BigPetStore: Embed user "types" into the generated data.

The data set generation in BigPetStore results in data with temporal and geographic patterns, however, there are no "personal" biases in the data.

We need to add personal biases into the data so that the Mahout recommender is capable of teasing out statistically significant product clusters for users.

A simple implementation:

 
given 2 "types" of customers (i.e. dog people, cat people)
t = hash (customer_name) % 2
if(t==0)
   customer buys only dog products
if(t==1) 
   customer buys only cat products

This approach will easily scale and consistently embed profiles into each persons purchases. Obviously using some OO magic we can create customers who also buy cat and dog products both... but the basic approach still remains (hash code -> customer type -> product biases).