Hi,
I've been playing with OSDL DBT-3 for a while and found very strange
phenomemon. The query in question is Q4:
select o_orderpriority, count(*) as order_count from orders where
o_orderdate >= date '1997-10-01' and o_orderdate < (date
'1997-10-01' + interval '3 month')::date and o_orderkey in (
select l_orderkey from lineitem where l_commitdate <
l_receiptdate ) group by o_orderpriority order by
o_orderpriority;
(I modified the original query a little bit so that it could use
i_o_orderdate index)
First I turn off enable_seqscan since old plan used seq scan on orders.
Sort (cost=86050.12..86050.12 rows=1 width=19) (actual time=302476.572..302476.575
rows=5 loops=1)
Sort Key: orders.o_orderpriority
-> HashAggregate (cost=86050.10..86050.11 rows=1 width=19) (actual
time=302476.525..302476.538 rows=5 loops=1)
-> Nested Loop IN Join (cost=0.00..86010.61 rows=7898 width=19) (actual
time=64.341..302136.493 rows=52544 loops=1)
-> Index Scan using orders_pkey on orders (cost=0.00..65387.00
rows=53357 width=30) (actual time=44.687..36364.312 rows=57306 loops=1)
Filter: ((o_orderdate >= '1997-10-01'::date) AND (o_orderdate <
'1998-01-01'::date))
-> Index Scan using i_l_orderkey on lineitem (cost=0.00..3.14 rows=3
width=11) (actual time=4.628..4.628 rows=1 loops=57306)
Index Cond: ("outer".o_orderkey = lineitem.l_orderkey)
Filter: (l_commitdate < l_receiptdate)
Total runtime: 302476.797 ms
(10 rows)
This took about 5 minutes. no so bad. (running on PostgreSQL 7.4.5
BTW)
Then I changed following variables.
enable_seqscan to on
effective_cache_size = 100000
random_page_cost = 1.5
This seems improve the query plan in the following part:
Index Cond: ((o_orderdate >= '1997-10-01'::date) AND (o_orderdate <
'1998-01-01'::date))
However actual execution time was almost 6 times slower than above:
Sort (cost=66763.68..66763.68 rows=1 width=19) (actual time=1915554.845..1915554.849
rows=5 loops=1)
Sort Key: orders.o_orderpriority
-> HashAggregate (cost=66763.66..66763.67 rows=1 width=19) (actual
time=1915554.797..1915554.811 rows=5 loops=1)
-> Nested Loop IN Join (cost=0.00..66724.17 rows=7898 width=19) (actual
time=277.150..1915137.592 rows=52544 loops=1)
-> Index Scan using i_o_orderdate on orders (cost=0.00..46100.56
rows=53357 width=30) (actual time=215.502..650031.049 rows=57306 loops=1)
Index Cond: ((o_orderdate >= '1997-10-01'::date) AND (o_orderdate
< '1998-01-01'::date))
-> Index Scan using i_l_orderkey on lineitem (cost=0.00..3.14 rows=3
width=11) (actual time=22.064..22.064 rows=1 loops=57306)
Index Cond: ("outer".o_orderkey = lineitem.l_orderkey)
Filter: (l_commitdate < l_receiptdate)
Total runtime: 1915555.070 ms
(10 rows)
Could anybody explain why? For me, these query plans are almost same,
and I don't understand how could that difference come from.
--
Tatsuo Ishii
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