module code
var tagg= require('threads_a_gogo');
API
tagg= require('threads_a_gogo') //生成tagg object var thread = tagg.create( /* no arguments */ ) //生成 thread object var thread_pool = tagg.createPool( numberOfThreads ) //生成 thread pool thread.load("boot.js").eval("boot()").emit("go").on("event", cb) //thread读取boot.js文件 执行boot(),发送event go,并且监听 event 事件 cb(err,result) thread_pool.load('path') //pool中的任意(.all 为全部)thread 读取path file pool.any.eval( program, cb ) //pool中的任意(.all 为全部)thread执行program
Why use multi-threading?
1. Parallel execution, no need to queue, fast.
2. Fairness, all threads have the same priority.
3. Make full use of resources and allow more CPUs to participate in task processing.
4. All threads share a storage address.
Example
Let’s do a simple test first, use the Fibonacci array to look at it, and add a multi-threaded node How powerful it is: (The test machine is 4CPU) Without the normal use of TAGG, asynchronous cannot help us deal with cpu-intensive tasks
function fibo (n) { return n > 1 ? fibo(n - 1) + fibo(n - 2) : 1; } var n=8 function back(){ if(!--n) return console.timeEnd('no thread'); } console.time('no thread'); process.nextTick(function(){ console.log(fibo (40)); back(); }) process.nextTick(function(){ console.log(fibo (40)); back(); }) process.nextTick(function(){ console.log(fibo (40)); back(); }) process.nextTick(function(){ console.log(fibo (40)); back(); }) process.nextTick(function(){ console.log(fibo (40)); back(); }) process.nextTick(function(){ console.log(fibo (40)); back(); }) process.nextTick(function(){ console.log(fibo (40)); back(); }) process.nextTick(function(){ console.log(fibo (40)); back(); })
We simulated 8 asynchronous behaviors for testing node v0.8.16 version, so process.nextTick is still an asynchronous method. Finally, our output result is:
165580141 165580141 165580141 165580141 165580141 165580141 165580141 165580141 no thread: 23346ms
Next, we use the TAGG module to test the same execution of 8 Fibonacci array calculations and see what the result is?
function fibo (n) { return n > 1 ? fibo(n - 1) + fibo(n - 2) : 1; } console.time('8 thread'); var numThreads= 8; //创建线程池,最大数为8 var threadPool= require('threads_a_gogo').createPool(numThreads).all.eval(fibo); //为线程池注册程序 var i=8; var cb = function(err,data){ //注册线程执行完毕的回调函数 console.log(data); if(!--i){ threadPool.destroy(); console.timeEnd('8 thread'); } } threadPool.any.eval('fibo(40)', cb); //开始向线程池中执行fibo(40)这个任务 threadPool.any.eval('fibo(40)', cb); threadPool.any.eval('fibo(40)', cb); threadPool.any.eval('fibo(40)', cb); threadPool.any.eval('fibo(40)', cb); threadPool.any.eval('fibo(40)', cb); threadPool.any.eval('fibo(40)', cb); threadPool.any.eval('fibo(40)', cb);
The most important result:
165580141 165580141 165580141 165580141 165580141 165580141 165580141 165580141 8 thread: 9510ms
Compared to the node that does not use the multi-threading model, after using the TAGG module, our test results on the 4CPU server are one step faster More than twice that.
The TAGG module has many other functions, such as event triggering, smooth exit, checking thread working status, etc. In short, the TAGG module injects new vitality into the node. node has been criticized for handling cpu-intensive tasks and has been properly solved. Even if you are not good at c code, you can easily write multi-threaded and truly non-blocking node program.
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