In this section we will use the file nodejs/bench_mem.js, tests are run on Node.js v16.14.2 from NVM, Ubuntu 21.10, on Lenovo ThinkPad P51 (2017) which has 32 GB RAM.
Related answer: stackoverflow.com/questions/12023359/what-do-the-return-values-of-node-js-process-memoryusage-stand-for/72043884#72043884
First using
topp
from stackoverflow.com/questions/1221555/retrieve-cpu-usage-and-memory-usage-of-a-single-process-on-linux/40576129#40576129 let's observe the memory usage of some baseline cases.For a Node.js infinite loop nodejs/infinite_loop.jsThis gives approximately:
topp infinite_loop.js
- RSS: 20 MB
- VSZ: 230 MB
Adding a single hello world to it as in nodejs/infinite_hello.js and running:leads to:We understand that Node.js preallocates VSZ wildly. No big deal, but it does mean that VSZ is a useless measure for Node.js.
topp infinite_hello.js
- RSS: 26 MB
- VSZ: 580 MB
Forcing garbage collection as in nodejs/infinite_hello.js brings it down to 20 MB however:
topp node --expose-gc infinite_hello_gc.js
Finally let's see a baseline for which gives initially:but after a few seconds randomly jumps to:so we understand that
process.memoryUsage
nodejs/infinite_memoryusage.js:node --expose-gc infinite_memoryusage.js
{
rss: 23851008,
heapTotal: 6987776,
heapUsed: 3674696,
external: 285296,
arrayBuffers: 10422
}
{
rss: 26005504,
heapTotal: 9084928,
heapUsed: 3761240,
external: 285296,
arrayBuffers: 10422
}
First a baseline case with an array of length 1:This gives the same results as with:
node --expose-gc bench_mem.js n 1
node --expose-gc infinite_memoryusage.js
. The same result is obtained by doing:a = undefined
node --expose-gc bench_mem.js dealloc
If we use we see that the memory is now, unsurprisingly, accounted for under Results for different N:We see therefore that typed arrays are much closer to what they advertise (4 bytes per element), even for smaller element counts, as expected.
Int32Array
typed array buffers instead of a simple Array
:node --expose-gc bench_mem.js array-buffer n N
arrayBuffers
, e.g. for N
1 million:{
rss: 31776768,
heapTotal: 6463488,
heapUsed: 3674520,
external: 4285296,
arrayBuffers: 4010422
}
|| N
|| `arrayBuffers`
|| `rss`
|| `rss` per elem
| 1 M
| 4 MB
| 31 MB
| 5
| 10 M
| 40 MB
| 67 MB
| 4.6
| 100 M
| 40 MB
| 427 MB
| 4
Now let's try one million objects of type gives:Disaster! Memory usage is up to 70 MB! Why?? We were expecting only about 24, 4 baseline + 2 * 10 for each million int?!
{ a: 1, b: -1 }
:node --expose-gc bench_mem.js obj
{
rss: 138969088,
heapTotal: 105246720,
heapUsed: 70103896,
external: 285296,
arrayBuffers: 10422
}
And now an equivalent version using gives the same result.
class
:node --expose-gc bench_mem.js class
Let's try Array:is even worse at 78 MB!! OMG why.
node --expose-gc bench_mem.js arr
{
rss: 164597760,
heapTotal: 129363968,
heapUsed: 78117008,
external: 285296,
arrayBuffers: 10422
}
Pinned article: ourbigbook/introduction-to-the-ourbigbook-project
Welcome to the OurBigBook Project! Our goal is to create the perfect publishing platform for STEM subjects, and get university-level students to write the best free STEM tutorials ever.
Everyone is welcome to create an account and play with the site: ourbigbook.com/go/register. We belive that students themselves can write amazing tutorials, but teachers are welcome too. You can write about anything you want, it doesn't have to be STEM or even educational. Silly test content is very welcome and you won't be penalized in any way. Just keep it legal!
Intro to OurBigBook
. Source. We have two killer features:
- topics: topics group articles by different users with the same title, e.g. here is the topic for the "Fundamental Theorem of Calculus" ourbigbook.com/go/topic/fundamental-theorem-of-calculusArticles of different users are sorted by upvote within each article page. This feature is a bit like:
- a Wikipedia where each user can have their own version of each article
- a Q&A website like Stack Overflow, where multiple people can give their views on a given topic, and the best ones are sorted by upvote. Except you don't need to wait for someone to ask first, and any topic goes, no matter how narrow or broad
This feature makes it possible for readers to find better explanations of any topic created by other writers. And it allows writers to create an explanation in a place that readers might actually find it.Figure 1. Screenshot of the "Derivative" topic page. View it live at: ourbigbook.com/go/topic/derivativeVideo 2. OurBigBook Web topics demo. Source. - local editing: you can store all your personal knowledge base content locally in a plaintext markup format that can be edited locally and published either:This way you can be sure that even if OurBigBook.com were to go down one day (which we have no plans to do as it is quite cheap to host!), your content will still be perfectly readable as a static site.
- to OurBigBook.com to get awesome multi-user features like topics and likes
- as HTML files to a static website, which you can host yourself for free on many external providers like GitHub Pages, and remain in full control
Figure 2. You can publish local OurBigBook lightweight markup files to either OurBigBook.com or as a static website.Figure 3. Visual Studio Code extension installation.Figure 5. . You can also edit articles on the Web editor without installing anything locally. Video 3. Edit locally and publish demo. Source. This shows editing OurBigBook Markup and publishing it using the Visual Studio Code extension. - Infinitely deep tables of contents:
All our software is open source and hosted at: github.com/ourbigbook/ourbigbook
Further documentation can be found at: docs.ourbigbook.com
Feel free to reach our to us for any help or suggestions: docs.ourbigbook.com/#contact