On Wed, Jul 24, 2019 at 4:24 AM Jatinder Sandhu
<jatinder(dot)sandhu(at)flightnetwork(dot)com> wrote:
>
>
> We encounter a issue when we do query on partition table directly with proper partition key provide. postgres able to find problem partition but when I do explain plan it showing 95% spend on planning the execution . Here is example
> itinerary=# EXPLAIN ANALYZE SELECT * FROM itinerary WHERE destination ='GRJ' AND departure_date = '2020-01-01' AND month_day = 101
> itinerary-# ;
> QUERY PLAN
> -----------------------------------------------------------------------------------------------------------------------------------------------------------------------
> Append (cost=0.29..13.79 rows=11 width=1024) (actual time=0.033..0.037 rows=1 loops=1)
> -> Index Scan using itinerary_101_destination_departure_date_idx on itinerary_101 (cost=0.29..13.73 rows=11 width=1024) (actual time=0.033..0.036 rows=1 loops=1)
> Index Cond: (((destination)::text = 'GRJ'::text) AND ((departure_date)::text = '2020-01-01'::text))
> Filter: (month_day = 101)
> Planning Time: 51.677 ms
> Execution Time: 0.086 ms
>
>
> When I do query on directly on the partition table it is quite fast
> itinerary=# EXPLAIN ANALYZE SELECT * FROM itinerary_101 WHERE destination ='GRJ' AND departure_date = '2020-01-01' AND month_day = 101
> itinerary-# ;
> QUERY PLAN
> -----------------------------------------------------------------------------------------------------------------------------------------------------------------
> Index Scan using itinerary_101_destination_departure_date_idx on itinerary_101 (cost=0.29..13.73 rows=11 width=1024) (actual time=0.043..0.048 rows=1 loops=1)
> Index Cond: (((destination)::text = 'GRJ'::text) AND ((departure_date)::text = '2020-01-01'::text))
> Filter: (month_day = 101)
> Planning Time: 0.191 ms
> Execution Time: 0.074 ms
> (5 rows)
>
> itinerary=#
>
> Can we know why this is happening?
>
I guess when you give the query on the parent table, based on your
clause it need to search which partition to scan that can increase the
planning time.
--
Regards,
Dilip Kumar
EnterpriseDB: http://www.enterprisedb.com