I'm already looking at 100,000+ records, and I am somewhat nervous as to how it will perform as the load begins to get a little bit higher. I suppose I will have to do a little tweaking to make it work properly, but it seems like this approach would lend itself a little more to indexing rather than using the 2 layer approach.

Which leads me to my next question - Chris, in your 2 layer approach how do you handle indexing? If you have a fairly sizable chunk of YAML/XML/etc data, how do you handle searching it?

Rolan Yang wrote:
Brian Dailey wrote:
This looks like what I'll ultimately be doing. I played around with some SQL queries and what I ended up with was similar to this - joining the table for each data value that I wanted to look up (and since I expect a matching data value, I don't even have to LEFT JOIN everything, which speeds it up significantly).

Thanks for all of your help and suggestions!


You may eventually reach a point where your data volume becomes monstrous and the queries start to take an unacceptably long time to run, or consume too much CPU, or maybe even lock up the tables from being written to. At that point (or before) you may want to consider setting up a second mysql machine as as replicated slave - dedicated for generating reports. Once you have that you can create triggers or run periodic batch processes to index your data in more optimized tables so the reports can be generated on the fly or at least more quickly.

~Rolan
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