Hi Tom,

Thanks for the help - much appreciated.

Yes I'm using PostGIS, and with a simply join to a relating table I could get 
access to the geometry for these point positions. Is using the GIST r-tree 
index faster than using the 2 b-tree indexes on the lat and long values? I 
guess this is a question for the PostGIS guys and a quick test could tell me 
anyway! My memory is that the GIST r-tree index is slow for points at the 
moment, and that a good implementation of a kd-tree index over GIST is required 
for better speed.

Regards,

Jeremy Palmer
Geodetic Surveyor
National Geodetic Office
 
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-----Original Message-----
From: Tom Lane [mailto:t...@sss.pgh.pa.us] 
Sent: Saturday, 10 July 2010 11:20 a.m.
To: Jeremy Palmer
Cc: pgsql-performance@postgresql.org
Subject: Re: [PERFORM] Index usage with functions in where condition 

Jeremy Palmer <jpal...@linz.govt.nz> writes:
> This is the query that does not use the indexes:

> SELECT
>   coo.nod_id,
>   6400000*radians(sqrt((coo.value1 - -41.0618)^2+((coo.value2 - 
> 175.58461)*cos(radians(-41.0618)))^2)) as distance
> FROM 
>   crs_coordinate coo
> WHERE
>   coo.value1 between -41.0618-degrees(1200.0/6400000.0) and 
> -41.0618+degrees(1200.0/6400000.0) and
>   coo.value2 between 
> 175.58461-degrees(1200.0/6400000.0)/(cos(radians(-41.0618))) and 
> 175.58461+degrees(1200.0/6400000.0)/(cos(radians(-41.0618)));

Those expressions yield float8, not numeric, and numeric vs float8 isn't
an indexable operator for reasons we needn't get into here.  You should
probably rethink whether numeric is really the best choice of datatype
for your columns, if this is the sort of value you expect to work with
--- you're paying a considerable price in speed and space for
perhaps-illusory precision gains.  But if you insist on using numeric
then the solution is to cast the expression results to numeric
explicitly.

BTW I wonder whether you ought not be looking into postgis rather than
rolling-your-own coordinate arithmetic ...

                        regards, tom lane
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