I'm using PostgreSQL 9.0 beta 1. I've got the following table definition:
# \d parts_2576
Table "public.parts_2576"
Column | Type |
Modifiers
------------+------------------------+-----------------------------------------------------------
ID | bigint | not null default
nextval('"parts_2576_ID_seq"'::regclass)
binaryID | character varying(32) | not null default ''::character varying
messageID | character varying(255) | not null default ''::character varying
subject | character varying(512) | not null default ''::character varying
fromname | character varying(512) | not null default ''::character varying
date | bigint | default 0::bigint
partnumber | bigint | not null default 0::bigint
size | bigint | not null default 0::bigint
Indexes:
"parts_2576_pkey" PRIMARY KEY, btree ("ID")
"binaryID_2576_idx" btree ("binaryID")
"date_2576_idx" btree (date)
"parts_2576_binaryID_idx" btree ("binaryID")
If I run this:
EXPLAIN ANALYZE SELECT SUM("size") AS totalsize, "binaryID", COUNT(*)
AS parttotal, MAX("subject") AS subject, MAX("fromname") AS fromname,
MIN("date") AS mindate FROM parts_2576 WHERE "binaryID" >
'1082fa89fe499741b8271f9c92136f44' GROUP BY "binaryID" ORDER BY
"binaryID" LIMIT 400;
I get this:
Limit (cost=0.00..316895.11 rows=400 width=211) (actual
time=3.880..1368.936 rows=400 loops=1)
-> GroupAggregate (cost=0.00..41843621.95 rows=52817 width=211)
(actual time=3.872..1367.048 rows=400 loops=1)
-> Index Scan using "binaryID_2576_idx" on parts_2576
(cost=0.00..41683754.21 rows=10578624 width=211) (actual
time=0.284..130.756 rows=19954 loops=1)
Index Cond: (("binaryID")::text >
'1082fa89fe499741b8271f9c92136f44'::text)
Total runtime: 1370.140 ms
The first thing which strikes me is how the GroupAggregate step shows
it got the 400 rows which matches the limit, but it estimated 52,817
rows. Shouldn't it have already known it would be 400?
I've got an index on "binaryID" (actually, I appear to have 2), but I
suspect it's not really working as intended as it's doing an
evaluation on its value and those greater than it. Is there a way to
optimise this like using a functional index or something?
Obviously this isn't my design (duplicate indexes and mixed-case
column names?), but I'd like to see if I can get things running
faster.
Thanks
Thom
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