[SPARK-5905] [MLLIB] Note requirements for certain RowMatrix methods in docs

Note methods that fail for cols > 65535; note that SVD does not require n >= m
CC mengxr

Author: Sean Owen <sowen@cloudera.com>

Closes #8839 from srowen/SPARK-5905.

1 files changed, 8 insertions, 3 deletions

diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala
index e55ef26858..7c7d900af3 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala
@@ -109,7 +109,8 @@ class RowMatrix @Since("1.0.0") (
   }
 
   /**
-   * Computes the Gramian matrix `A^T A`.
+   * Computes the Gramian matrix `A^T A`. Note that this cannot be computed on matrices with
+   * more than 65535 columns.
    */
   @Since("1.0.0")
   def computeGramianMatrix(): Matrix = {
@@ -150,7 +151,8 @@ class RowMatrix @Since("1.0.0") (
    *  - s is a Vector of size k, holding the singular values in descending order,
    *  - V is a Matrix of size n x k that satisfies V' * V = eye(k).
    *
-   * We assume n is smaller than m. The singular values and the right singular vectors are derived
+   * We assume n is smaller than m, though this is not strictly required.
+   * The singular values and the right singular vectors are derived
    * from the eigenvalues and the eigenvectors of the Gramian matrix A' * A. U, the matrix
    * storing the right singular vectors, is computed via matrix multiplication as
    * U = A * (V * S^-1^), if requested by user. The actual method to use is determined
@@ -320,7 +322,8 @@ class RowMatrix @Since("1.0.0") (
   }
 
   /**
-   * Computes the covariance matrix, treating each row as an observation.
+   * Computes the covariance matrix, treating each row as an observation. Note that this cannot
+   * be computed on matrices with more than 65535 columns.
    * @return a local dense matrix of size n x n
    */
   @Since("1.0.0")
@@ -374,6 +377,8 @@ class RowMatrix @Since("1.0.0") (
    * The row data do not need to be "centered" first; it is not necessary for
    * the mean of each column to be 0.
    *
+   * Note that this cannot be computed on matrices with more than 65535 columns.
+   *
    * @param k number of top principal components.
    * @return a matrix of size n-by-k, whose columns are principal components
    */