za*******@gmail.com wrote:

pr******@gmail.com wrote:

>>Hi,

I have a database with two tables

a) A table of 2 million records with city, zip and associated

information (say XYZ) and

b) zipcode latitude, longitude table having >40,000 records/zip codes

PROBLEM:

I need to find the the XYZs within the the range of a certain zipcode.

This zipcode and radial range in miles is entered by the user (web

interface).

The brute force way is to calculate the distance between the user

zipcode and all the zipcodes in the database. Once the zipcode_range

subroutine gives back the zipcodes within a certain radius, I need to

find all the XYZs from the table #1.

Another approach is to find the zipcodes with a square region (min/max

of the user zipcode latitude/longitude position).

Both the approaches are consuming too much time. Especially if the

radial distance starts increasing.

My questions:

1. Is there any other smart way to do the above task.

2. I am working on a 2.4ghz/512MB RAM machine. Any suggestions how to

increase the performance. Right now each select command to the

2Million record table takes about a minute.

Thanks.

have you read this article over at

http://www.phparchitect.com/sample.php?mid=9

the whole thing seems very informative - particularly listing 3

Seems about right to me.

I've tried the cos, sin acos and that seemed a little slow so I did this:

(Perl)

my

$mile_lat=convertToMiles($L{latitude},$L{longitude },$L{latitude}-1,$L{longitude});

my

$mile_lon=convertToMiles($L{latitude},$L{longitude },$L{latitude},$L{longitude}-1);

$sql_zip=qq{ , ceiling(sqrt(pow(((latitude - $L{latitude}) *

$mile_lat),2) + pow(((longitude -$L{longitude}) * $mile_lon),2))) AS

distance };

sub convertToMiles{

($lat1, $lon1, $lat2, $lon2)=@_;

$dist = acos(sin(deg2rad($lat1)) * sin(deg2rad($lat2)) +

cos(deg2rad($lat1)) * cos(deg2rad($lat2)) * cos(deg2rad($lon1 - $lon2)));

$dist = rad2deg($dist);

return $miles = $dist * 69;

} # end sub

The $L{latitude} stuff is from the zipcode database, I found that

indexing the zipcode database was essential!

Close enough and more than fast enough my purposes. All that is doing is

finding the approximate distance per degree ($mile_lat and $mile_lon)

and then just finding the length of the hypoteneus. That will start to

fail for large distances (multi state) because the earth is curved.

Jeff

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