What would be the best approach?

I've to a process that will potentially result in a table with over 91,000,000 rows.

The user will input a range of latitude and longitude values to download a csv file from that table, but here's my concern:

With that much data, I feel like it's going to be better to break up that one table and instead have 10 different tables, each one housing data specific to a particular state. Now when those queries are run, I'm asking my system to sort through less data and hence the app works quicker.

Is my concern justified or should I feel comfortable in setting things up in one mammoth table?
brucegustPHP DeveloperAsked:
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Chris GralikeSpecialistCommented:
Hi Brucegust,

Did you work out a data model or are you discovering the best approach while coding?
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GaryCommented:
If you were using an indexed spatial points column the search should be pretty quick
http://dev.mysql.com/doc/refman/5.1/en/gis-property-functions.html

Seperating them then how would you know which state table to search?

I'll see if I can find a tutorial on it as it takes a little setting up, but what MySQL version are you on?

I use this method on a few million records and it's very quick
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Ray PaseurCommented:
Please post the CREATE TABLE statement and some of your test data.  It only needs to be about 4 rows, but we need to see the complete row, with all of the columns filled.  Armed with that (it's called the SSCCE) we should be able to give you some pretty solid ideas.
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Ray PaseurCommented:
Now that I've looked at your data a little bit, I think the answer is "break up the data into several tables."  By my computations in your related questions it looks like you may get 160,000,000+ rows.  Of course, your query arrival rates and response times will be important considerations (did you ever think you would be using the second derivative again?!) and at some level you may want a DBA to get hands-on with the application and to help you with the design.
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