David Price wrote:
I have 2 servers both with the exact same data, the same O.S., the same
version of Postgres (7.4.5) and the exact same db schema's (one production
server, one development server).  One server is using the correct index for
SQL queries resulting in extremely slow performance, the other server is
properly selecting the index to use and performance is many times better.  I
have tried vacuum, but that did not work.  I finally resorted to dumping the
data, removing the database completely, creating a new database and
importing the data only to have to problem resurface.  The table has
5,000,000+ rows on both the systems.

When I run 'analyze verbose' on the correctly working system, the following
is displayed:

EXPLAIN ANALYZE is usually considered enough

 Index Scan using trptserc on trans  (cost=0.00..465.10 rows=44 width=118)
   Index Cond: (trn_patno = 199999)
   Filter: ((trn_old_date >= '1994-08-23'::date) AND (trn_old_date <=
'2004-08-23'::date) AND (trn_bill_inc = 'B'::bpchar))
(687 rows)

Now, when I run 'analyze verbose' on the INCORRECTLY working system, the following is displayed:

 Index Scan using todate on trans  (cost=0.00..105165.74 rows=1 width=143)
   Index Cond: ((trn_old_date >= '1994-08-23'::date) AND (trn_old_date <=
   Filter: ((trn_patno = 199999) AND (trn_bill_inc = 'B'::bpchar))
(713 rows)

These queries are different. The first returns 687 rows and the second 713 rows. You need to check your systems if they are supposed to be identical.

Things to check:
1. postgresql.conf settings match - different costs could cause this
2. statistics on the two columns (trn_patno,trn_old_date) - if they differ considerably between systems that would also explain it.

I suspect the second one, at a wild guess the working system happens to know 199999 is fairly rare wheras the second just estimates an average.

If the stats don't help, people are going to want to see the entire query+plan. Could you repost with the query and explain analyse on both system. Oh, and some idea on how many rows/unique values are involved in the important columns.

  Richard Huxton
  Archonet Ltd

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