Github user dbtsai commented on a diff in the pull request:
https://github.com/apache/spark/pull/15628#discussion_r105272811
--- Diff:
mllib-local/src/main/scala/org/apache/spark/ml/linalg/Matrices.scala ---
@@ -153,6 +154,97 @@ sealed trait Matrix extends Serializable {
*/
@Since("2.0.0")
def numActives: Int
+
+ /**
+ * Converts this matrix to a sparse matrix.
+ *
+ * @param colMajor Whether the values of the resulting sparse matrix
should be in column major
+ * or row major order. If `false`, resulting matrix
will be row major.
+ */
+ private[ml] def toSparseMatrix(colMajor: Boolean): SparseMatrix
+
+ /**
+ * Converts this matrix to a sparse matrix in column major order.
+ */
+ @Since("2.2.0")
+ def toCSCMatrix: SparseMatrix = toSparseMatrix(colMajor = true)
+
+ /**
+ * Converts this matrix to a sparse matrix in row major order.
+ */
+ @Since("2.2.0")
+ def toCSRMatrix: SparseMatrix = toSparseMatrix(colMajor = false)
+
+ /**
+ * Converts this matrix to a sparse matrix in column major order.
+ */
+ @Since("2.2.0")
+ def toSparse: SparseMatrix = toSparseMatrix(colMajor = true)
+
+ /**
+ * Converts this matrix to a dense matrix.
+ *
+ * @param colMajor Whether the values of the resulting dense matrix
should be in column major
+ * or row major order. If `false`, resulting matrix
will be row major.
+ */
+ private[ml] def toDenseMatrix(colMajor: Boolean): DenseMatrix
+
+ /**
+ * Converts this matrix to a dense matrix in column major order.
+ */
+ @Since("2.2.0")
+ def toDense: DenseMatrix = toDenseMatrix(colMajor = true)
+
+ /**
+ * Returns a matrix in either dense or sparse format, whichever uses
less storage.
+ *
+ * @param colMajor Whether the values of the resulting matrix should be
in column major
+ * or row major order. If `false`, resulting matrix
will be row major.
+ */
+ @Since("2.2.0")
+ def compressed(colMajor: Boolean): Matrix = {
+ if (getDenseSizeInBytes < getSparseSizeInBytes(colMajor)) {
+ toDenseMatrix(colMajor)
+ } else {
+ toSparseMatrix(colMajor)
+ }
+ }
+
+ /**
+ * Returns a matrix in dense column major, dense row major, sparse row
major, or sparse column
+ * major format, whichever uses less storage. When dense representation
is optimal, it maintains
+ * the current layout order.
+ */
+ @Since("2.2.0")
+ def compressed: Matrix = {
--- End diff --
Won't `compressed(colMajor: Boolean)` and `compressed` cause the
overloading ambiguous issue?
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