From: | Stepan Neretin <sncfmgg(at)gmail(dot)com> |
---|---|
To: | Антуан Виолин <violin(dot)antuan(at)gmail(dot)com> |
Cc: | "Andrey M(dot) Borodin" <x4mmm(at)yandex-team(dot)ru>, PostgreSQL Hackers <pgsql-hackers(at)postgresql(dot)org> |
Subject: | Re: Sort functions with specialized comparators |
Date: | 2024-07-15 10:47:32 |
Message-ID: | CAN-sa+B4eb7_ktRotUXMnfGHFNEdj3yy6Ta_c5vJevFHPhsprg@mail.gmail.com |
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Thread: | |
Lists: | pgsql-hackers |
On Mon, Jul 15, 2024 at 4:52 PM Stepan Neretin <sncfmgg(at)gmail(dot)com> wrote:
>
>
> On Mon, Jul 15, 2024 at 12:23 PM Антуан Виолин <violin(dot)antuan(at)gmail(dot)com>
> wrote:
>
>> Hello all.
>>>
>>> I have decided to explore more areas in which I can optimize and have
>>> added
>>> two new benchmarks. Do you have any thoughts on this?
>>>
>>> postgres=# select bench_int16_sort(1000000);
>>> bench_int16_sort
>>>
>>>
>>> -----------------------------------------------------------------------------------------------------------------
>>> Time taken by usual sort: 66354981 ns, Time taken by optimized sort:
>>> 52151523 ns, Percentage difference: 21.41%
>>> (1 row)
>>>
>>> postgres=# select bench_float8_sort(1000000);
>>> bench_float8_sort
>>>
>>>
>>> ------------------------------------------------------------------------------------------------------------------
>>> Time taken by usual sort: 121475231 ns, Time taken by optimized sort:
>>> 74458545 ns, Percentage difference: 38.70%
>>> (1 row)
>>>
>>
>> Hello all
>> We would like to see the relationship between the length of the sorted
>> array and the performance gain, perhaps some graphs. We also want to see
>> to set a "worst case" test, sorting the array in ascending order when it
>> is initially descending
>>
>> Best, regards, Antoine Violin
>>
>> postgres=#
>>>
>>
>> On Mon, Jul 15, 2024 at 10:32 AM Stepan Neretin <sncfmgg(at)gmail(dot)com>
>> wrote:
>>
>>>
>>>
>>> On Sat, Jun 8, 2024 at 1:50 AM Stepan Neretin <sncfmgg(at)gmail(dot)com> wrote:
>>>
>>>> Hello all.
>>>>
>>>> I am interested in the proposed patch and would like to propose some
>>>> additional changes that would complement it. My changes would introduce
>>>> similar optimizations when working with a list of integers or object
>>>> identifiers. Additionally, my patch includes an extension for
>>>> benchmarking, which shows an average speedup of 30-40%.
>>>>
>>>> postgres=# SELECT bench_oid_sort(1000000);
>>>> bench_oid_sort
>>>>
>>>>
>>>> ----------------------------------------------------------------------------------------------------------------
>>>> Time taken by list_sort: 116990848 ns, Time taken by list_oid_sort:
>>>> 80446640 ns, Percentage difference: 31.24%
>>>> (1 row)
>>>>
>>>> postgres=# SELECT bench_int_sort(1000000);
>>>> bench_int_sort
>>>>
>>>>
>>>> ----------------------------------------------------------------------------------------------------------------
>>>> Time taken by list_sort: 118168506 ns, Time taken by list_int_sort:
>>>> 80523373 ns, Percentage difference: 31.86%
>>>> (1 row)
>>>>
>>>> What do you think about these changes?
>>>>
>>>> Best regards, Stepan Neretin.
>>>>
>>>> On Fri, Jun 7, 2024 at 11:08 PM Andrey M. Borodin <x4mmm(at)yandex-team(dot)ru>
>>>> wrote:
>>>>
>>>>> Hi!
>>>>>
>>>>> In a thread about sorting comparators[0] Andres noted that we have
>>>>> infrastructure to help compiler optimize sorting. PFA attached PoC
>>>>> implementation. I've checked that it indeed works on the benchmark from
>>>>> that thread.
>>>>>
>>>>> postgres=# CREATE TABLE arrays_to_sort AS
>>>>> SELECT array_shuffle(a) arr
>>>>> FROM
>>>>> (SELECT ARRAY(SELECT generate_series(1, 1000000)) a),
>>>>> generate_series(1, 10);
>>>>>
>>>>> postgres=# SELECT (sort(arr))[1] FROM arrays_to_sort; -- original
>>>>> Time: 990.199 ms
>>>>> postgres=# SELECT (sort(arr))[1] FROM arrays_to_sort; -- patched
>>>>> Time: 696.156 ms
>>>>>
>>>>> The benefit seems to be on the order of magnitude with 30% speedup.
>>>>>
>>>>> There's plenty of sorting by TransactionId, BlockNumber, OffsetNumber,
>>>>> Oid etc. But this sorting routines never show up in perf top or something
>>>>> like that.
>>>>>
>>>>> Seems like in most cases we do not spend much time in sorting. But
>>>>> specialization does not cost us much too, only some CPU cycles of a
>>>>> compiler. I think we can further improve speedup by converting inline
>>>>> comparator to value extractor: more compilers will see what is actually
>>>>> going on. But I have no proofs for this reasoning.
>>>>>
>>>>> What do you think?
>>>>>
>>>>>
>>>>> Best regards, Andrey Borodin.
>>>>>
>>>>> [0]
>>>>> https://www.postgresql.org/message-id/flat/20240209184014.sobshkcsfjix6u4r%40awork3.anarazel.de#fc23df2cf314bef35095b632380b4a59
>>>>
>>>>
>>> Hello all.
>>>
>>> I have decided to explore more areas in which I can optimize and have
>>> added two new benchmarks. Do you have any thoughts on this?
>>>
>>> postgres=# select bench_int16_sort(1000000);
>>> bench_int16_sort
>>>
>>>
>>> -----------------------------------------------------------------------------------------------------------------
>>> Time taken by usual sort: 66354981 ns, Time taken by optimized sort:
>>> 52151523 ns, Percentage difference: 21.41%
>>> (1 row)
>>>
>>> postgres=# select bench_float8_sort(1000000);
>>> bench_float8_sort
>>>
>>>
>>> ------------------------------------------------------------------------------------------------------------------
>>> Time taken by usual sort: 121475231 ns, Time taken by optimized sort:
>>> 74458545 ns, Percentage difference: 38.70%
>>> (1 row)
>>>
>>> postgres=#
>>>
>>> Best regards, Stepan Neretin.
>>>
>>
>
> I run benchmark with my patches:
> ./pgbench -c 10 -j2 -t1000 -d postgres
>
> pgbench (18devel)
> starting vacuum...end.
> transaction type: <builtin: TPC-B (sort of)>
> scaling factor: 10
> query mode: simple
> number of clients: 10
> number of threads: 2
> maximum number of tries: 1
> number of transactions per client: 1000
> number of transactions actually processed: 10000/10000
> number of failed transactions: 0 (0.000%)
> latency average = 1.609 ms
> initial connection time = 24.080 ms
> tps = 6214.244789 (without initial connection time)
>
> and without:
> ./pgbench -c 10 -j2 -t1000 -d postgres
>
> pgbench (18devel)
> starting vacuum...end.
> transaction type: <builtin: TPC-B (sort of)>
> scaling factor: 10
> query mode: simple
> number of clients: 10
> number of threads: 2
> maximum number of tries: 1
> number of transactions per client: 1000
> number of transactions actually processed: 10000/10000
> number of failed transactions: 0 (0.000%)
> latency average = 1.731 ms
> initial connection time = 15.177 ms
> tps = 5776.173285 (without initial connection time)
>
> tps with my patches increase. What do you think?
>
> Best regards, Stepan Neretin.
>
I implement reverse benchmarks:
postgres=# SELECT bench_oid_reverse_sort(1000);
bench_oid_reverse_sort
----------------------------------------------------------------------------------------------------------
Time taken by list_sort: 182557 ns, Time taken by list_oid_sort: 85864 ns,
Percentage difference: 52.97%
(1 row)
Time: 2,291 ms
postgres=# SELECT bench_oid_reverse_sort(100000);
bench_oid_reverse_sort
-------------------------------------------------------------------------------------------------------------
Time taken by list_sort: 9064163 ns, Time taken by list_oid_sort: 4313448
ns, Percentage difference: 52.41%
(1 row)
Time: 17,146 ms
postgres=# SELECT bench_oid_reverse_sort(1000000);
bench_oid_reverse_sort
---------------------------------------------------------------------------------------------------------------
Time taken by list_sort: 61990395 ns, Time taken by list_oid_sort:
23703380 ns, Percentage difference: 61.76%
(1 row)
postgres=# SELECT bench_int_reverse_sort(1000000);
bench_int_reverse_sort
---------------------------------------------------------------------------------------------------------------
Time taken by list_sort: 50712416 ns, Time taken by list_int_sort:
24120417 ns, Percentage difference: 52.44%
(1 row)
Time: 89,359 ms
postgres=# SELECT bench_float8_reverse_sort(1000000);
bench_float8_reverse_sort
-----------------------------------------------------------------------------------------------------------------
Time taken by usual sort: 57447775 ns, Time taken by optimized sort:
25214023 ns, Percentage difference: 56.11%
(1 row)
Time: 92,308 ms
Hello again. I want to show you the graphs of when we increase the length
vector/array sorting time (ns). What do you think about graphs?
Best regards, Stepan Neretin.
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