Recommendation engine with mahout
I recommend you to take a look to Oryx (https://github.com/OryxProject/oryx). Oryx is based on Apache Mahout (actually one of the creators of Mahout Sean Owen built it) and provides recommendation using collaborative filtering. Oryx is a very practical tool for implementing recommendation. I have used it in several projects: recommending products in retail stores (small businesses), building an e-commerce recommender and user similarity from mobile app interaction. 

You just have to represent data in the form:
UserId ItemId Value

Where value is a measure (subjective) of the importance or influence of the interaction between that user and the item. User and item can be anything actually, and the same procedure can be used for tagging. For example, for recommending songs, finding similar songs and bands, and finding similar users according to their music tastes you can represent data as

UserId SongId NumberOfPlays

Where NumberOfPlays is the amount of times a song has been played by user (in an online music service for example). This exampl was given in Myrrix the predecessor of Oryx. They also show how to recommend tags to questions in StackOverflow.

The github site is not that well documented but it will be enough to get it running (and working :))