delete tests

python/pyspark/streaming/tests.py

@@ -253,53 +253,6 @@ def _test_func(self, input, func, expected, numSlices=None, sort=False):
         self.assertEqual(expected, result)
 
 
-class TestTransform(PySparkStreamingTestCase):
-    def setUp(self):
-        PySparkStreamingTestCase.setUp(self)
-        self.timeout = 10
-
-    def test_transform(self):
-        input = [range(1, 5), range(5, 9), range(9, 13)]
-
-        def func(stream):
-            return stream.transform(lambda r: r and r.map(str))
-
-        expected = map(lambda x: map(str, x), input)
-        self._test_func(input, func, expected)
-        self.assertEqual(expected, output)
-
-    def _test_func(self, input, func, expected, numSlices=None):
-        """
-        Start stream and return the result.
-        @param input: dataset for the test. This should be list of lists.
-        @param func: wrapped function. This function should return PythonDStream object.
-        @param expected: expected output for this testcase.
-        @param numSlices: the number of slices in the rdd in the dstream.
-        """
-        # Generate input stream with user-defined input.
-        input_stream = self.ssc._makeStream(input, numSlices)
-        # Apply test function to stream.
-        stream = func(input_stream)
-        result = stream.collect()
-        self.ssc.start()
-
-        start_time = time.time()
-        # Loop until get the expected the number of the result from the stream.
-        while True:
-            current_time = time.time()
-            # Check time out.
-            if (current_time - start_time) > self.timeout:
-                break
-            # StreamingContext.awaitTermination is not used to wait because
-            # if py4j server is called every 50 milliseconds, it gets an error.
-            time.sleep(0.05)
-            # Check if the output is the same length of expected output.
-            if len(expected) == len(result):
-                break
-
-        return result
-
-
 class TestStreamingContext(unittest.TestCase):
     """
     Should we have conf property in  SparkContext?