IDEA激活码
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v8
Does a Javascript closure retain the entire parent lexical environment or only the subset of values the closure references? [duplicate]
问题 This question already has answers here : About closure, LexicalEnvironment and GC (3 answers) Closed 1 year ago . Consider the following example: function makeFunction() { let x = 3; let s = "giant string, 100 MB in size"; return () => { console.log(x); }; } // Are both x and s held in memory here // or only x, because only x was referred to by the closure returned // from makeFunction? let made = makeFunction(); // Suppose there are no further usages of makeFunction after this point // Let's
Does a Javascript closure retain the entire parent lexical environment or only the subset of values the closure references? [duplicate]
问题 This question already has answers here : About closure, LexicalEnvironment and GC (3 answers) Closed 1 year ago . Consider the following example: function makeFunction() { let x = 3; let s = "giant string, 100 MB in size"; return () => { console.log(x); }; } // Are both x and s held in memory here // or only x, because only x was referred to by the closure returned // from makeFunction? let made = makeFunction(); // Suppose there are no further usages of makeFunction after this point // Let's
How to scrape JavaScript rendered Website by R?
问题 Just wanna ask if there is any good approach to scrape the website below? https://list.jd.com/list.html?cat=737,794,798&page=1&sort=sort_rank_asc&trans=1&JL=6_0_0#J_main Basically I want to get the name and price of all products However, the price info is stored in some JQuery scripts Is Selenium the only solution? Thought of using V8 / Jsonlite, but it seems that they are not applicable. It'd be great if you can offer some alternatives in R. (Access to exe files is blocked in my computer, I
How does V8 optimise the creation of very large arrays?
问题 Recently, I had to work on optimising a task that involved the creation of really large arrays (~ 10⁸ elements). I tested a few different methods, and, according to jsperf, the following option seemed to be the fastest. var max = 10000000; var arr = new Array(max); for (let i = 0; i < max; i++) { arr[i] = true; } Which was ~ 85% faster than var max = 10000000; var arr = []; for (let i = 0; i < max; i++) { arr.push(true); } And indeed, the first snippet was much faster in my actual app as well
How does V8 optimise the creation of very large arrays?
问题 Recently, I had to work on optimising a task that involved the creation of really large arrays (~ 10⁸ elements). I tested a few different methods, and, according to jsperf, the following option seemed to be the fastest. var max = 10000000; var arr = new Array(max); for (let i = 0; i < max; i++) { arr[i] = true; } Which was ~ 85% faster than var max = 10000000; var arr = []; for (let i = 0; i < max; i++) { arr.push(true); } And indeed, the first snippet was much faster in my actual app as well
How does V8 optimise the creation of very large arrays?
问题 Recently, I had to work on optimising a task that involved the creation of really large arrays (~ 10⁸ elements). I tested a few different methods, and, according to jsperf, the following option seemed to be the fastest. var max = 10000000; var arr = new Array(max); for (let i = 0; i < max; i++) { arr[i] = true; } Which was ~ 85% faster than var max = 10000000; var arr = []; for (let i = 0; i < max; i++) { arr.push(true); } And indeed, the first snippet was much faster in my actual app as well
Does nodejs/V8 store compiled machine code anywhere on disk?
问题 Edit : Node uses bytecode since Node 8.3, before that, sources were compiled directly to machine code. I do a lot of Python coding, and there's always bytecode lying around in .pyc files. I was wondering if node stores its machine code in similar files, eg it would make sense to keep the machine code representation around on disk and re-use it if a file's source is unchanged. If so, where does node/v8 store this machine code? Edit 2 : As @dystroy mentions below this is a dupe of How can I see
Is it normal for Node.js' RSS (Resident Set Size) to grow with each request, until reaching some cap?
问题 I've noticed that RSS (Resident Set Size) of my node.js app is growing over time, and considering I'm having a "JS Object Allocation Failed - Out of Memory" error on my server, it seems a likely cause. I set up the following very simple Node app: var express = require('express'); var app = express(); app.get('/',function(req,res,next){ res.end(JSON.stringify(process.memoryUsage())); }); app.listen(8888); By simply holding down the "refresh" hotkey @ http:// localhost:8888/ I can watch the RSS
Nodejs介绍和环境搭建
Nodejs是JavaScript的运行环境，它让 Java Script 可以开发后端程序，实现几乎其他后端 Node.js 是一个 Javascript 运行环境 (runtime) 可以与 PHP、 JSP、 Python、 Ruby 等后端语言平起平坐。 Nodejs 是基于 V8 引擎， V8 是 Google 发布的开源 JavaScript 引擎，本身就是用于 Chrome 浏览器 的 JS 解释部分，但是 Ryan Dahl 把这个 V8 搬到了服务器上，用于做服务器的软件。 优势： 1.NodeJs 语法完全是 js 语法 懂 JS 基础就可以学会 Nodejs 后端开发。成本。Node 打破了过去 JavaScript 只能在浏览器中运行的局面。前后端编程环境统一，可以大大降低开发 2.NodeJs 超强的高并发能力。 Node.js 的首要目标是提供一种简单的、用于创建高性能服务器及可在该服务器中运行的各种应用程 序的开发工具。首先让我们来看一下现在的服务器端语言中存在着什么问题。在 Java、PHP 或者.net等服务器端语言中，会为每一个客户端连接创建一个新的线程。而每个线程需要耗费大约 2MB 内存理论上， 一个 8GB 内存的服务器可以同时连接的最大用户数为 4000个左右 。要让 Web 应用程序支持更多的用户，就 需要增加服务器的数量，而