I accidentally saw an article about sending http requests under nodejs without caching dns results. This means that if you write an http collection program based on nodejs, if you do not provide dns caching, each request will foolishly repeat the resolution of the domain name into an ip address. Sounds like it will affect performance a lot, right?
In my project, sending http requests does not use node’s native http library, but relies on a commonly used Request library. I checked the relevant documents and github issues of the library, and also found some posts related to dns. But what most people say is that the dns issue itself is not within the scope of the Request library, but is attributed to the core issue of nodejs. omg, it feels so profound!
Fortunately, the article mentioned above also proposed two solutions:
Application level: dnscache
OS level: Bind, dnsmasq and unbound
No matter which solution it is, it seems to be very simple. , just install and initialize it. But the question is, how do we verify that they are real and effective? Since my local development machine operating system environment is win7 64bit, I cannot test the operating system level solution mentioned above. Then let’s take a look at whether the application level solution is effective~~
First of all, we need to enable win to track dns requests. Here I found a software that can be run directly without installation after downloading. Then, we also need a method to clear the cache, you can see here, simply execute it in the terminal:
ipconfig /flushdns
The tool is ready, we create a test script:
const Request = require('request'); function fetch(url, callback){ Request.head({ url: url, timeout: 10000, tunnel: true, gzip: true, proxy: false, followRedirect: false }, callback); } let now = Date.now(); fetch('http://blog.kazaff.me', function(err, response, body){ console.log('lookup time without cache: ', Date.now() - now); });
Okay Yes, now open DNSQuerySniffer, and then clean up the local DNS cache first. When everything is ready, execute our test script node test.js. You will see a DNS request and its related information in DNSQuerySniffer. Within a certain time interval, if you run our test script repeatedly, you will find that the DNS request will not be triggered again. What does this mean? My win7 environment itself has its own operating system level DNS cache (but the cache time is very short).
Modify our test script as follows:
const dnscache = require('dnscache')({ "enable": true }); const Request = require('request'); function fetch(url, callback){ Request.head({ url: url, timeout: 10000, tunnel: true, gzip: true, proxy: false, followRedirect: false }, callback); } let now = Date.now(); fetch('http://priceline.com', function(err, response, body){ console.log('lookup time without cache: ', Date.now() - now); setTimeout(function(){ now = Date.now(); fetch('http://priceline.com', function(err, response, body){ console.log('lookup time with cache: ', Date.now() - now); }); }, 2000); });
This time we quickly clear the local DNS cache after executing the test script (if you are not fast, you can appropriately extend the trigger interval of setTimeout), you will find that two seconds The subsequent http request does not re-query the DNS. What does this mean? Obviously, our application maintains its own DNS cache, so the second request does not care whether the corresponding DNS cache record exists locally in the operating system.

JavaScript is widely used in websites, mobile applications, desktop applications and server-side programming. 1) In website development, JavaScript operates DOM together with HTML and CSS to achieve dynamic effects and supports frameworks such as jQuery and React. 2) Through ReactNative and Ionic, JavaScript is used to develop cross-platform mobile applications. 3) The Electron framework enables JavaScript to build desktop applications. 4) Node.js allows JavaScript to run on the server side and supports high concurrent requests.

Python is more suitable for data science and automation, while JavaScript is more suitable for front-end and full-stack development. 1. Python performs well in data science and machine learning, using libraries such as NumPy and Pandas for data processing and modeling. 2. Python is concise and efficient in automation and scripting. 3. JavaScript is indispensable in front-end development and is used to build dynamic web pages and single-page applications. 4. JavaScript plays a role in back-end development through Node.js and supports full-stack development.

C and C play a vital role in the JavaScript engine, mainly used to implement interpreters and JIT compilers. 1) C is used to parse JavaScript source code and generate an abstract syntax tree. 2) C is responsible for generating and executing bytecode. 3) C implements the JIT compiler, optimizes and compiles hot-spot code at runtime, and significantly improves the execution efficiency of JavaScript.

JavaScript's application in the real world includes front-end and back-end development. 1) Display front-end applications by building a TODO list application, involving DOM operations and event processing. 2) Build RESTfulAPI through Node.js and Express to demonstrate back-end applications.

The main uses of JavaScript in web development include client interaction, form verification and asynchronous communication. 1) Dynamic content update and user interaction through DOM operations; 2) Client verification is carried out before the user submits data to improve the user experience; 3) Refreshless communication with the server is achieved through AJAX technology.

Understanding how JavaScript engine works internally is important to developers because it helps write more efficient code and understand performance bottlenecks and optimization strategies. 1) The engine's workflow includes three stages: parsing, compiling and execution; 2) During the execution process, the engine will perform dynamic optimization, such as inline cache and hidden classes; 3) Best practices include avoiding global variables, optimizing loops, using const and lets, and avoiding excessive use of closures.

Python is more suitable for beginners, with a smooth learning curve and concise syntax; JavaScript is suitable for front-end development, with a steep learning curve and flexible syntax. 1. Python syntax is intuitive and suitable for data science and back-end development. 2. JavaScript is flexible and widely used in front-end and server-side programming.

Python and JavaScript have their own advantages and disadvantages in terms of community, libraries and resources. 1) The Python community is friendly and suitable for beginners, but the front-end development resources are not as rich as JavaScript. 2) Python is powerful in data science and machine learning libraries, while JavaScript is better in front-end development libraries and frameworks. 3) Both have rich learning resources, but Python is suitable for starting with official documents, while JavaScript is better with MDNWebDocs. The choice should be based on project needs and personal interests.


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