Re: [PATCH] Incremental sort - Mailing list pgsql-hackers

From Alexander Korotkov
Subject Re: [PATCH] Incremental sort
Date
Msg-id CAPpHfdsnMTL4V57eutAt68ZeA7d4N-eWfthcXY=2PK0P5iU+kw@mail.gmail.com
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In response to Re: [HACKERS] [PATCH] Incremental sort  (Heikki Linnakangas <hlinnaka@iki.fi>)
List pgsql-hackers
On Mon, Mar 20, 2017 at 5:19 PM, Heikki Linnakangas <hlinnaka@iki.fi> wrote:
On 03/20/2017 11:33 AM, Alexander Korotkov wrote:
Please, find rebased patch in the attachment.

I had a quick look at this.

* I'd love to have an explanation of what an Incremental Sort is, in the file header comment for nodeIncrementalSort.c.
 
Done.

* I didn't understand the maxMem stuff in tuplesort.c. The comments there use the phrase "on-disk memory", which seems like an oxymoron. Also, "maximum status" seems weird, as it assumes that there's a natural order to the states.
 
Variables were renamed.

* In the below example, the incremental sort is significantly slower than the Seq Scan + Sort you get otherwise:

create table foo (a int4, b int4, c int4);
insert into sorttest select g, g, g from generate_series(1, 1000000) g;
vacuum foo;
create index i_sorttest on sorttest (a, b, c);
set work_mem='100MB';


postgres=# explain select count(*) from (select * from sorttest order by a, c) as t;
                                              QUERY PLAN
-------------------------------------------------------------------------------------------------------
 Aggregate  (cost=138655.68..138655.69 rows=1 width=8)
   ->  Incremental Sort  (cost=610.99..124870.38 rows=1102824 width=12)
         Sort Key: sorttest.a, sorttest.c
         Presorted Key: sorttest.a
         ->  Index Only Scan using i_sorttest on sorttest (cost=0.43..53578.79 rows=1102824 width=12)
(5 rows)

Time: 0.409 ms
postgres=# select count(*) from (select * from sorttest order by a, c) as t;
  count
---------
 1000000
(1 row)

Time: 387.091 ms


postgres=# explain select count(*) from (select * from sorttest order by a, c) as t;
                                  QUERY PLAN
-------------------------------------------------------------------------------
 Aggregate  (cost=130063.84..130063.85 rows=1 width=8)
   ->  Sort  (cost=115063.84..117563.84 rows=1000000 width=12)
         Sort Key: sorttest.a, sorttest.c
         ->  Seq Scan on sorttest  (cost=0.00..15406.00 rows=1000000 width=12)
(4 rows)

Time: 0.345 ms
postgres=# select count(*) from (select * from sorttest order by a, c) as t;
  count
---------
 1000000
(1 row)

Time: 231.668 ms

According to 'perf', 85% of the CPU time is spent in ExecCopySlot(). To alleviate that, it might be worthwhile to add a special case for when the group contains exactly one group, and not put the tuple to the tuplesort in that case.

I'm not sure we should do such optimization for one tuple per group, since it's similar situation with 2 or 3 tuples per group.
 
Or if we cannot ensure that the Incremental Sort is actually faster, the cost model should probably be smarter, to avoid picking an incremental sort when it's not a win.

I added to cost_sort() extra costing for incremental sort: cost of extra tuple copying and comparing as well as cost of tuplesort reset.
The only problem is that I made following estimate for tuplesort reset:

run_cost += 10.0 * cpu_tuple_cost * num_groups;

It makes ordinal sort to be selected in your example, but it contains constant 10 which is quite arbitrary.  It would be nice to evade such hard coded constants, but I don't know how could we calculate such cost realistically.

------
Alexander Korotkov
Postgres Professional: http://www.postgrespro.com
The Russian Postgres Company
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