Re: [HACKERS] Moving relation extension locks out of heavyweight lock manager

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От Mahendra Singh Thalor
Тема Re: [HACKERS] Moving relation extension locks out of heavyweight lock manager
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Msg-id CAKYtNAre3w8DNo7=Kcg7Pt3hZ6_YJ-Fb7_kBFk9BxOks9vSvNQ@mail.gmail.com
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Ответ на Re: [HACKERS] Moving relation extension locks out of heavyweight lock manager  (Mahendra Singh Thalor <mahi6run@gmail.com>)
Ответы Re: [HACKERS] Moving relation extension locks out of heavyweight lock manager  (Amit Kapila <amit.kapila16@gmail.com>)
Список pgsql-hackers
On Sat, 8 Feb 2020 at 00:27, Mahendra Singh Thalor <mahi6run@gmail.com> wrote:
>
> On Thu, 6 Feb 2020 at 09:44, Amit Kapila <amit.kapila16@gmail.com> wrote:
> >
> > On Thu, Feb 6, 2020 at 1:57 AM Mahendra Singh Thalor <mahi6run@gmail.com> wrote:
> > >
> > > On Wed, 5 Feb 2020 at 12:07, Masahiko Sawada <sawada.mshk@gmail.com> wrote:
> > > >
> > > > On Mon, Feb 3, 2020 at 8:03 PM Amit Kapila <amit.kapila16@gmail.com> wrote:
> > > > >
> > > > > On Tue, Jun 26, 2018 at 12:47 PM Masahiko Sawada <sawada.mshk@gmail.com> wrote:
> > > > > >
> > > > > > On Fri, Apr 27, 2018 at 4:25 AM, Robert Haas <robertmhaas@gmail.com> wrote:
> > > > > > > On Thu, Apr 26, 2018 at 3:10 PM, Andres Freund <andres@anarazel.de> wrote:
> > > > > > >>> I think the real question is whether the scenario is common enough to
> > > > > > >>> worry about.  In practice, you'd have to be extremely unlucky to be
> > > > > > >>> doing many bulk loads at the same time that all happened to hash to
> > > > > > >>> the same bucket.
> > > > > > >>
> > > > > > >> With a bunch of parallel bulkloads into partitioned tables that really
> > > > > > >> doesn't seem that unlikely?
> > > > > > >
> > > > > > > It increases the likelihood of collisions, but probably decreases the
> > > > > > > number of cases where the contention gets really bad.
> > > > > > >
> > > > > > > For example, suppose each table has 100 partitions and you are
> > > > > > > bulk-loading 10 of them at a time.  It's virtually certain that you
> > > > > > > will have some collisions, but the amount of contention within each
> > > > > > > bucket will remain fairly low because each backend spends only 1% of
> > > > > > > its time in the bucket corresponding to any given partition.
> > > > > > >
> > > > > >
> > > > > > I share another result of performance evaluation between current HEAD
> > > > > > and current HEAD with v13 patch(N_RELEXTLOCK_ENTS = 1024).
> > > > > >
> > > > > > Type of table: normal table, unlogged table
> > > > > > Number of child tables : 16, 64 (all tables are located on the same tablespace)
> > > > > > Number of clients : 32
> > > > > > Number of trials : 100
> > > > > > Duration: 180 seconds for each trials
> > > > > >
> > > > > > The hardware spec of server is Intel Xeon 2.4GHz (HT 160cores), 256GB
> > > > > > RAM, NVMe SSD 1.5TB.
> > > > > > Each clients load 10kB random data across all partitioned tables.
> > > > > >
> > > > > > Here is the result.
> > > > > >
> > > > > >  childs |   type   | target  |  avg_tps   | diff with HEAD
> > > > > > --------+----------+---------+------------+------------------
> > > > > >      16 | normal   | HEAD    |   1643.833 |
> > > > > >      16 | normal   | Patched |  1619.5404 |      0.985222
> > > > > >      16 | unlogged | HEAD    |  9069.3543 |
> > > > > >      16 | unlogged | Patched |  9368.0263 |      1.032932
> > > > > >      64 | normal   | HEAD    |   1598.698 |
> > > > > >      64 | normal   | Patched |  1587.5906 |      0.993052
> > > > > >      64 | unlogged | HEAD    |  9629.7315 |
> > > > > >      64 | unlogged | Patched | 10208.2196 |      1.060073
> > > > > > (8 rows)
> > > > > >
> > > > > > For normal tables, loading tps decreased 1% ~ 2% with this patch
> > > > > > whereas it increased 3% ~ 6% for unlogged tables. There were
> > > > > > collisions at 0 ~ 5 relation extension lock slots between 2 relations
> > > > > > in the 64 child tables case but it didn't seem to affect the tps.
> > > > > >
> > > > >
> > > > > AFAIU, this resembles the workload that Andres was worried about.   I
> > > > > think we should once run this test in a different environment, but
> > > > > considering this to be correct and repeatable, where do we go with
> > > > > this patch especially when we know it improves many workloads [1] as
> > > > > well.  We know that on a pathological case constructed by Mithun [2],
> > > > > this causes regression as well.  I am not sure if the test done by
> > > > > Mithun really mimics any real-world workload as he has tested by
> > > > > making N_RELEXTLOCK_ENTS = 1 to hit the worst case.
> > > > >
> > > > > Sawada-San, if you have a script or data for the test done by you,
> > > > > then please share it so that others can also try to reproduce it.
> > > >
> > > > Unfortunately the environment I used for performance verification is
> > > > no longer available.
> > > >
> > > > I agree to run this test in a different environment. I've attached the
> > > > rebased version patch. I'm measuring the performance with/without
> > > > patch, so will share the results.
> > > >
> > >
> > > Thanks Sawada-san for patch.
> > >
> > > From last few days, I was reading this thread and was reviewing v13 patch.  To debug and test, I did re-base of v13 patch. I compared my re-based patch and v14 patch. I think,  ordering of header files is not alphabetically in v14 patch. (I haven't reviewed v14 patch fully because before review, I wanted to test false sharing).  While debugging, I didn't noticed any hang or lock related issue.
> > >
> > > I did some testing to test false sharing(bulk insert, COPY data, bulk insert into partitions tables).  Below is the testing summary.
> > >
> > > Test setup(Bulk insert into partition tables):
> > > autovacuum=off
> > > shared_buffers=512MB -c max_wal_size=20GB -c checkpoint_timeout=12min
> > >
> > > Basically, I created a table with 13 partitions. Using pgbench, I inserted bulk data. I used below pgbench command:
> > > ./pgbench -c $threads -j $threads -T 180 -f insert1.sql@1 -f insert2.sql@1 -f insert3.sql@1 -f insert4.sql@1 postgres
> > >
> > > I took scripts from previews mails and modified. For reference, I am attaching test scripts.  I tested with default 1024 slots(N_RELEXTLOCK_ENTS = 1024).
> > >
> > > Clients          HEAD (tps)                     With v14 patch (tps)      %change      (time: 180s)
> > > 1                    92.979796                        100.877446                     +8.49 %
> > > 32                   392.881863                      388.470622                    -1.12 %
> > > 56                   551.753235                       528.018852                   -4.30 %
> > > 60                   648.273767                       653.251507                   +0.76 %
> > > 64                   645.975124                       671.322140                   +3.92 %
> > > 66                   662.728010                       673.399762                   +1.61 %
> > > 70                   647.103183                       660.694914                   +2.10 %
> > > 74                   648.824027                       676.487622                  +4.26 %
> > >
> > > From above results, we can see that in most cases, TPS is slightly increased with v14 patch. I am still testing and will post my results.
> > >
> >
> > The number at 56 and 74 client count seem slightly suspicious.   Can
> > you please repeat those tests?  Basically, I am not able to come up
> > with a theory why at 56 clients the performance with the patch is a
> > bit lower and then at 74 it is higher.
>
> Okay. I will repeat test.

I re-tested in different machine because in previous machine, results are  in-consistent

My testing machine:
$ lscpu
Architecture:          ppc64le
Byte Order:            Little Endian
CPU(s):                192
On-line CPU(s) list:   0-191
Thread(s) per core:    8
Core(s) per socket:    1
Socket(s):             24
NUMA node(s):          4
Model:                 IBM,8286-42A
L1d cache:             64K
L1i cache:             32K
L2 cache:              512K
L3 cache:              8192K
NUMA node0 CPU(s):     0-47
NUMA node1 CPU(s):     48-95
NUMA node2 CPU(s):     96-143
NUMA node3 CPU(s):     144-191

./pgbench -c $threads -j $threads -T 180 -f insert1.sql@1 -f insert2.sql@1 -f insert3.sql@1 -f insert4.sql@1 postgres

Clients        HEAD(tps)            With v14 patch(tps)        %change       (time: 180s)
1                 41.491486              41.375532                  -0.27%
32              335.138568            330.028739                 -1.52%
56             353.783930             360.883710                  +2.00%
60             341.741925             359.028041                 +5.05%
64             338.521730             356.511423                  +5.13%
66             339.838921             352.761766                  +3.80%
70            339.305454              353.658425                +4.23%
74            332.016217              348.809042                 +5.05%       

From above results, it seems that there is very little regression with the patch(+-5%) that can be run to run variation.

>
> >
> > > I want to test extension lock by blocking use of fsm(use_fsm=false in code).  I think, if we block use of fsm, then load will increase into extension lock.  Is this correct way to test?
> > >
> >
> > Hmm, I think instead of directly hacking the code, you might want to
> > use the operation (probably cluster or vacuum full) where we set
> > HEAP_INSERT_SKIP_FSM.  I think along with this you can try with
> > unlogged tables because that might stress the extension lock.
>
> Okay. I will test.

I tested with unlogged tables also.  There also I was getting 3-6% gain in tps.

>
> >
> > In the above test, you might want to test with a higher number of
> > partitions (say up to 100) as well.  Also, see if you want to use the
> > Copy command.
>
> Okay. I will test.

I tested with 500, 1000, 2000 paratitions. I observed max +5% regress in the tps and there was no performace degradation.

For example:
I created a table with 2000 paratitions and then I checked false sharing.
Slot NumberSlot Freq.Slot NumberSlot Freq.Slot NumberSlot Freq.
156139731144610
62713521048810
782121031050110
812121131070110
192111751073710
221112351075410
367112541078110
546113141079010
814114191083310
917114241088810

From above table, we can see that total 13 child tables are falling in same backet (slot 156) so I did bulk-loading only in those 13 child tables to check tps in false sharing but I noticed that there was no performance degradation.

--
Thanks and Regards
Mahendra Singh Thalor
EnterpriseDB: http://www.enterprisedb.com

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