Hi Shivaram, Thank you for the link. I'm trying to figure out how can I port this to mllib. May you can help me to understand how pieces fit together. Currently, in mllib there's different types of distributed matrix :
BlockMatrix, CoordinateMatrix, IndexedRowMatrix and RowMatrix. Which one should correspond to RowPartitionedMatrix in ml-matrix ? On Tue, Mar 3, 2015 at 8:02 PM, Shivaram Venkataraman < shiva...@eecs.berkeley.edu> wrote: > There are couple of solvers that I've written that is part of the AMPLab > ml-matrix repo [1,2]. These aren't part of MLLib yet though and if you are > interested in porting them I'd be happy to review it > > Thanks > Shivaram > > > [1] > https://github.com/amplab/ml-matrix/blob/master/src/main/scala/edu/berkeley/cs/amplab/mlmatrix/TSQR.scala > [2] > https://github.com/amplab/ml-matrix/blob/master/src/main/scala/edu/berkeley/cs/amplab/mlmatrix/NormalEquations.scala > > On Tue, Mar 3, 2015 at 9:01 AM, Jaonary Rabarisoa <jaon...@gmail.com> > wrote: > >> Dear all, >> >> Is there a least square solver based on DistributedMatrix that we can use >> out of the box in the current (or the master) version of spark ? >> It seems that the only least square solver available in spark is private >> to recommender package. >> >> >> Cheers, >> >> Jao >> > >