Hello,
I would like to add some linear algebra operations to all the
DistributedMatrix classes that Spark actually handles (CoordinateMatrix,
BlockMatrix, IndexedRowMatrix and RowMatrix), but first I would like do
ask if you consider this useful. (For me, it is)
Of course, these operations will be distributed, but they will rely on
the local implementation of mllib linalg. For example, when multiplying
an IndexedRowMatrix by a DenseVector, the multiplication of one of the
matrix rows by the vector will be performed by using the local
implementation
What is your opinion about it?
Thank you
--
José Manuel Abuín Mosquera
Pre-doctoral researcher
Centro de Investigación en Tecnoloxías da Información (CiTIUS)
University of Santiago de Compostela
15782 Santiago de Compostela, Spain
http://citius.usc.es/equipo/investigadores-en-formacion/josemanuel.abuin
http://jmabuin.github.io
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