We are working on a PRs to add block partitioned matrix formats and dense matrix multiply methods. This should be out in the next few weeks or so. The sparse methods still need some research on partitioning schemes etc. and we will do that after the dense methods are in place.
Thanks Shivaram On Wed, Nov 5, 2014 at 2:00 AM, Duy Huynh <[email protected]> wrote: > ok great. when will this be ready? > > On Wed, Nov 5, 2014 at 4:27 AM, Xiangrui Meng <[email protected]> wrote: > >> We are working on distributed block matrices. The main JIRA is at: >> >> https://issues.apache.org/jira/browse/SPARK-3434 >> >> The goal is to support basic distributed linear algebra, (dense first >> and then sparse). >> >> -Xiangrui >> >> On Wed, Nov 5, 2014 at 12:23 AM, ll <[email protected]> wrote: >> > @sowen.. i am looking for distributed operations, especially very large >> > sparse matrix x sparse matrix multiplication. what is the best way to >> > implement this in spark? >> > >> > >> > >> > -- >> > View this message in context: >> http://apache-spark-user-list.1001560.n3.nabble.com/Matrix-multiplication-in-spark-tp12562p18164.html >> > Sent from the Apache Spark User List mailing list archive at Nabble.com. >> > >> > --------------------------------------------------------------------- >> > To unsubscribe, e-mail: [email protected] >> > For additional commands, e-mail: [email protected] >> > >> > >
