[ https://issues.apache.org/jira/browse/MAHOUT-305?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12860914#action_12860914 ]
Sean Owen commented on MAHOUT-305: ---------------------------------- OK, I think I get the (item1,item2) -> (item2,count) part, at least, why it can be used in conjunction with a one-pass solution. I wasn't sure how you guarantee that all (item1,item2) for item1 arrive at the same reducer. But the answer is the partitioner? Then it works; I still think there is a need for lots of pruning and big combiner buffers after the map but that's different. Am I right that (item1,item2) -> count is all that's needed? > Combine both cooccurrence-based CF M/R jobs > ------------------------------------------- > > Key: MAHOUT-305 > URL: https://issues.apache.org/jira/browse/MAHOUT-305 > Project: Mahout > Issue Type: Improvement > Components: Collaborative Filtering > Affects Versions: 0.2 > Reporter: Sean Owen > Assignee: Ankur > Priority: Minor > > We have two different but essentially identical MapReduce jobs to make > recommendations based on item co-occurrence: > org.apache.mahout.cf.taste.hadoop.{item,cooccurrence}. They ought to be > merged. Not sure exactly how to approach that but noting this in JIRA, per > Ankur. -- This message is automatically generated by JIRA. - You can reply to this email to add a comment to the issue online.