In Java/Scala-land, the intent is to use Breeze for this. "Vector" in Spark is an opaque wrapper around the Breeze representation, which contains a bunch of methods like this.
On Fri, Mar 13, 2015 at 3:28 PM, Daniel, Ronald (ELS-SDG) <[email protected]> wrote: >> Any convenient tool to do this [sparse vector product] in Spark? > > > > Unfortunately, it seems that there are very few operations defined for > sparse vectors. I needed to add some, and ended up converting them to > (dense) numpy vectors and doing the addition on those. > > > > Best regards, > > Ron > > > > > > From: Xi Shen [mailto:[email protected]] > Sent: Friday, March 13, 2015 1:50 AM > To: [email protected] > Subject: How to do spares vector product in Spark? > > > > Hi, > > > > I have two RDD[Vector], both Vector are spares and of the form: > > > > (id, value) > > > > "id" indicates the position of the value in the vector space. I want to > apply dot product on two of such RDD[Vector] and get a scale value. The none > exist values are treated as zero. > > > > Any convenient tool to do this in Spark? > > > > > > Thanks, > > David --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
