The best bet is to index the field that your WHERE clause look in.  So,
if you do WHERE Zip='blah', then index by zip.  

Create ZIP as your 'clustered' index if you are using SQL server.  Then
you can create as many non-clustered index's as you need, but as you
create more index's, you will get diminished returns on performance
increases.  If you have a table with 10 fields and make 4 - 5 index's,
it should work great.  :)

Have fun!

Chris Peterson
Gainey Transportation

On Mon, 2003-09-08 at 10:42, Phillip B wrote:
> This is what I have done. I took a zipcode table and my dealer table and
> made a view that pretty much joins the two on the zip code. Neither of these
> are indexed yet.
> 
> I then wrote the following two queries to find dealers. The second query can
> take almost 8 seconds to run and is the view of the dealer and zip code
> table. I'm not that comfortable with indexing my tables yet so I was looking
> for some advice on what to index in the tables.
> 
> SELECT
>  zip,
>  lat,
>  long,
>  city,
>  state
> FROM
>  zips
> WHERE
>  zip='#form.passedzipcode#'
> 
> SELECT
>  TOP 15
>  lat,
>  long,
>  name,
>  city,
>  state,
>  zipcode,
>  area_code,
>  phone,
>  3963 * (ACOS((SIN(#passedzip.lat#/57.2958) * SIN(lat/57.2958)) +
>  (COS(#passedzip.lat#/57.2958) * COS(lat/57.2958) *
>  COS(long/57.2958 - #passedzip.long#/57.2958)))) AS distance
> FROM
>  dealers_geo
> #WHERE#
>  3963 * (ACOS((SIN(#passedzip.lat#/57.2958) * SIN(lat/57.2958)) +
>  (COS(#passedzip.lat#/57.2958) * COS(lat/57.2958) *
>  COS(long/57.2958 - #passedzip.long#/57.2958)))) <= #form.passedradius#
> ORDER BY
>  distance
> 
> 
> Phillip B.
> 
> www.LoungeRoyale.com
> www.FillWorks.com
> 
> 
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