Re: [HACKERS] why is postgres estimating so badly?

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От Nathan C. Burnett
Тема Re: [HACKERS] why is postgres estimating so badly?
Дата
Msg-id Pine.LNX.4.21.0207171202390.18317-100000@delicious.cs.wisc.edu
обсуждение исходный текст
Ответ на why is postgres estimating so badly?  ("Luis Alberto Amigo Navarro" <lamigo@atc.unican.es>)
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The first thing to point out is that the estimated cost is measured in
terms of page reads while the actual time is measured in milliseconds.  So
even if the cost estimate is accurate it is unlikely that those numbers
will be the same.

-N

--
Nathan C. Burnett
Research Assistant, Wisconsin Network Disks
Department of Computer Sciences
University of Wisconsin - Madison
ncb@cs.wisc.edu

On Wed, 17 Jul 2002, Luis Alberto Amigo Navarro wrote:

> I have a query and estimations and results don�t look similar, here is explain analyze:
>
>  NOTICE:  QUERY PLAN:
>
> Sort  (cost=12443.90..12443.90 rows=1 width=93) (actual time=505331.94..505332.67 rows=175 loops=1)
>   ->  Aggregate  (cost=12443.88..12443.89 rows=1 width=93) (actual time=472520.29..505326.48 rows=175 loops=1)
>         ->  Group  (cost=12443.88..12443.89 rows=1 width=93) (actual time=472307.31..485173.92 rows=325302 loops=1)
>               ->  Sort  (cost=12443.88..12443.88 rows=1 width=93) (actual time=472307.24..473769.79 rows=325302
loops=1)
>                     ->  Nested Loop  (cost=12439.25..12443.87 rows=1 width=93) (actual time=103787.68..441614.43
rows=325302loops=1) 
>                           ->  Hash Join  (cost=12439.25..12440.64 rows=1 width=85) (actual time=103733.76..120916.86
rows=325302loops=1) 
>                                 ->  Seq Scan on nation  (cost=0.00..1.25 rows=25 width=15) (actual time=7.81..8.72
rows=25loops=1) 
>                                 ->  Hash  (cost=12439.25..12439.25 rows=1 width=70) (actual time=103722.25..103722.25
rows=0loops=1) 
>                                       ->  Nested Loop  (cost=0.00..12439.25 rows=1 width=70) (actual
time=95.43..100162.91rows=325302 loops=1) 
>                                             ->  Nested Loop  (cost=0.00..12436.23 rows=1 width=62) (actual
time=84.91..47502.93rows=325302 loops=1) 
>                                                   ->  Nested Loop  (cost=0.00..12412.93 rows=4 width=24) (actual
time=66.86..8806.01rows=43424 loops=1) 
>                                                         ->  Seq Scan on part  (cost=0.00..12399.00 rows=1 width=4)
(actualtime=24.88..4076.81 rows=10856 loops=1) 
>                                                         ->  Index Scan using partsupp_pkey on partsupp
(cost=0.00..13.89rows=4 width=20) (actual time=0.20..0.34 rows=4 loops=10856) 
>                                                   ->  Index Scan using l_partsupp_index on lineitem  (cost=0.00..6.02
rows=1width=38) (actual time=0.20..0.61 rows=7 loops=43424) 
>                                             ->  Index Scan using supplier_pkey on supplier  (cost=0.00..3.01 rows=1
width=8)(actual time=0.08..0.10 rows=1 loops=325302) 
>                           ->  Index Scan using orders_pkey on orders  (cost=0.00..3.22 rows=1 width=8) (actual
time=0.85..0.87rows=1 loops=325302) 
> Total runtime: 505563.85 msec
>
> estimated 12000msec
>
> here is the query:
> SELECT
>  nation,
>  o_year,
>  CAST((sum(amount))AS NUMERIC(10,2))AS sum_profit
> FROM(
>  SELECT
>   nation.name AS nation,
>   EXTRACT(year FROM orders.orderdate) AS o_year,
>   lineitem.extendedprice*(1-lineitem.discount)-partsupp.supplycost*lineitem.quantity AS amount
>  FROM
>   part,
>   supplier,
>   lineitem,
>   partsupp,
>   orders,
>   nation
>  WHERE
>   supplier.suppkey=lineitem.suppkey
>   AND partsupp.suppkey=lineitem.suppkey
>   AND partsupp.partkey=lineitem.partkey
>   AND part.partkey=lineitem.partkey
>   AND orders.orderkey=lineitem.orderkey
>   AND supplier.nationkey=nation.nationkey
>   AND part.name LIKE '%green%'
>  ) AS profit
> GROUP BY
>  nation,
>  o_year
> ORDER BY
>  nation,
>  o_year DESC;
>
> lineitem is about 6M rows
> partsupp 800K rows
> part 200K rows
>
> any advice?
> Thanks and regards
>
>
>



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