tweaks to docs

1 files changed, 4 insertions, 5 deletions

diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/sparsesvd.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/sparsesvd.scala
index 0ab05de872..83b2178c09 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/sparsesvd.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/sparsesvd.scala
@@ -65,12 +65,10 @@ object SVD {
       throw new IllegalArgumentException("Expecting a tall and skinny matrix")
     }
 
-    if (min_svalue < 1.0e-9) {
-      throw new IllegalArgumentException("Minimum singular value must be greater than 1e-9")
+    if (min_svalue < 1.0e-8) {
+      throw new IllegalArgumentException("Minimum singular value requested must be greater than 1e-9")
     }
 
-    val sc = data.sparkContext
-
     // Compute A^T A, assuming rows are sparse enough to fit in memory
     val rows = data.map(entry =>
             (entry._1._1, (entry._1._2, entry._2))).groupByKey().cache()
@@ -80,7 +78,6 @@ object SVD {
                             ((colind1, colind2), mval1*mval2) } }
     }.reduceByKey(_+_)
 
-
     // Construct jblas A^T A locally
     val ata = DoubleMatrix.zeros(n, n)
     for(entry <- emits.toArray) {
@@ -97,6 +94,8 @@ object SVD {
       throw new Exception("All singular values are smaller than min_svalue: " + min_svalue)
     }
 
+    val sc = data.sparkContext
+
     // prepare V for returning
     val retV = sc.makeRDD(
             Array.tabulate(V.rows, sigma.length){ (i,j) =>