Hi, I am new to Spark ML Lib. I am using FPGrowth model for finding related items.
Number of transactions are 63K and the total number of items in all transactions are 200K. I am running FPGrowth model to generate frequent items sets. It is taking huge amount of time to generate frequent itemsets.* I am setting min-support value such that each item appears in at least ~(number of items)/(number of transactions).* It is taking lots of time in case If I say item can appear at least once in the database. If I give higher value to min-support then output is very smaller. Could anyone please guide me how to reduce the execution time for generating frequent items? ------ Thanks, Raju Bairishetti, www.lazada.com
