Your idea is flatten the UInt8Array into the stream.

While I understand the logic, that's a terrible idea.

* The overhead is massive. Now every 1KiB turns into 1024 objects. And terrible locality.

* Raw byte APIs...network, fs, etc fundamentally operate on byte arrays anyway.

In the most respectful way possible...this idea would only be appealing to someone who's not used to optimizing systems for efficiency.

▲

conartist6 7 hours ago | parent | next [-]

JS engines actually are optimized to make that usage pattern fast.

Small, short-lived objects with known key ordering (monomorphism) are not a major cost in JS because the GC design is generational. The smallest, youngest generation of objects can be quickly collected with an incremental GC because the perf assumption is that most of the items in the youngest generation will be garbage. This allows collection to be optimized by first finding the live objects in the gen0 pool, copying them out, then throwing away the old gen0 pool memory and replacing it with a new chunk.

▲

softfalcon 7 hours ago | parent | next [-]

What happens when I send an extremely high throughput of data and the scheduler decides to pause garbage collection due to there being too many interrupts to my process sending network events? (a common way network data is handed off to an application in many linux distros)

Are there any concerns that the extra array overhead will make the application even more vulnerable to out of memory errors while it holds off on GC to process the big stream (or multiple streams)?

I am mostly curious, maybe this is not a problem for JS engines, but I have sometimes seen GC get paused on high throughput systems in GoLang, C#, and Java, which causes a lot of headaches.

▲

conartist6 6 hours ago | parent [-]

Yeah I don't think that's generally a problem for JS engines because of the incremental garbage collector.

If you make all your memory usage patterns possible for the incremental collector to collect, you won't experience noticeable hangups because the incremental collector doesn't stop the world. This was already pretty important for JS since full collections would (do) show up as hiccups in the responsiveness of the UI.

	▲	softfalcon 3 hours ago \| parent [-]
		Interesting, thanks for the info, I'll do some reading on what you're saying. I agree, you're right about JS having issues with hiccups in the UI due to scheduling on a single process thread. Makes a lot of sense, cool that the garbage collector can run independently of the call stack and function scheduler.

▲

conartist6 7 hours ago | parent | prev [-]

It's not blazingly fast, no, but it's not as much overhead as people think either when they're imagining what it would cost to do the same thing with malloc. TC39 knew all this when they picked { step, done } as the API for iteration and they still picked it, so I'm not really introducing new risk but rather trusting that they knew what they were doing when they designed string iterators.

At the moment the consensus seems to be that these language features haven't been worth investing much in optimizing because they aren't widely used in perf-critical pathways. So there's a chicken and egg problem, but one that gives me some hope that these APIs will actually get faster as their usage becomes more common and important, which it should if we adopt one of these proposed solutions to the current DevX problems

▲

fwip 7 hours ago | parent | prev [-]

I agree with your post, but in practice, couldn't you get back that efficiency by setting T = UInt8Array? That is, write your stream to send / receive arrays.

My reference point is from a noob experience with Golang - where I was losing a bunch of efficiency to channel overhead from sending millions of small items. Sending batches of ~1000 instead cut that down to a negligible amount. It is a little less ergonomic to work with (adding a nesting level to your loop).