Re: GroupAggregate and Integer Arrays - Mailing list pgsql-performance

Hi,

Wondering if anyone could suggest how we could improve the performance of this type of query?

The intensive part is the summing of integer arrays as far as I can see.

We're thinking there's not much we can do to improve performance apart from throw more CPU at it... would love to be proven wrong though!

Query:

  explain (analyse,buffers) 

  select 

  sum(s2.array_a),sum(s2.array_b)

  from mytable s1 left join mytable s2

  on s1.code=s2.code and s1.buyer=s2.seller and s2.seller='XX'

  where s1.buyer='XX'

  group by s1.buyer,s1.code

;

Depesz Explain Link:

http://explain.depesz.com/s/m3XP

                                                                               QUERY PLAN                                                                               

------------------------------------------------------------------------------------------------------------------------------------------------------------------------

 GroupAggregate  (cost=275573.49..336223.36 rows=2547 width=524) (actual time=1059.340..22946.772 rows=22730 loops=1)

   Buffers: shared hit=113596 read=1020 dirtied=15

   ->  Merge Left Join  (cost=275573.49..278850.09 rows=113560 width=524) (actual time=1058.773..1728.186 rows=240979 loops=1)

         Merge Cond: ((s1.code)::text = (s2.code)::text)

         Join Filter: (s1.buyer = (s2.seller)::bpchar)

         Buffers: shared hit=113596 read=1020 dirtied=15

         ->  Index Only Scan using mytable_buyer_idx on mytable s1  (cost=0.42..1226.06 rows=25465 width=12) (actual time=0.015..35.790 rows=22730 loops=1)

               Index Cond: (buyer = 'XX'::bpchar)

               Heap Fetches: 3739

               Buffers: shared hit=16805 dirtied=1

         ->  Sort  (cost=275573.07..275818.33 rows=98106 width=525) (actual time=1058.736..1141.560 rows=231662 loops=1)

               Sort Key: s2.code

               Sort Method: quicksort  Memory: 241426kB

               Buffers: shared hit=96791 read=1020 dirtied=14

               ->  Bitmap Heap Scan on mytable s2  (cost=12256.28..267439.07 rows=98106 width=525) (actual time=60.330..325.730 rows=231662 loops=1)

                     Recheck Cond: ((seller)::text = 'XX'::text)

                     Filter: ((seller)::bpchar = 'XX'::bpchar)

                     Buffers: shared hit=96791 read=1020 dirtied=14

                     ->  Bitmap Index Scan on mytable_seller_idx  (cost=0.00..12231.75 rows=254844 width=0) (actual time=40.474..40.474 rows=233244 loops=1)

                           Index Cond: ((seller)::text = 'XX'::text)

                           Buffers: shared hit=30 read=1020

 Total runtime: 22968.292 ms

(22 rows)

Table size:

=> select count(*) from mytable;

 count  

--------

 602669

(1 row)

Array types:

# select array_a,array_b from mytable limit 1;

      array_a      |     array_b      

---------------------------+---------------------------

 {0,0,0,0,0,0,0,0,0,0,0,0} | {0,0,0,0,0,0,0,0,0,0,0,0}

Example schema:

# \d mytable

                        Table "public.mytable"

      Column       |         Type          |       Modifiers        

-------------------+-----------------------+------------------------

 buyer             | character(2)          | not null

 code              | character varying(20) | not null

 seller            | character varying(50) | 

 array_a           | integer[]             | 

 array_b           | integer[]             | 

Indexes:

    "mytable_buyer_code_idx" UNIQUE, btree (buyer, code) CLUSTER

    "mytable_buyer_idx" btree (buyer)

    "mytable_code_idx" btree (code)

    "mytable_seller_idx" btree (seller)

Version:

> SELECT version() ;

                                                   version                                                    

--------------------------------------------------------------------------------------------------------------

 PostgreSQL 9.3.6 on x86_64-unknown-linux-gnu, compiled by gcc (GCC) 4.6.3 20120306 (Red Hat 4.6.3-2), 64-bit

(1 row)

This is running on an AWS RDS instance.

Thanks for any pointers

--

David