More accurate tests

Author: Lewuathe

python/pyspark/mllib/tests.py

@@ -366,9 +366,9 @@ def test_col_norms(self):
         data2 = self.sc.parallelize(xrange(10)).map(lambda x: Vectors.dense(x))
         summary2 = Statistics.colStats(data2)
         self.assertEqual(array([45.0]), summary2.normL1())
-        # Confirm normL2 is among this span because it is a float value.
-        self.assertTrue(summary2.normL2()[0] > 16.5)
-        self.assertTrue(summary2.normL2()[0] < 17.0)
+        import math
+        expectedNormL2 = math.sqrt(sum(map(lambda x: x*x, xrange(10))))
+        self.assertTrue(math.fabs(summary2.normL2()[0] - expectedNormL2) < 1e-14)
 
 
 class VectorUDTTests(PySparkTestCase):