Hi, guys, For item-based recommendation, I pre-calculated the item similarities on Hadoop per algorithm, which generated 20m rows each. The problem now is I can't just load them into memory via MySQLJDBCInMemoryItemSimilarity with 4GB memory. I tried MySQLJDBCItemSimilarity, however it's way too slow. What are the alternatives?
For user-based recommendation, I can't load 100m lines of data model from FileDataModel into memory. It ran out of memory after 20m lines. The same issue with JDBCDataModel is way too slow. Does anyone precalculate the user similarities before and recommend items to a user? Anyone had the similar issues before? Thanks, YG
