[SPARK-2091][MLLIB] use numpy.dot instead of ndarray.dot

`ndarray.dot` is not available in numpy 1.4. This PR makes pyspark/mllib compatible with numpy 1.4.

Author: Xiangrui Meng <meng@databricks.com>

Closes #1035 from mengxr/numpy-1.4 and squashes the following commits:

7ad2f0c [Xiangrui Meng] use numpy.dot instead of ndarray.dot

1 files changed, 5 insertions, 3 deletions

diff --git a/python/pyspark/mllib/_common.py b/python/pyspark/mllib/_common.py
index a411a5d591..e609b60a0f 100644
--- a/python/pyspark/mllib/_common.py
+++ b/python/pyspark/mllib/_common.py
@@ -454,7 +454,7 @@ def _squared_distance(v1, v2):
     v2 = _convert_vector(v2)
     if type(v1) == ndarray and type(v2) == ndarray:
         diff = v1 - v2
-        return diff.dot(diff)
+        return numpy.dot(diff, diff)
     elif type(v1) == ndarray:
         return v2.squared_distance(v1)
     else:
@@ -469,10 +469,12 @@ def _dot(vec, target):
     calling numpy.dot of the two vectors, but for SciPy ones, we
     have to transpose them because they're column vectors.
     """
-    if type(vec) == ndarray or type(vec) == SparseVector:
+    if type(vec) == ndarray:
+        return numpy.dot(vec, target)
+    elif type(vec) == SparseVector:
         return vec.dot(target)
     elif type(vec) == list:
-        return _convert_vector(vec).dot(target)
+        return numpy.dot(_convert_vector(vec), target)
     else:
         return vec.transpose().dot(target)[0]