Best way to cross matching large datasets

Posted on 16th Feb 2014 by admin

Hi,

Im running a script where am I cross matching about 200 000 data sets with each other. Each data set consists of 8 parameters and I want to count all datasets which have similar or the same parameters for each data set.

Right now, I am doing the matching via a MySql query which im calling about 200 000 times. The problem is that using a query is extremely expensive… it takes up to 2 hours until the script is done. So I am wondering if there is a better method to cross match data sets and if some of could help me find a better solution.

While researching I found out that arrays may be a faster alternative to queries. And so far, I identified 3 possible ways for cross matching:

1. nested foreach () loops
foreach($array as ar1)
foreach($array as ar2)
if ($ar1[0] == $ar1[0])….

2. Using an Array_map with Callback function, so that i would have only one "hand coded" loop
foreach($array as arr)
if ($arr[0] == $parameter)….

3. Array walk where i could save one "hand coded" loop as well.

Theoretically would be the best/fastest way to go about it? Can Anyone tell me what technically the difference between those 3 ways is? And which one is the better approach or if there other alternatives to them?

I am thankful for any advice that helps me reduce execution time!

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