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v0.12.4 consumes 8GB RAM on startup after building with or without jemalloc on production grade server #3107

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jcstein opened this issue Jan 16, 2024 · 6 comments
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bug Something isn't working external Issues created by non node team members

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@jcstein
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jcstein commented Jan 16, 2024

Celestia Node version

v0.12.4

OS

ubuntu, production grade server

Install tools

No response

Others

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Steps to reproduce it

Run light node

Expected result

Syncs using under 500 MB RAM as per documentation

Actual result

Uses 8GB RAM on startup, with and without jemalloc

Relevant log output

No response

Notes

Originally reported in celestia-da rollkit/celestia-da#35 (comment)

@jcstein jcstein added the bug Something isn't working label Jan 16, 2024
@github-actions github-actions bot added the external Issues created by non node team members label Jan 16, 2024
@jcstein
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jcstein commented Jan 16, 2024

cc @tuxcanfly and @mycodecrafting for visibility on the issue

@jcstein jcstein changed the title v0.12.4 consumes 8GB RAM on startup after building with or without jemalloc v0.12.4 consumes 8GB RAM on startup after building with or without jemalloc on production grade server Jan 16, 2024
@mycodecrafting
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some added info.

OS: Ubuntu 20.04.6 LTS
Arch type: x86_64

Build and install following guide here: https://docs.celestia.org/nodes/celestia-node

Go version: go1.21.1 linux/amd64

celestia built version

Semantic version: v0.12.4
Commit: 8e5a71746bc9bd9300ad3e4853797e64fdd1d018
Build Date: Tue 16 Jan 2024 08:26:39 PM UTC
System version: amd64/linux
Golang version: go1.21.1

@tuxcanfly
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Attaching heap snapshots from @mycodecrafting collected at 1m intervals.

heap-snapshots.tar.gz

@jcstein
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jcstein commented Jan 17, 2024

from @mycodecrafting: Ubuntu server and mem usage on celestia-node has grown to 18.6G overnight

@Wondertan Wondertan self-assigned this Jan 17, 2024
@Wondertan
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Does this run over an clean node or synced node?

@Wondertan
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After debugging this closely with @mycodecrafting, my conclusion is that the issue is a false alarm:

If we ever find an OOM and an ever-growing heap, then we can revisit the conclusion with more data points,
but until then, there is nothing to worry about as the node works and behaves correctly.

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