Github user MechCoder commented on a diff in the pull request:
https://github.com/apache/spark/pull/5872#discussion_r29761983
--- Diff: python/pyspark/mllib/linalg.py ---
@@ -633,6 +743,57 @@ def stringify(vector):
"""
return str(vector)
+ @staticmethod
+ def dot(a, b):
+ """
+ Dot product between two vectors.
+ a and b can be of type, SparseVector, DenseVector, np.ndarray
+ or array.array.
+
+ >>> a = Vectors.sparse(4, [(0, 1), (3, 4)])
+ >>> b = Vectors.dense([23, 41, 9, 1])
+ >>> Vectors.dot(a, b)
+ 27.0
+ >>> Vectors.dot(a, a)
+ 17.0
+ >>> Vectors.dot(a, np.array([0, 1, 2, 4]))
+ 16.0
+ """
+ a, b = _convert_to_vector(a), _convert_to_vector(b)
+ return a.dot(b)
+
+ @staticmethod
+ def squared_distance(a, b):
--- End diff --
I'm thinking we should keep both for a couple of versions, deprecate
squared_distance and advice users to use sqdist. (At least that's how it works
in sklearn.)
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