Modding · Reading list · Why does modding-books use twice the memory of comparable tools?

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MOr/modding-books·posted by zhou_yi·2 hours agoTutorialLocked

Why does modding-books use twice the memory of comparable tools?

Short version: modding-books needs almost no tuning at small and medium scale — the point where it starts to hurt is much further out than most people assume. Full measurements below.

# Load test: do not jump straight to the max concurrency.
# Ramp it up, otherwise you miss the knee.
for c in 50 100 200 400 800; do
  wrk -t8 -c$c -d60s --latency http://127.0.0.1:8080/api/feed
  sleep 20
done

On trade-offs, my view is this: if nobody on the team owns this area long-term, do not introduce a second mechanism. With two coexistence you first have to work out which one is even in play when things break, and that costs far more than the performance you saved.

One last trap: in container environments remember to adjust the memory-related parameters in step. Otherwise the host limit and the process expectation disagree, and the symptom is intermittent, unreproducible failure.

The first thing was to collapse the variables. We were changing config and upgrading the version at the same time, and afterwards nobody could say which change caused what. We rolled back to moving one variable at a time, re-ran three times, and only then did the curve settle. Tedious, but not skippable.

18 comments

18 comments

M
Kkernel_panic·5 hours agoedited

I just read the modding-books source — the author actually explains the reasoning in a comment, roughly "so that it degrades into predictable behaviour in extreme cases".

475
Lli_ming·12 minutes ago

A question: what changes in a container with a 512Mi memory limit? That is how we run it in production.

445
Sslow_query·2 days ago

I see point 3 differently. The trade-off depends on your read/write ratio: read-heavy with little writing means caching actually widens the inconsistency window.

1
Rran_bo·12 minutes ago

This is not a modding-books problem, it is a usage problem. The docs say this API is not thread-safe and you must lock around it yourself.

466
Aalice_dev·just now

This matches what we see in production. We only hit it past 3k QPS; the earlier load tests showed nothing — the test traffic was too clean, with no long-tail requests.

209
Oops_wangOP·28 minutes ago

Sharing our numbers, 8 cores 16GB, same scenario:

| Concurrency | P50 | P99 |
|---|---|---|
| 200 | 12ms | 88ms |
| 500 | 31ms | 340ms |

P99 clearly collapses at 500 concurrency, which lines up with your knee point.

218
Ttang_haoOP·2 hours ago

Worth learning from this debugging approach. We went straight at the logs and took a much longer route.

173
Llinlin·2 days ago

This matches what we see in production. We only hit it past 3k QPS; the earlier load tests showed nothing — the test traffic was too clean, with no long-tail requests.

10
Ttang_hao·just now

Has anyone run a controlled experiment? I did, reducing it to a single variable, and the difference was 4% — within noise. So I suspect the main cause is something else.

1
Zzhou_yi·2 days ago

Worth learning from this debugging approach. We went straight at the logs and took a much longer route.

134
Ddev_zhou·12 minutes ago

We have run this in production for two years without hitting it. That said, we never reached this scale, so our experience is not really evidence here.

49
Aalice_dev·2 days ago

Saved. I am reworking this area this week — this saves a lot of wrong turns.

9
Wwinter·3 minutes ago

There is actually a simpler fix that needs no architecture change: move this check up to the gateway and the problem disappears. The cost is one extra lookup at the gateway.

200
Nnikic·12 minutes ago

Can you give a minimal reproduction? I ran it locally for ten minutes and could not reproduce on macOS with the latest version.

129
Kkite·12 minutes ago

One counter-example: below modding-books 7.4 the semantics of that code are different, so do not copy it verbatim. We got burned in staging and rolled back once.

1
Bbob_chenMod·3 minutes ago

Thanks for sharing real numbers — far more useful than the articles that only cover concepts.

78
Hhuang_ke·1 hour ago

Agreeing with the above. One addition: with this option enabled the GC count in your metrics doubles, so adjust the alert threshold at the same time or it will keep firing.

17
Sswoole_lee·just nowedited

Sharing our numbers, 8 cores 16GB, same scenario:

| Concurrency | P50 | P99 |
|---|---|---|
| 200 | 12ms | 88ms |
| 500 | 31ms | 340ms |

P99 clearly collapses at 500 concurrency, which lines up with your knee point.

4

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