The number of items in your data sets isn't the problem. You have 15,000 and 500,000, which are small enough to process easily with a database. The real issue is that one data set is highly unstructured.

There are a number of ways to skin this cat. But the key is that you're going to need to write a routine that takes an email message and produces a list of possible original recipients from that message. This step should be generous - you don't want to miss any.

Now pick your method. One approach is to create a hash whose keys are the 15,000 test email addresses and follow this pseudocode: 

while (my $file = get_email_file()) {
  for my $email (get_possible_original_recipients($file)) {
    if ($in_test{$email}) {
      # Do something here.
    }
  }
}

[download]
A secopnd approach is to create a table in a database with the fields (filename, email_in_file), populate another table with your test emails, then join them.

Personally I'd suggest following the second approach for several reasons.

  1. It is easily parallelizable - you can have multiple jobs populating that first table at once so you get through that big step faster.
  2. As you tweak the more complex later processing, it is faster to re-run. You can just execute a query rather than having to search gigabytes of emails every time you tweak it.
  3. This is generally useful information to have, you're likely to find other uses for it later.

In reply to Re: Algorithm advice sought for seaching through GB's of text (email) files by tilly
in thread Algorithm advice sought for seaching through GB's of text (email) files by chargrill

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