Currently the RowSimiairtyJob uses a similarity measure to pairwise compare all rows in a DistributedRowMatrix.
For many applications including a cross-action recommender we need something like RSJ that takes two DRMs and compares matching rows of each. The output would be the same form as RSJ, and ideally would allow the use of any similarity type already defined--especially LLR.
There are two implementations of a Cross-Recommender one based on the Mahout RecommenderJob, and another based on Solr, that can immediately benefit from a Cross-RSJ.
A modification of the matrix multiply job may be a place to start since the current RSJ seems to rely heavily if self-similarity.