Hi all!
I'm using Spark 2.0.1 with two workers (one executor each) with 20Gb each.
And run following code:
JavaRDD entries = ...; // filing the dataCoordinateMatrix
cmatrix = new CoordinateMatrix(entries.rdd());BlockMatrix matrix =
cmatrix.toBlockMatrix(100, 1000);BlockMatrix cooc =
matrix.transp
Hi all!
I have MatrixFactorizationModel object. If I'm trying to recommend products to
single user right after constructing model through ALS.train(...) then it takes
300ms (for my data and hardware). But if I save model to disk and load it back
then recommendation takes almost 2000ms. Also Spar