That's not quite what I'm looking for. Let me provide an example. I have a rowmatrix A that is nxm and I have two local matrices b and c. b is mx1 and c is nx1. In my spark job I wish to perform the following two computations

A*b

and

A^T*c

I don't think this is possible without being able to transpose a rowmatrix. Am I correct?

Thanks,

Alex

As you mentioned, you can perform A * b, where A is a rowmatrix and b is a local matrix.

From your email, I figure you want to compute b * A^T. To do this, you can compute C = A b^T, whose result is the transpose of what you were looking for, i.e. C^T = b * A^T. To undo the transpose, you would have transpose C manually yourself. Be careful
though, because the result might not have each Row fit in memory on a single machine, which is what RowMatrix requires. This danger is why we didn't provide a transpose operation in RowMatrix natively.

To address this and more, there is an effort to provide more comprehensive linear algebra through block matrices, which will likely make it to 1.3:

Best,

Reza

On Mon, Jan 12, 2015 at 6:33 AM, Alex Minnaar
<aminnaar@verticalscope.com> wrote:

I have a rowMatrix on which I want to perform two multiplications. The first is a right multiplication with a local matrix which is fine. But after that I also wish to right multiply the transpose of my rowMatrix with a different local matrix. I understand that there is no functionality to transpose a rowMatrix at this time but I was wondering if anyone could suggest a any kind of work-around for this. I had thought that I might be able to initially create two rowMatrices - a normal version and a transposed version - and use either when appropriate. Can anyone think of another alternative?

Thanks,

Alex