This example counts to finity, sleeping 1 second between each count. Related:
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.
A C hello world with an infinite loop at the end has:
  • 2.7 MB
  • 770 KB
For a Node.js infinite loop nodejs/infinite_loop.js
topp infinite_loop.js
This gives approximately:
  • RSS: 20 MB
  • VSZ: 230 MB
Adding a single hello world to it as in nodejs/infinite_hello.js and running:
topp infinite_hello.js
leads to:
  • RSS: 26 MB
  • VSZ: 580 MB
We understand that Node.js preallocates VSZ wildly. No big deal, but it does mean that VSZ is a useless measure for Node.js.
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 process.memoryUsage nodejs/infinite_memoryusage.js:
node --expose-gc infinite_memoryusage.js
which gives initially:
{
  rss: 23851008,
  heapTotal: 6987776,
  heapUsed: 3674696,
  external: 285296,
  arrayBuffers: 10422
}
but after a few seconds randomly jumps to:
{
  rss: 26005504,
  heapTotal: 9084928,
  heapUsed: 3761240,
  external: 285296,
  arrayBuffers: 10422
}
so we understand that
  • heapUsed seems constant at 3.7 MB
  • heapTotal is a very noisy, as it starts at 7 MB, but randomly jumps to 9 MB at one point without apparent reason
Now let's run our main test program.
First a baseline case with an array of length 1:
node --expose-gc bench_mem.js n 1
This gives the same results as node --expose-gc infinite_memoryusage.js. The same result is obtained by doing:
a = undefined
with:
node --expose-gc bench_mem.js dealloc
Not let's vary the size of n a bit with:
node --expose-gc bench_mem.js n N
which gives:
NheapUsedheapTotalrssheapUsed per elemrss per elem
1 M14 MB48 MB56 MB1030
10 M122 MB157 MB176 MB1815
100 M906 MB940 MB960 MB99.3
"rss per elem" is calculated as: rss - 26 MB, where 26 MB is the baseline RSS seen on n 1.
Similarly "heapUsed per elem" deduces the 4 MB (approximation of the above 3.7 MB) seen on n 1.
Note that to reach MAX_SAFE_INTEGER we would need 8 bytes per elem worst case.
Everything below 100 million (8) is therefore very memory wasteful in terms of RSS.
If we use Int32Array typed array buffers instead of a simple Array:
node --expose-gc bench_mem.js array-buffer n N
we see that the memory is now, unsurprisingly, accounted for under arrayBuffers, e.g. for N 1 million:
{
  rss: 31776768,
  heapTotal: 6463488,
  heapUsed: 3674520,
  external: 4285296,
  arrayBuffers: 4010422
}
Results for different N:
|| 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
We see therefore that typed arrays are much closer to what they advertise (4 bytes per element), even for smaller element counts, as expected.
Now let's try one million objects of type { a: 1, b: -1 }:
node --expose-gc bench_mem.js obj
gives:
{
  rss: 138969088,
  heapTotal: 105246720,
  heapUsed: 70103896,
  external: 285296,
  arrayBuffers: 10422
}
Disaster! Memory usage is up to 70 MB! Why?? We were expecting only about 24, 4 baseline + 2 * 10 for each million int?!
And now an equivalent version using class:
node --expose-gc bench_mem.js class
gives the same result.
Let's try Array:
node --expose-gc bench_mem.js arr
is even worse at 78 MB!! OMG why.
{
  rss: 164597760,
  heapTotal: 129363968,
  heapUsed: 78117008,
  external: 285296,
  arrayBuffers: 10422
}
Let's change the number of fields on the object? First as a sanity check:
node --expose-gc bench_mem.js obj 2
produces as expected the smae result as:
node --expose-gc bench_mem.js obj
so adding properties one by one doesn't change anything from creating the literal all at once. Good.
Now:
node --expose-gc bench_mem.js obj N
gives heapUsed:
  • 1: 70M
  • 2: 70M
  • 3: 70M
  • 4: 70M
  • 5: 110M
  • 6: 110M
  • 7: 110M
  • 8: 134M
  • 9: 134M
  • 10: 134M
  • 11: 158M