MySQL Community · The edge cases the MySQL docs never spell out

406
Myr/mysql·posted by bob_chen·just nowTutorial

The edge cases the MySQL docs never spell out

Most MySQL articles stop at "how to use it" and never cover "when not to use it". This is an attempt at the second half.

What genuinely surprised me was the tail. The average looked great while P99 jumped by an order of magnitude past some threshold. The cause was not MySQL itself but our upstream connection reuse — the load test traffic was too clean and hid the long-tail requests.

Documentation first44%
Source code first28%
Just ask someone17%
Run a demo and learn by error11%

690 votes total

62 comments

62 comments

M
Kkernel_panic·2 days agoedited

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

447
Mmike_xu·2 days ago

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

35
Llinlin·5 hours 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.

446
Mmike_xu·2 days ago

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

385
Rrase·2 days ago

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.

105
Rrase·2 days agoedited

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.

41
Sslow_query·2 days 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.

260
Oops_wang·2 days ago

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

41
Zzhou_yiOP·28 minutes 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.

296
Ttang_hao·just now

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.

287
Llinlin·12 minutes 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.

478
Kkernel_panic·2 days ago

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

65
Wwinter·2 days agoedited

One counter-example: below MySQL 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_chen·2 days ago

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

278
Llinlin·2 days ago

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

263
Cchen_devOP·2 days ago

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

181
Hhuang_ke·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.

219
Ddev_zhou·12 minutes ago

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

192
Zzhu_zong·1 hour 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.

3
Mmike_xu·2 days 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.

188
Aalice_dev·3 minutes ago

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

151
Aalice_dev·yesterday

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.

77
Hhuang_ke·2 days ago

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

75
Rran_bo·2 days ago

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

66
Sswoole_lee·2 days 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.

57
Rran_bo·2 days 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.

47
Ttang_hao·2 days agoedited

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

247
Zzhou_yi·just now

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

40
Mmike_xu·2 hours ago

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

201
LlinlinOP·just now

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

1
Sslow_query·2 days ago

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

1
Mmike_xuMod·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.

17
Sswoole_lee·2 days 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.

420
Ttang_hao·2 days ago

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

82
Sslow_query·yesterday

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

209
Bbob_chen·2 days ago

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

175
Kkite·12 minutes agoedited

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

11
Sswoole_lee·just now

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.

9
Rrase·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.

7
Zzhu_zong·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.

6
Rran_bo·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.

53
Aalice_dev·2 days ago

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

125
Bbob_chen·1 hour ago

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

6
Aalice_dev·3 minutes ago

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

464
Zzhu_zongOPMod·2 days ago

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.

394
Wwinter·yesterday

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.

350
Lli_ming·2 days 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.

142
Sswoole_lee·3 minutes agoLevel 6

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

407
Kkite·2 days agoLevel 6

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.

62
Kkite·2 days ago

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

115
Zzhu_zong·2 days agoLevel 6

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

101
Kkernel_panic·2 days ago

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

184
Oops_wang·2 days ago

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

82
Sslow_query·2 hours agoLevel 6

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.

1
Lli_ming·yesterday

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.

101
Rrase·2 days ago

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

209
Cchen_devMod·2 days agoedited

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

230
Kkernel_panic·5 hours 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.

6
Llinlin·2 days ago

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

5
Hhuang_ke·2 days ago

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
Ddev_zhou·yesterday

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

1
Kkite·yesterday

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.

1

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