I would recommend writing a UDF based on the Aho Corasick algorithm [1] which is seeded with relation a and then applied to relation b. This should let you do a single-pass search on each "row" in B, reducing your algorithmic complexity from O(n^2) to O(n).
I'd love to know if anyone else has a better way of doing this, because it's a problem I'm also working on :) -Zach [1] http://en.wikipedia.org/wiki/Aho%E2%80%93Corasick_string_matching_algorithm On Thursday, December 2, 2010 at 1:53 PM, Arun A K wrote: > Hello > > I have this problem to solve using Pig. > > *Input* > 1. Relation A which has only one field of type chararray. Sample of A > follows: > *abc* > *xyz gh* > *zzz yy* > *red* > > Approximate numbers of rows in A = 10,000 > > 2. Relation B which has only one field of type chararray. Sample of B > follows: > *red car* > *red ferrari* > *abc* > *abcd* > *xyz ghis* > > Approximate numbers of rows in B = 1 billion > > *Problem to be solved* I need to find all case-insensitive variants of each > term in relation A existing in relation B. For example: Term 'red' from A > would have variants 'red car' and 'red ferrari' in B. > > I was able to get variants of one term in A from B using matches operator > i.e. matches '.*red.*' How to go about creating a complete solution for this > problem? Should I use a UDF or go for native Map Reduce? Am a bit confused > on how to proceed on this. I would really appreciate any help on this. > > Thanks much. > > Regards > Arun A K > > > >
