Hi ! I am using mahout item-based recommendation with mongodb. I play around with it and have serval questions.
- How to persistent the recommend model from memory to disk? I know it is an old question and there already exists several discussions, such as this one <http://mail-archives.apache.org/mod_mbox/mahout-user/201112.mbox/%3ccanq80da42nfr8p5mt-qnbo-ycaxyfrbskyoefairdzyrdy-...@mail.gmail.com%3E> . The result come out I have to do it myself. I just wondering is there any realization after two years? - Is it better to set index in the collection ( the one provides preference data )? I read the source and find some query on the collection, such as (user_id, item_id), (user_id), (item_id). Also when refresh called, it will scan the whole collection to find the new data, so (create_at). Would I benefit from ensure index on the fields? If yes, which indexes should I ensure? - From what I can understand, I can use refreshData to achieve event driven fresh. That is, when an event ( user scores at an item), I can call refresh to refresh the model. And it is better on performance and the model keeps up to date. Am I right? Thanks! — hyg
