Hi, all
I’m reading the source code of master branch
there is a new predict() function in MatrixFactorizationModel
/**
* Predict the rating of many users for many products.
* The output RDD has an element per each element in the input RDD
(including all duplicates)
* unless a user or product is missing in the training set.
*
* @param usersProducts RDD of (user, product) pairs.
* @return RDD of Ratings.
*/
def predict(usersProducts: RDD[(Int, Int)]): RDD[Rating] = {
val users = userFeatures.join(usersProducts).map{
case (user, (uFeatures, product)) => (product, (user, uFeatures))
}
users.join(productFeatures).map {
case (product, ((user, uFeatures), pFeatures)) =>
val userVector = new DoubleMatrix(uFeatures)
val productVector = new DoubleMatrix(pFeatures)
Rating(user, product, userVector.dot(productVector))
}
}
it seems that the author can directly call join with a RDD object?
It’s a new feature in next version? I’m used to creating a PairRDDFunctions
with the current RDD and then calls join, etc.
Did I misunderstand something?
Best,
--
Nan Zhu
