Re: BUG #18471: Possible JIT memory leak resulting in signal 11: Segmentation fault on ARM
От | Dmitry Dolgov |
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Тема | Re: BUG #18471: Possible JIT memory leak resulting in signal 11: Segmentation fault on ARM |
Дата | |
Msg-id | 20240521160800.xendwle36apwyy36@ddolgov.remote.csb обсуждение исходный текст |
Ответ на | BUG #18471: Possible JIT memory leak resulting in signal 11: Segmentation fault on ARM (PG Bug reporting form <noreply@postgresql.org>) |
Список | pgsql-bugs |
> On Fri, May 17, 2024 at 01:13:06PM +0000, PG Bug reporting form wrote: > The following bug has been logged on the website: > > Bug reference: 18471 > Logged by: Joachim Haecker-Becker > Email address: joachim.haecker-becker@arcor.de > PostgreSQL version: 16.3 > Operating system: Debian Bookworm > Description: > > We have a reproducible way to force a postgres process to consume more and > more RAM until it crashes on ARM. > The same works on X86 without any issue. > With jit=off it runs on ARM as well. > > We run into this situation in a real-life database situation with a lot of > joins and aggregate functions. > The following code is just a mock to reproduce a similar situation without > needing access to our real data. > This issue blocks us from upgrading or ARM-hosted databases into something > newer than 14.7. I think it would be useful to know how much memory difference are we talking about and, just to make everything clear, how exactly postgres crashes (OOM kill I assume)? It's important to differentiate between the case "ARM with jit crashes, ARM without jit doesn't" and "ARM with jit crashes, ARM without jit crashes with even more columns" (the same goes for x86). I've tried to reproduce it on an arm64 VM (16.3 build with llvm 17), and although I could observe some difference in memory consumption between JIT on/off, but it wasn't huge (around 10% or so). Running it under valgrind shows only complains about memory allocated for bitcode modules, which is expected -- as far as I recall postgres is somewhat wasteful when it comes to allocating memory for those modules, even more so for parallel workers. This is the case here, where there is growing number of parallel hash workers. This would not explain any difference from x86 of course, but there might be different baseline memory consumption for different architectures.
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