Ok. maybe you are in a rush.
But I would keep the thread open, to understand what I am not
understanding or else, it'll become a habit of converting sql to plpgsql :)
Big Guys,
It seems, when the table is partitioned by range, it makes use of a nested
loop which helps in partition pruning.
if the table is list partitioned, it scans all the partitions.
Is this expected ?
LIST BASED PARTITION
**********************
postgres@go:~$ more p.sql
drop table tbl1;
drop table tprt;
create table tbl1(col1 int);
insert into tbl1 values (501), (505);
-- Basic table
create table tprt (col1 int) partition by list (col1);
create table tprt_1 partition of tprt for values in (501);
create table tprt_2 partition of tprt for values in (1001);
create table tprt_3 partition of tprt for values in (2001);
create table tprt_4 partition of tprt for values in (3001);
create table tprt_5 partition of tprt for values in (4001);
create table tprt_6 partition of tprt for values in (5001);
create index tprt1_idx on tprt_1 (col1);
create index tprt2_idx on tprt_2 (col1);
create index tprt3_idx on tprt_3 (col1);
create index tprt4_idx on tprt_4 (col1);
create index tprt5_idx on tprt_5 (col1);
create index tprt6_idx on tprt_6 (col1);
insert into tprt values (501), (1001), (2001), (3001), (4001), (5001),
(501);
alter table tbl1 add column col2 int default 0;
update tbl1 set col2 =1 where col1 = 501;
vacuum analyze tprt;
vacuum analyze tbl1;
explain analyze select * from tprt where tprt.col1 in (select tbl1.col1
from tbl1 where tbl1.col2 in (1, 2) );
QUERY PLAN
------------------------------------------------------------------------------------------------------------
Hash Semi Join (cost=1.05..7.20 rows=2 width=4) (actual time=0.028..0.034
rows=2 loops=1)
Hash Cond: (tprt.col1 = tbl1.col1)
-> Append (cost=0.00..6.10 rows=7 width=4) (actual time=0.003..0.008
rows=7 loops=1)
-> Seq Scan on tprt_1 (cost=0.00..1.02 rows=2 width=4) (actual
time=0.002..0.003 rows=2 loops=1)
-> Seq Scan on tprt_2 (cost=0.00..1.01 rows=1 width=4) (actual
time=0.001..0.001 rows=1 loops=1)
-> Seq Scan on tprt_3 (cost=0.00..1.01 rows=1 width=4) (actual
time=0.001..0.001 rows=1 loops=1)
-> Seq Scan on tprt_4 (cost=0.00..1.01 rows=1 width=4) (actual
time=0.000..0.000 rows=1 loops=1)
-> Seq Scan on tprt_5 (cost=0.00..1.01 rows=1 width=4) (actual
time=0.001..0.001 rows=1 loops=1)
-> Seq Scan on tprt_6 (cost=0.00..1.01 rows=1 width=4) (actual
time=0.001..0.001 rows=1 loops=1)
-> Hash (cost=1.02..1.02 rows=2 width=4) (actual time=0.006..0.006
rows=1 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 9kB
-> Seq Scan on tbl1 (cost=0.00..1.02 rows=2 width=4) (actual
time=0.003..0.003 rows=1 loops=1)
Filter: (col2 = ANY ('{1,2}'::integer[]))
Rows Removed by Filter: 1
Planning Time: 0.237 ms
Execution Time: 0.060 ms
*even if i set hashjoin off*
postgres=# set enable_hashjoin TO 0;
SET
postgres=# explain analyze select * from tprt where tprt.col1 in (select
tbl1.col1 from tbl1 where tbl1.col2 in (1, 2) );
QUERY PLAN
------------------------------------------------------------------------------------------------------------
Nested Loop Semi Join (cost=0.00..7.34 rows=2 width=4) (actual
time=0.013..0.023 rows=2 loops=1)
Join Filter: (tprt.col1 = tbl1.col1)
Rows Removed by Join Filter: 5
-> Append (cost=0.00..6.10 rows=7 width=4) (actual time=0.004..0.010
rows=7 loops=1)
-> Seq Scan on tprt_1 (cost=0.00..1.02 rows=2 width=4) (actual
time=0.003..0.003 rows=2 loops=1)
-> Seq Scan on tprt_2 (cost=0.00..1.01 rows=1 width=4) (actual
time=0.001..0.001 rows=1 loops=1)
-> Seq Scan on tprt_3 (cost=0.00..1.01 rows=1 width=4) (actual
time=0.001..0.001 rows=1 loops=1)
-> Seq Scan on tprt_4 (cost=0.00..1.01 rows=1 width=4) (actual
time=0.001..0.001 rows=1 loops=1)
-> Seq Scan on tprt_5 (cost=0.00..1.01 rows=1 width=4) (actual
time=0.001..0.001 rows=1 loops=1)
-> Seq Scan on tprt_6 (cost=0.00..1.01 rows=1 width=4) (actual
time=0.001..0.001 rows=1 loops=1)
-> Materialize (cost=0.00..1.03 rows=2 width=4) (actual
time=0.001..0.001 rows=1 loops=7)
-> Seq Scan on tbl1 (cost=0.00..1.02 rows=2 width=4) (actual
time=0.007..0.007 rows=1 loops=1)
Filter: (col2 = ANY ('{1,2}'::integer[]))
Rows Removed by Filter: 1
Planning Time: 0.578 ms
Execution Time: 0.038 ms
(16 rows)
**********************
RANGE BASED PARTITION
**********************
postgres@go:~$ more q.sql
drop table tbl1;
drop table tprt;
create table tbl1(col1 int);
insert into tbl1 values (501), (505);
-- Basic table
create table tprt (col1 int) partition by range(col1);
create table tprt_1 partition of tprt for values from (0) to (500);
create table tprt_2 partition of tprt for values from (500) to (1000);
create table tprt_3 partition of tprt for values from (1000) to (1500);
create table tprt_4 partition of tprt for values from (1500) to (2000);
create table tprt_5 partition of tprt for values from (2000) to (22500);
create index tprt1_idx on tprt_1 (col1);
create index tprt2_idx on tprt_2 (col1);
create index tprt3_idx on tprt_3 (col1);
create index tprt4_idx on tprt_4 (col1);
create index tprt5_idx on tprt_5 (col1);
insert into tprt values (501), (1001), (2001), (3001), (4001), (5001),
(501);
vacuum analyze tbl1;
vacuum analyze tprt;
alter table tbl1 add column col2 int default 0;
update tbl1 set col2 =1 where col1 = 501;
explain analyze select * from tprt where tprt.col1 in (select tbl1.col1
from tbl1 where tbl1.col2 in (1, 2) );
QUERY PLAN
----------------------------------------------------------------------------------------------------------------
Nested Loop (cost=3.29..55.37 rows=2 width=4) (actual time=0.016..0.018
rows=2 loops=1)
-> Unique (cost=1.03..1.04 rows=2 width=4) (actual time=0.012..0.012
rows=1 loops=1)
-> Sort (cost=1.03..1.04 rows=2 width=4) (actual
time=0.011..0.011 rows=1 loops=1)
Sort Key: tbl1.col1
Sort Method: quicksort Memory: 25kB
-> Seq Scan on tbl1 (cost=0.00..1.02 rows=2 width=4)
(actual time=0.004..0.005 rows=1 loops=1)
Filter: (col2 = ANY ('{1,2}'::integer[]))
Rows Removed by Filter: 1
-> Append (cost=2.26..26.86 rows=30 width=4) (actual time=0.003..0.004
rows=2 loops=1)
-> Bitmap Heap Scan on tprt_1 (cost=2.26..11.81 rows=13 width=4)
(never executed)
Recheck Cond: (col1 = tbl1.col1)
-> Bitmap Index Scan on tprt1_idx (cost=0.00..2.25 rows=13
width=0) (never executed)
Index Cond: (col1 = tbl1.col1)
-> Seq Scan on tprt_2 (cost=0.00..1.02 rows=2 width=4) (actual
time=0.001..0.002 rows=2 loops=1)
Filter: (tbl1.col1 = col1)
-> Seq Scan on tprt_3 (cost=0.00..1.01 rows=1 width=4) (never
executed)
Filter: (tbl1.col1 = col1)
-> Bitmap Heap Scan on tprt_4 (cost=2.26..11.81 rows=13 width=4)
(never executed)
Recheck Cond: (col1 = tbl1.col1)
-> Bitmap Index Scan on tprt4_idx (cost=0.00..2.25 rows=13
width=0) (never executed)
Index Cond: (col1 = tbl1.col1)
-> Seq Scan on tprt_5 (cost=0.00..1.05 rows=1 width=4) (never
executed)
Filter: (tbl1.col1 = col1)
Planning Time: 0.214 ms
Execution Time: 0.069 ms
(25 rows)
**********************
On Tue, 11 May 2021 at 17:44, Niels Jespersen <n...@dst.dk> wrote:
> >
>
> >Sorry,
>
> >
>
> >I made a major mistake. I somehow saw the period and period_version as
> the same.
>
> >so, yes partitions are not pruned here. So my suggestion makes no sense.
>
>
>
> Thats quite ok. I think my plan now is to have a table returning function
> that executes a query dynamically. The query has a where caluse that is
> first constructed.
>
>
>
> Like this:
>
>
>
>
>
> return query execute format('select d.x, d.y from %1$I.%1$I d where
> d.period_version = any(' || quote_literal(_periode_version_array)
> ||'::text[])', register_in);
>
>
>
> Regards Niels
>
>
>
>
>
--
Thanks,
Vijay
Mumbai, India
