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Discussion (37 Comments)Read Original on HackerNews
Will try it out as next distro for my Debian system, longtime experience with Void Linux (runit) on another box is great.
It's my third attempt to make my regular Linux desktop less disk-chatty. This is a huge issue for btrfs and for COW FS in general, because they have massive write amplification for small and frequent writes (38,7 TB written to my idle desktop SSD in 2 years).
If you're interested, here are my findings this time so far:
Have you considered using a different fstype like XFS for this? btrfs is good for homedirs, but I wouldn't necessarily use it for other filesystems (/usr, /var, etc.)
audit - appears to be some sort of AppArmor logging?
br[] - bridge interface docker uses consistently rebuilds itself? May be related to docker compose networking.
I am not again binary logs, or logs in a database. It's just yet another time I deal with good ideas implemented horribly, horribly badly when it comes to systemd.
The first thing I do on a Linux system is install a proper syslog daemon.
See StandardOutput= and StandardError=.
systemd is a stewarded FOSS, which means there's a team behind it, who are getting paid, and develop this software with release cycles, backwards compatibility guarantees, architectural decisions, and such.
These people know better. I usually only prepare fixes for FOSS one-man-show which have little to no maintenance, otherwise I prefer professionals to handle it. Sometimes "suggestion" PR is worse than a triaged issue IMO.
That said, would you look a gift horse in the mouth?
See also the design rationale: https://docs.google.com/document/u/0/d/1IC9yOXj7j6cdLLxWEBAG...
It's basically comparing an append-only fixed-format text file with a queryable database. Of course the former is going to be more performant on writes.
But I never really made any effort to change the on-disk structure or how writes were performed. My focus was more on the read performance for journalctl and stability of the daemon.
Back when I was paid to fix things in journald at CoreOS ages ago, it couldn't even avoid getting killed by its own service watchdog.
My impression back then was the on-disk format dispersed the information too much within the same file, and those individual datums being written at discontiguous offsets were quite small, far smaller than an IO block size or even a disk sector size.
Seemed like a write amplification problem due to the file format. If you write a few bytes into some arbitrary position within a file, the storage has to write back the whole block, despite your only changing a tiny fraction of it. If those few bytes happened to cross a block boundary, guess what? two blocks get written.
The format had no consideration for these block-oriented storage details, then doing the IO via mmap rubs salt into the wound since the kernel has to try guess what to prefetch asynchronously... but I don't think that aspect amplifies the writes above what plain buffered IO would do - maybe I'm wrong. I'd expect the mmap aspect to be causing more/mispredicted reads, and polluting the page cache with unrelated contents (you tend to end up with the entire journal cached IIRC, if you have enough memory). I suppose there's probably compounding of the write amplification problem since the kernel will be dirtying pages at page size granularity vs. 512b sectors, and you have the same issue of small writes landing on page boundaries dirtying two pages. So that aspect of using mmap for the writes probably is exacerbating the problem.
Thank you for your service!
https://github.com/systemd/systemd/blob/199f75205b9c0625bf56...
Also, why mmaped file?
There was mailing list discussion at the time journald was conceived though, you can find it if you look.
https://0pointer.de/blog/projects/the-journal.html might be a good entry-point.
It doesn't look like there was an open design review; Lennard Poettering just dropped it in in v38. https://lists.freedesktop.org/archives/systemd-devel/2012-Ja...
> Performance: journal operations for appending and browsing should be fast in terms of complexity. O(log n) or better is highly advisable, in order to provide for organization-wide log monitoring with good performance
> Minimal Footprint: journal data files should be small in disk size, especially in the light that the amount of data generated might be substantially bigger than on classic syslog.
> If you write a few bytes into some arbitrary position within a file, the storage has to write back the whole block, despite your only changing a tiny fraction of it. If those few bytes happened to cross a block boundary, guess what? two blocks get written.
Exactly. So either make the format append-only or make it append-mostly with occasional writebacks from the append-only log to the main data structure. Nice and simple.
> I'd expect the mmap aspect to be causing more/mispredicted reads, and polluting the page cache with unrelated contents (you tend to end up with the entire journal cached IIRC, if you have enough memory).
If you used an LSM or append-only approach, you could MADV_DONTNEED the pages behind your write cursor pretty easily.
the last time I contributed to journald upstream was to fix a degenerate behavior with many journal files: https://github.com/systemd/systemd/commit/176f73272e6e3116ca...
that makes a dramatic difference for those hitting this case, but it only gets things from nearly unusable to slow-as-usual.
"But isn't it an OLAP database? Shouldn't you use SQLite for something that's vaguely real-time?"
Eh, in this instance, I think I'd prefer the columnar design and automatic compression DuckDB affords. Log entries have lots of little fields, many of which are unchanging from row-to-row, and DuckDB excels at storing this kind of data.
BTW: no, you don't need O(N*log(N) writes for DDB. No, you're not doing a whole block-group write for every message. No, Parquet is not a magical solution. Do people have any idea how DB storage engines actually work?
You can read them with DuckDB, but you don't end up with O(log n) writes -- which is, to speak plain English, batshit fucking insane for a system logger.
What those cursed writes buys you is O(log n) reads, but there's just no scenario that is necessary. If you have literally any time or subsystem constraints, parquet's predicate pushdowns means you get plenty fast access even with a full scan.