如何使用简单的Express应用程序使用Node.js集群？ [英] How do I use Node.js clusters with my simple Express app?
问题描述
- 我建立了一个简单的应用程序，从Redis DB中提取数据（50个项目），并将其放在localhost上。我做了一个ApacheBench（c = 100，n = 50000），我在双核T2080 @ 1.73GHz（我的6哟笔记本电脑）上得到了一个半体面的150个请求/秒，但是proc的使用非常令人失望显示：
— I built a simple app that pulls in data (50 items) from a Redis DB and throws it up at localhost. I did an ApacheBench (c = 100, n = 50000) and I'm getting a semi-decent 150 requests/sec on a dual-core T2080 @ 1.73GHz (my 6 y.o laptop), but the proc usage is very disappointing as shown:
只有一个核心被使用，这是根据Node的设计，但是我想我可以将我的请求/秒增加到〜300，甚至更多，如果我可以使用Node.js集群。我已经搞砸了很多，但是我无法弄清楚如何把这里给出的代码用于我的应用程序，如下所示：
Only one core is used, which is as per design in Node, but I think I can nearly double my requests/sec to ~300, maybe even more, if I can use Node.js clusters. I fiddled around quite a bit but I haven't been able to figure out how to put the code given here for use with my app which is listed below:
var
express = require( 'express' ),
app = express.createServer(),
redis = require( 'redis' ).createClient();
app.configure( function() {
app.set( 'view options', { layout: false } );
app.set( 'view engine', 'jade' );
app.set( 'views', __dirname + '/views' );
app.use( express.bodyParser() );
} );
function log( what ) { console.log( what ); }
app.get( '/', function( req, res ) {
redis.lrange( 'items', 0, 50, function( err, items ) {
if( err ) { log( err ); } else {
res.render( 'index', { items: items } );
}
});
});
app.listen( 8080 );
我也想强调，应用程序是I / O密集型（不是CPU密集型，已经做了类似 threads-a-gogo ，比群集更好的选择）
I also want to emphasize that the app is I/O intensive (not CPU-intensive, which would've made something like threads-a-gogo a better choice than clusters).
想了解一些帮助。
推荐答案
实际上，您的工作负载并不是真正的I / O绑定：由于基于玉石的动态页面生成的成本，它是CPU限制的。我不能猜测你的玉模板的复杂性，但即使使用简单的模板，生成HTML页面也很贵。
Actually, your workload is not really I/O bound: it is CPU bound due to the cost of jade-based dynamic page generation. I cannot guess the complexity of your jade template, but even with simple templates, generating HTML pages is expensive.
对于我的测试，我使用了这个模板：
For my tests I used this template:
html(lang="en")
head
title Example
body
h1 Jade - node template engine
#container
ul#users
each user in items
li User:#{user}
我在Redis中的项目键中添加了100个虚拟字符串。
I added 100 dummy strings to the items key in Redis.
在我的框上，我得到475 req /其中node.js CPU为100％（这意味着此双核心盒上的CPU占用率为50％）。我们来替换：
On my box, I get 475 req/s with node.js CPU at 100% (which means 50% CPU consumption on this dual core box). Let's replace:
res.render( 'index', { items: items } );
by：
res.send( '<html lang="en"><head><title>Example</title></head><body><h1>Jade - node template engine</h1><div id="container"><ul id="users"><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li><li>User:NOTHING</li></ul></div></body></html>' );
现在，基准测试的结果接近2700 req / s。因此，瓶颈显然是由于HTML页面的格式化。
Now, the result of the benchmark is close to 2700 req/s. So the bottleneck is clearly due to the formatting of the HTML page.
在这种情况下使用集群包是一个好主意，它是直接的。代码可以修改如下：
Using the cluster package in this situation is a good idea, and it is straightforward. The code can be modified as follows:
var cluster = require('cluster')
if ( cluster.isMaster ) {
for ( var i=0; i<2; ++i )
cluster.fork();
} else {
var
express = require( 'express' ),
app = express.createServer(),
redis = require( 'redis' ).createClient();
app.configure( function() {
app.set( 'view options', { layout: false } );
app.set( 'view engine', 'jade' );
app.set( 'views', __dirname + '/views' );
app.use( express.bodyParser() );
});
function log( what ) { console.log( what ); }
app.get( '/', function( req, res ) {
redis.lrange( 'items', 0, 50, function( err, items ) {
if( err ) { log( err ); } else {
res.render( 'index', { items: items } );
}
});
});
app.listen( 8080 );
}
现在，基准测试的结果接近750 req / s，100％ CPU消耗（与最初的475 req / s相比）。
Now the result of the benchmark is close to 750 req/s with 100 % CPU consumption (to be compared with the initial 475 req/s).
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