Algorithm for data filter

Question

Can you suggest me an algorithm for filtering out data.

I am using javascript and trying to write out a filter function which filters an array of data.I have an array of data and an array of filters, so in order to apply each filter on every data, I have written 2 for loops

foreach(data)
{
  foreach(filter)
  {
   check data with filter
  }
}

this is not the proper code, but in short that what my function does, the problem is this takes a huge amount of time, can someone suggest a better method.

I am using the Mootools library and the array of data is JSON array

Details of data and Filter

Data is JSON array of lets say user, so it will be

data = [{"name" : "first", "email" :  "first@first", "age" : "20"}.
        {"name" : "second", "email" :  "second@second", "age" : "21"}
        {"name" : "third", "email" :  "third@third", "age" : "22"}]

Array of filters is basically self define class for different fields of data

alFilter[0] = filterName;
alFilter[1] = filterEmail;
alFilter[2] = filterAge;

So when I enter the first for loop, I get a single JSON opbject (first row) in the above case. When I enter the second for loop (filters loop) I have a filter class which extracts the exact field on which the current filter would work and check the filter with the appropriate field of the data.

So in my example

foreach(data)
{
 foreach(filter)
{
  //loop one - filter name
 // loop two - filter email
 // loop three - filter age
}
}

when the second loop ends i set a flag denoting if the data has been filtered or not and depending on it the data is displayed.

Answer 1

You're going to have to give us some more detail about the exact structure of your data and filters to really be able to help you out. Are the filters being used to select a subset of data, or to modify the data? What are the filters doing?

That said, there are a few general suggestions:

1. Do less work. Is there some way you can limit the amount of data you're working on? Some pre-filter that can run quickly and cut it down before you do your main loop?
2. Break out of the inner loop as soon as possible. If one of the filters rejects a datum, then break out of the inner loop and move on to the next datum. If this is possible, then you should also try to make the most selective filters come first. (This is assuming that your filters are being used to reject items out of the list, rather than modify them)
3. Check for redundancy in the computation the filters perform. If each of them performs some complicated calculations that share some subroutines, then perhaps memoization or dynamic programming may be used to avoid redundant computation.

Really, it all boils down to the first point, do less work, at all three levels of your code. Can you do less work by limiting the items in the outer loop? Do less work by stopping after a particular filter and doing the most selective filters first? Do less work by not doing any redundant computation inside of each filter?

Answer 2

That's pretty much how you should do it. The trick is to optimize that "check data with filter"-part. You need to traverse all your data and check against all your filters - you'll not going to get any faster than that.

Avoid string comparisons, use data models as native as possible, try to reduce the data set on each pass with filter, etc.

Without further knowledge, it's hard to optimize this for you.