Re: Append Cost in query planners - Mailing list pgsql-performance

Heikki,


Thanks for your reply. Will try to do the changes and rivert back. I had one more requirement for partitioning.

I wanted to inherit two different tables for partition. Below is the query used to create the table, an crete the inheritance.


CREATE TABLE metrics_d20070601 (CHECK (sqldate = '20070601')) INHERITS (metrics, date);

Further more we are using the below mentioned query:

SELECT rs.id AS sid, rs.name AS sname, rc.id AS cid, rc.name AS cname, rc.type AS rtype, rc.act_type AS acttype, ra.id AS adid, ra.name AS avname, rch.id AS chid, rch.name AS chname, rcr.dim AS dim, SUM(metrics.imp_del) AS imp, SUM(metrics.clidel) AS cli, date.sqldate AS date, rg.id AS gid 
FROM metrics, rn CROSS JOIN date, ra, rs, rc, rch, rcr, rg
WHERE metrics.netkey = rn.key
AND rn.id = 10
AND metrics.advkey = ra.key
AND metrics.campkey = rc.key
AND metrics.skey = rs.key
AND metrics.chkey = rch.key
AND metrics.cr_key = rcr.key 
AND date.sqldate BETWEEN '6/01/2007' AND '6/01/2007'
AND metrics.gkey = rg.key 
GROUP BY date.sqldate , rs.id, rs.name, ra.id, ra.name, rc.id, rc.name, rc.rev_type , rc.act_type, rch.id, rch.name, rcr.dim, rg.id;

And the query execution plan is as below

                                                                                                                                  QUERY PLAN                                                                                                             
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
 GroupAggregate  (cost=589766.28..651315.41 rows=1119075 width=127)
   ->  Sort  (cost=589766.28..592563.97 rows=1119075 width=127)
         Sort Key: public.date.sqldate, rs.id, rs.name, ra.id, ra.name, rc.id, rc.name, rc.rtype, rc.act_type, rch.id, rch.name, rcr.dim, rg.id
         ->  Hash Join  (cost=64914.87..433619.51 rows=1119075 width=127)
               Hash Cond: ("outer".adv_key = "inner"."key")
               ->  Hash Join  (cost=64419.08..402349.16 rows=1119075 width=111)
                     Hash Cond: ("outer".s_key = "inner"."key")
                     ->  Hash Join  (cost= 63827.54..368185.38 rows=1119075 width=96)
                           Hash Cond: ("outer".campkey = "inner"."key")
                           ->  Hash Join  (cost=61339.00..323731.53 rows=1119075 width=66)
                                 Hash Cond: ("outer".chkey = "inner"."key")
                                 ->  Hash Join  (cost=59480.62..293896.26 rows=1119075 width=46)
                                       Hash Cond: ("outer".cr_key = "inner"."key")
                                       ->  Hash Join  (cost=51298.73..243749.06 rows=1119075 width=48)
                                             Hash Cond: ("outer".gkey = "inner"."key")
                                             ->  Hash Join  (cost=51051.50..204334.21 rows=1119075 width=48)
                                                   Hash Cond: (("outer".netkey = "inner"."key") AND ("outer".date_key = "inner"."key"))
                                                   ->  Append  (cost=0.00..51795.56 rows=1901256 width=48)
                                                         ->  Seq Scan on metrics  (cost= 0.00..25614.71 rows=940271 width=48)
                                                         ->  Seq Scan on metrics_d20070601 metrics  (cost=0.00..26180.85 rows=960985 width=48)
                                                   ->  Hash  (cost=40615.57..40615.57 rows=960986 width=16)
                                                         ->  Nested Loop  (cost=0.00..40615.57 rows=960986 width=16)
                                                               ->  Index Scan using rpt_netw_key_idx on rn  (cost=0.00..16.92 rows=1 width=4)
                                                                     Filter: (id = 10)
                                                               ->  Append  (cost=0.00..30988.79 rows=960986 width=12)
                                                                     ->  Index Scan using rpt_dt_sqldt_idx on date  (cost=0.00..3.02 rows=1 width=12)
                                                                           Index Cond: ((sqldate >= '2007-06-01 00:00:00'::timestamp without time zone) AND (sqldate <= '2007-06-01 00:00:00'::timestamp without time zone))
                                                                     ->  Seq Scan on metrics_d20070601 rpt_date  (cost=0.00..30985.78 rows=960985 width=12)
                                                                           Filter: ((sqldate >= '2007-06-01 00:00:00'::timestamp without time zone) AND (sqldate <= '2007-06-01 00:00:00'::timestamp without time zone))
                                             ->  Hash  (cost=223.18..223.18 rows=9618 width=8)
                                                   ->  Seq Scan on rg  (cost=0.00..223.18 rows=9618 width=8)
                                       ->  Hash  (cost=7367.71..7367.71 rows=325671 width=6)
                                             ->  Seq Scan on rc  (cost=0.00..7367.71 rows=325671 width=6)
                                 ->  Hash  (cost= 1652.51..1652.51 rows=82351 width=28)
                                       ->  Seq Scan on rch  (cost=0.00..1652.51 rows=82351 width=28)
                           ->  Hash  (cost=2283.83..2283.83 rows=81883 width=38)
                                 ->  Seq Scan on rc  (cost=0.00..2283.83 rows=81883 width=38)
                     ->  Hash  (cost=520.63..520.63 rows=28363 width=23)
                           ->  Seq Scan on rs  (cost= 0.00..520.63 rows=28363 width=23)
               ->  Hash  (cost=435.63..435.63 rows=24063 width=24)
                     ->  Seq Scan on radv  (cost=0.00..435.63 rows=24063 width=24)
(41 rows)

Can you let me know how we can avoid the double looping on the metrics table. This been a big table causes the queries to slowdown.


Regards & Thanks,
Nimesh.