Github user debasish83 commented on the pull request:
https://github.com/apache/spark/pull/6213#issuecomment-104934928
@mengxr I generalized MatrixFactorizationModel.recommendAll and use it for
similarUsers and similarProducts and use dgemm...In IndexedRowMatrix I only
exposed rowSimilarity as the public API and it uses blocked BLAS level-1
computation...It is easy to use gemv in IndexedRowMatrix.rowSimilarity for
CosineKernel but for RBFKernel things will get tricky since for sparse vector,
I don't think we can write euclidean distance as norm1*norm1 + norm2*norm2 - 2
dot(x, y) without letting go of some accuracy which might be ok compared to
runtime benefits...I am looking further into RBF computation using dgemv...
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