Re: Speed up Clog Access by increasing CLOG buffers
| От | Amit Kapila |
|---|---|
| Тема | Re: Speed up Clog Access by increasing CLOG buffers |
| Дата | |
| Msg-id | CAA4eK1L4iV-2qe7AyMVsb+nz7SiX8JvCO+CqhXwaiXgm3CaBUw@mail.gmail.com обсуждение исходный текст |
| Ответ на | Re: Speed up Clog Access by increasing CLOG buffers (Robert Haas <robertmhaas@gmail.com>) |
| Ответы |
Re: Speed up Clog Access by increasing CLOG buffers
|
| Список | pgsql-hackers |
On Tue, Feb 23, 2016 at 7:06 PM, Robert Haas <robertmhaas@gmail.com> wrote:
On Sun, Feb 21, 2016 at 7:45 PM, Amit Kapila <amit.kapila16@gmail.com> wrote:I mean, my basic feeling is that I would not accept a 2-3% regression in the single client case to get a 10% speedup in the case where we have 128 clients.
When I tried by running the pgbench first with patch and then with Head, I see 1.2% performance increase with patch. TPS with patch is 976 and with Head it is 964. For 3, 30 mins TPS data, refer "Patch – group_clog_update_v5" and before that "HEAD – Commit 481725c0" in perf_write_clogcontrollock_data_v6.ods attached with this mail.
Nonetheless, I have observed that below new check has been added by the patch which can effect single client performance. So I have changed it such that new check is done only when we there is actually a need of group update which means when multiple clients tries to update clog at-a-time.
+ if (!InRecovery &&
+ all_trans_same_page &&
+ nsubxids < PGPROC_MAX_CACHED_SUBXIDS &&
+ !IsGXactActive())
I understand your point. I think to verify whether it is run-to-runvariation or an actual regression, I will re-run these tests on singleclient multiple times and post the result.Perhaps you could also try it on a couple of different machines (e.g. MacBook Pro and a couple of different large servers).
Okay, I have tried latest patch (group_update_clog_v6.patch) on 2 different big servers and then on Mac-Pro. The detailed data for various runs can be found in attached document perf_write_clogcontrollock_data_v6.ods. I have taken the performance data for higher client-counts with somewhat larger scale factor (1000) and data for median of same is as below:
M/c configuration
-----------------------------
RAM - 500GB
8 sockets, 64 cores(Hyperthreaded128 threads total)
Non-default parameters
------------------------------------
max_connections = 1000
shared_buffers=32GB
min_wal_size=10GB
max_wal_size=15GB
checkpoint_timeout =35min
maintenance_work_mem = 1GB
checkpoint_completion_target = 0.9
wal_buffers = 256MB
| Client_Count/Patch_ver | 1 | 8 | 64 | 128 | 256 |
| HEAD | 871 | 5090 | 17760 | 17616 | 13907 |
| PATCH | 900 | 5110 | 18331 | 20277 | 19263 |
Here, we can see that there is a gain of ~15% to ~38% at higher client count.
The attached document (perf_write_clogcontrollock_data_v6.ods) contains data, mainly focussing on single client performance. The data is for multiple runs on different machines, so I thought it is better to present in form of document rather than dumping everything in e-mail. Do let me know if there is any confusion in understanding/interpreting the data.
Thanks to Dilip Kumar for helping me in conducting test of this patch on MacBook-Pro.
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