Matrix Transpose on RowMatrix in Spark

Question

Suppose I have a RowMatrix.

1. How can I transpose it. The API documentation does not seem to have a transpose method.
2. The Matrix has the transpose() me

Answer 1

This is a variant of the previous solution but working for sparse row matrix and keeping the transposed sparse too when needed:

  def transpose(X: RowMatrix): RowMatrix = {
    val m = X.numRows ().toInt
    val n = X.numCols ().toInt

    val transposed = X.rows.zipWithIndex.flatMap {
      case (sp: SparseVector, i: Long) => sp.indices.zip (sp.values).map {case (j, value) => (i, j, value)}
      case (dp: DenseVector, i: Long) => Range (0, n).toArray.zip (dp.values).map {case (j, value) => (i, j, value)}
    }.sortBy (t => t._1).groupBy (t => t._2).map {case (i, g) =>
      val (indices, values) = g.map {case (i, j, value) => (i.toInt, value)}.unzip
      if (indices.size == m) {
        (i, Vectors.dense (values.toArray) )
      } else {
        (i, Vectors.sparse (m, indices.toArray, values.toArray))
      }
    }.sortBy(t => t._1).map (t => t._2)

    new RowMatrix (transposed)
  }

Hope this help!