8.0.3 - Linux 2.6.18..
Freshly vacuumed and analyzed
This database has been humming along fine for a while now, but I've got one of
those sticky queries that is taking
much too long to finish.
After some digging, I've found that the planner is choosing to apply a
necessary seq scan to the table. Unfortunately,
it's scanning the whole table, when it seems that it could have joined it to a
smaller table first and reduce the
amount of rows it would have to scan dramatically ( 70 million to about 5,000 ).
The table "eventactivity" has about 70million rows in it, index on "incidentid"
The table "keyword_incidents" is a temporary table and has incidentid as its
primary key. It contains
5125 rows. eventmain and eventgeo both have 2.1 million. My hope is that I can
convince the planner to do the
join to keyword_incidents *first* and then do the seq scan for the LIKE condition. Instead, it seems that it's seqscanning the
whole 70 million rows first and then doing the join, which takes a lot longer than I'd like to wait for it. Or, maybe I'm
misreading the explain output?
Thanks again
-Dan
---------------------------------
Here's the query:
explain analyze
select
*
from
keyword_incidents,
eventactivity,
eventmain,
eventgeo
where
eventmain.incidentid = keyword_incidents.incidentid and
eventgeo.incidentid = keyword_incidents.incidentid and
eventactivity.incidentid = keyword_incidents.incidentid
and ( recordtext like '%JOSE CHAVEZ%' )
order by eventmain.entrydate limit 10000;
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Limit (cost=2388918.07..2388918.08 rows=1 width=455) (actual
time=81771.186..81771.292 rows=26 loops=1)
-> Sort (cost=2388918.07..2388918.08 rows=1 width=455) (actual
time=81771.180..81771.215 rows=26 loops=1)
Sort Key: eventmain.entrydate
-> Nested Loop (cost=0.00..2388918.06 rows=1 width=455) (actual
time=357.389..81770.982 rows=26 loops=1)
-> Nested Loop (cost=0.00..2388913.27 rows=1 width=230)
(actual time=357.292..81767.385 rows=26 loops=1)
-> Nested Loop (cost=0.00..2388909.33 rows=1 width=122)
(actual time=357.226..81764.501 rows=26 loops=1)
-> Seq Scan on eventactivity (cost=0.00..2388874.46 rows=7 width=84) (actual time=357.147..81762.582
rows=27 loops=1)
Filter: ((recordtext)::text ~~ '%JOSE
CHAVEZ%'::text)
-> Index Scan using keyword_incidentid_pkey on keyword_incidents (cost=0.00..4.97 rows=1 width=38)
(actual time=0.034..0.036 rows=1 loops=27)
Index Cond: (("outer".incidentid)::text =
(keyword_incidents.incidentid)::text)
-> Index Scan using eventgeo_incidentid_idx on eventgeo (cost=0.00..3.93 rows=1 width=108) (actual
time=0.076..0.081 rows=1 loops=26)
Index Cond: (("outer".incidentid)::text =
(eventgeo.incidentid)::text)
-> Index Scan using eventmain_incidentid_idx on eventmain (cost=0.00..4.78 rows=1 width=225) (actual
time=0.069..0.075 rows=1 loops=26)
Index Cond: (("outer".incidentid)::text =
(eventmain.incidentid)::text)
Total runtime: 81771.529 ms
(15 rows)
---------------------------(end of broadcast)---------------------------
TIP 6: explain analyze is your friend
