"Idle cost is that one lightweight SELECT per millisecond per database — no page-cache pressure, no writer-lock contention, no kernel file watcher in the mix."
I think (respectfully) the LLM that probably wrote this overshot the mark here because busy-polling a select does not actually sound better to me than a "kernel file watcher".
Respectfully (thanks haha) - yeah probably right. Original intent was to use inotify type thing but i avoided per-platform differences at the outset. this was definitely a for fun project that blew up unintentionally and am working to harden/improve.
One cannot be a little bit pregnant. But a DB can be only a little bit in the RAM, and specifically in the page cache. SQLite can act exactly like that, and it's damn fast as long as it does not need to durably write a transaction. Polling once a millisecond could spend a few microseconds.
I wonder if using a tiny Redis instance, or even something like LevelDB would be even more efficient.
Hold on -- if it really is "one lightweight SELECT per millisecond", and you're saying a select is "a couple hundred microseconds", say generously 200us?, then you're spending 200us out of every 1000us just selecting. That's a lot of polling!
I mean only in the same sense that you spend 1 second per second doing something. Time is probably not the best way to evaluate the resources this consumes and I doubt it takes much of anything else either.
It does seem weird though even for sqlite. I wonder how oban does it. I also wonder if OP knows oban can run on sqlite.
Yeah, again, to be clear: I get how SQLite works and I'm not dunking on the design, I'm just saying the comparison set up on this page snags. It's a classic LLM negated triptych, but "one of these things is not like the other": cache pressure: bad, writer contention: bad, kernel file watcher: ... good, actually? Intuitively seems better than this design?
to me it sounds like they asked it to not make a kernel file watcher, and now it writes that into every comment everywhere, despite not even being in the implementation
That only catches changes made by the database connection being "hooked."
This has a thread running in the background trying to catch changes made by other connections, potentially (I'm not sure here, but I suspect as much) in different processes that are modifying the same database.
good point. but ime and as seems to be widely understood writing from multiple connections is a bit of a minefield in SQLite. and afaik it still would be possible to have a hook on all connections you expect to be writing?
Yeah, I had the same instinct - this feels very much like a "nice idea" but the execution falls short. I mean - busily banging on sqlite like this? Shit at that point just use Redis.
For what it's worth, Kine (software that k3s uses to replace etcd with SQL databases) implements etcd watches on SQLite through polling[1]. The reason being that SQLite does not offer NOTIFY/LISTEN like MySQL and Postgres do. Ironically, Honkey attempts implementing NOTIFY/LISTEN through polling.
k3s has been running on my home server for about three years now (using the default SQLite backend), and there doesn't seem to be excessive CPU usage despite dozens of watches existing in the simulated etcd. Of course, this doesn't say much about Honker, but it's nonetheless worth pointing out that sometimes the choice of database forces one towards a certain design.
With SQLite, you're basically funneled towards a single-writer / single-process design anyway ... in which case why not use a more traditional condvar + mutex rather than polling?
Really might be in sqlite. I've learned to never trust my intuition about performance with that thing. So many times I've gone to "optimize" something and discovered that the naive hack way I had been doing it was faster anyway. It's built for this sort of bullshit.
I had a manual fs polling thing a while back. It was ugly (low time budget, didn't wanna mess with the native watchers), just scanned the whole thing once per second. It averaged out to like 0.3% CPU.
Not elegant, but acceptable for my purposes! (Small-ish directory, and "ping me within a second or two" was realtime enough for this use case.)
i mean, technically this is once per millisecond, so this would happen 1000x more. In your case due to the kernel overhead you would likely not even be able to do it (300% CPU?).
Either way this does seem like a very large overhead due to the fact that there's just no other way to do it without a deeper kernel integration which might be outside the scope of what sqlite is trying to do.
>honker polls SQLite’s PRAGMA data_version every millisecond
I don't understand why you need busy polling if you're in-process anyway (what you usually have with Sqlite). Just make the event processing thread wait on a condition and wake it up after a transaction commits. In my Sqlite-based pet project, I have a Transaction interface that keeps track of whether an event was actually published inside a transaction, and if it was, the event processing thread is immediately notified inside Commit() to wake up and issue SELECTs. When no events are published, the Sqlite database is not touched and CPU has zero usage. Additionally, on application startup, we need to SELECT in case some events were written to the queue but did not have the chance to be processed because the application restarted or crashed.
> Once real work flows through a SQLite-backed app, you need a queue. The usual answer is “add Redis + Celery.”
Are they joking? SQLite is usually used for single-process (mutliple threads) applications. The proper way to communicate between threads/processes is a ring buffer, where you allocate structs (allocation typically is incrementing a pointer), and futex/eventfd for notifications (+ some spinlocking to avoid going to kernel when the tasks arrive quickly). Why do you need redis for that? If you need persistent tasks, then you can store them in the table, and still use futex for notifications. This polling is inefficient and they should not make it a library which will cause other lazy developers add it to their app.
> honker polls SQLite’s PRAGMA data_version every millisecond. That’s a monotonic counter SQLite increments on every commit from any connection, journal mode, or process — a ~3 µs read for a precise wake signal
That's 3 ms per second = 0.3% CPU time wasted for every waiting thread.
Like Electron, this feels like written by a web developer and not a real programmer.
>That's 3 ms per second = 0.3% CPU time wasted for every waiting thread.
I suspect that's actually "per process, per database (usually 1)", and not based on number of threads or tables. `data_version` semantics mean there's no need for more than one connection polling it, and it's being used as a relatively lightweight "DB has changed, check queues" check (that's pretty much its whole purpose).
Also I believe this is mostly intended for multi-process use, e.g. out-of-process workers, so an in-process dirty tracker (e.g. just check after insert/update/delete) isn't sufficient.
So I do think it's somewhat crazy, but it is at least very simple. fsnotify-like monitoring seems like a fairly obvious improvement tho, not sure why that isn't part of it. Maybe it's slower? I haven't tried to do anything actually-performant-or-reliable with fs notifications, dunno what dragons lie in wait.
Key difference vs SQL polling is that we’re touching metadata instead of data pages. I have work in process to make this work without any polling (innotify, kqueue, mmap’d shm file check) after the original stat(2) direction proved unreliable if lightweight.
Would love your feedback and or contributions in the repo - still figuring out the end shape.
It’s an interesting approach and can be quite fun to use for new projects.
> How it works: honker polls SQLite’s PRAGMA data_version every millisecond. That’s a monotonic counter SQLite increments on every commit from any connection, journal mode, or process — a ~3 µs read for a precise wake signal.
I've implemented something similar in the past, but using inotify. You need to watch the -wal file for IN_MODIFY. To make it work reliably I found I had to run:
BEGIN IMMEDIATE TRANSACTION; ROLLBACK;
Otherwise the new changes weren't guaranteed to be visible to the process. I'm sure there's a more targetted approach that would work instead - maybe flock on a particular byte in the `-shm` file.
I think this is interesting too sqlite a as the coordination boundary: business state, queue state, stream offsets, retries, and acks all sharing one transactional substrate. The 1ms polling is getting a lot of weight in the thread though :)
I think (respectfully) the LLM that probably wrote this overshot the mark here because busy-polling a select does not actually sound better to me than a "kernel file watcher".
Love Fly.
This reminds me of the teenager who told her dad that she was just a tiny little bit pregnant.
I wonder if using a tiny Redis instance, or even something like LevelDB would be even more efficient.
(read that in the way of "think of the children!")
It does seem weird though even for sqlite. I wonder how oban does it. I also wonder if OP knows oban can run on sqlite.
And if you are making changes, don't you have to poll regardless after the file watcher wakes you?
For WAL mode, SQLite can probably satisfy this query just by inspecting some shared memory. But it is busy waiting, sure.
This has a thread running in the background trying to catch changes made by other connections, potentially (I'm not sure here, but I suspect as much) in different processes that are modifying the same database.
k3s has been running on my home server for about three years now (using the default SQLite backend), and there doesn't seem to be excessive CPU usage despite dozens of watches existing in the simulated etcd. Of course, this doesn't say much about Honker, but it's nonetheless worth pointing out that sometimes the choice of database forces one towards a certain design.
[1] https://github.com/k3s-io/kine/blob/648a2daa/pkg/logstructur...
I had a manual fs polling thing a while back. It was ugly (low time budget, didn't wanna mess with the native watchers), just scanned the whole thing once per second. It averaged out to like 0.3% CPU.
Not elegant, but acceptable for my purposes! (Small-ish directory, and "ping me within a second or two" was realtime enough for this use case.)
Either way this does seem like a very large overhead due to the fact that there's just no other way to do it without a deeper kernel integration which might be outside the scope of what sqlite is trying to do.
For the low, low cost of $1 per minute, you can also lease a supercar.
I don't understand why you need busy polling if you're in-process anyway (what you usually have with Sqlite). Just make the event processing thread wait on a condition and wake it up after a transaction commits. In my Sqlite-based pet project, I have a Transaction interface that keeps track of whether an event was actually published inside a transaction, and if it was, the event processing thread is immediately notified inside Commit() to wake up and issue SELECTs. When no events are published, the Sqlite database is not touched and CPU has zero usage. Additionally, on application startup, we need to SELECT in case some events were written to the queue but did not have the chance to be processed because the application restarted or crashed.
Are they joking? SQLite is usually used for single-process (mutliple threads) applications. The proper way to communicate between threads/processes is a ring buffer, where you allocate structs (allocation typically is incrementing a pointer), and futex/eventfd for notifications (+ some spinlocking to avoid going to kernel when the tasks arrive quickly). Why do you need redis for that? If you need persistent tasks, then you can store them in the table, and still use futex for notifications. This polling is inefficient and they should not make it a library which will cause other lazy developers add it to their app.
> honker polls SQLite’s PRAGMA data_version every millisecond. That’s a monotonic counter SQLite increments on every commit from any connection, journal mode, or process — a ~3 µs read for a precise wake signal
That's 3 ms per second = 0.3% CPU time wasted for every waiting thread.
Like Electron, this feels like written by a web developer and not a real programmer.
I suspect that's actually "per process, per database (usually 1)", and not based on number of threads or tables. `data_version` semantics mean there's no need for more than one connection polling it, and it's being used as a relatively lightweight "DB has changed, check queues" check (that's pretty much its whole purpose).
Also I believe this is mostly intended for multi-process use, e.g. out-of-process workers, so an in-process dirty tracker (e.g. just check after insert/update/delete) isn't sufficient.
So I do think it's somewhat crazy, but it is at least very simple. fsnotify-like monitoring seems like a fairly obvious improvement tho, not sure why that isn't part of it. Maybe it's slower? I haven't tried to do anything actually-performant-or-reliable with fs notifications, dunno what dragons lie in wait.
Key difference vs SQL polling is that we’re touching metadata instead of data pages. I have work in process to make this work without any polling (innotify, kqueue, mmap’d shm file check) after the original stat(2) direction proved unreliable if lightweight.
Would love your feedback and or contributions in the repo - still figuring out the end shape.
> How it works: honker polls SQLite’s PRAGMA data_version every millisecond. That’s a monotonic counter SQLite increments on every commit from any connection, journal mode, or process — a ~3 µs read for a precise wake signal.
https://github.com/oldmoe/litestack
To make it look even more absurd . SQLite is not concurrent and you’ll have tons of problems using it practically .
I’d like to see messages per second.