I have a query that thinks it's going to generate a huge number of rows,
when in fact it won't:
INSERT INTO page_log.rrs
( bucket_id, page_id,project_id,other,
hits,min_hits,max_hits,total_duration,min_duration,max_duration )
SELECT a.rrs_bucket_id, page_id,project_id,other
,
count(*),count(*),count(*),sum(duration),min(duration),max(duration)
FROM
(SELECT b.bucket_id AS rrs_bucket_id, s.*
FROM rrs.bucket b
JOIN page_log.log s
ON (
b.prev_end_time < log_time
AND b.end_time >= log_time )
WHERE b.rrs_id = '1'
AND b.end_time <= '2005-01-21 20:23:00+00'
AND b.end_time > '1970-01-01 00:00:00+00'
) a
GROUP BY rrs_bucket_id, page_id,project_id,other;
QUERY PLAN
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Subquery Scan "*SELECT*" (cost=170461360504.98..183419912556.69 rows=91175544
width=77)
-> GroupAggregate (cost=170461360504.98..183418316984.67 rows=91175544
width=29)
-> Sort (cost=170461360504.98..171639141309.21 rows=471112321692
width=29)
Sort Key: b.bucket_id, s.page_id, s.project_id, s.other
-> Nested Loop (cost=0.00..17287707964.10 rows=471112321692
width=29)
-> Seq Scan on bucket b (cost=0.00..9275.84 rows=281406
width=20)
Filter: ((rrs_id = 1) AND (end_time <= '2005-01-21
20:23:00+00'::timestamp with time zone) AND (end_time > '1970-01-01
00:00:00+00'::timestamp with time zone))
-> Index Scan using log__log_time on log s
(cost=0.00..36321.24 rows=1674137 width=33)
Index Cond: (("outer".prev_end_time < s.log_time)
AND ("outer".end_time >= s.log_time))
The final rowcount after the aggregate will actually be about 1.9M
rows:
QUERY PLAN
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Subquery Scan "*SELECT*" (cost=170461360504.98..183419912556.69 rows=91175544
width=77) (actual time=156777.374..234613.843 rows=1945123 loops=1)
-> GroupAggregate (cost=170461360504.98..183418316984.67 rows=91175544
width=29) (actual time=156777.345..214246.751 rows=1945123 loops=1)
-> Sort (cost=170461360504.98..171639141309.21 rows=471112321692
width=29) (actual time=156777.296..177517.663 rows=4915567 loops=1)
Sort Key: b.bucket_id, s.page_id, s.project_id, s.other
-> Nested Loop (cost=0.00..17287707964.10 rows=471112321692
width=29) (actual time=0.662..90702.755 rows=4915567 loops=1)
-> Seq Scan on bucket b (cost=0.00..9275.84 rows=281406
width=20) (actual time=0.063..1591.591 rows=265122 loops=1)
Filter: ((rrs_id = 1) AND (end_time <= '2005-01-21
20:23:00+00'::timestamp with time zone) AND (end_time > '1970-01-01
00:00:00+00'::timestamp with time zone))
-> Index Scan using log__log_time on log s
(cost=0.00..36321.24 rows=1674137 width=33) (actual time=0.014..0.174 rows=19
loops=265122)
Index Cond: (("outer".prev_end_time < s.log_time)
AND ("outer".end_time >= s.log_time))
Total runtime: 299623.954 ms
Everything is analyzed, and the statistics target is set to 1000.
Basically, it seems that it doesn't understand that each row in log will
match up with at most one row in bucket. There is a unique index on
bucket(rrs_id, end_time), so it should be able to tell this.
--
Jim C. Nasby, Database Consultant [EMAIL PROTECTED]
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