Github user giwa commented on a diff in the pull request:
https://github.com/apache/spark/pull/2538#discussion_r18079362
--- Diff: python/pyspark/streaming/tests.py ---
@@ -0,0 +1,321 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+"""
+Unit tests for Python SparkStreaming; additional tests are implemented as
doctests in
+individual modules.
+
+Callback server is sometimes unstable sometimes, which cause error in test
case.
+But this is very rare case.
+"""
+from itertools import chain
+import time
+import operator
+import unittest
+
+from pyspark.context import SparkContext
+from pyspark.streaming.context import StreamingContext
+from pyspark.streaming.duration import Seconds
+
+
+class PySparkStreamingTestCase(unittest.TestCase):
+ def setUp(self):
+ class_name = self.__class__.__name__
+ self.sc = SparkContext(appName=class_name)
+ self.ssc = StreamingContext(self.sc, duration=Seconds(1))
+
+ def tearDown(self):
+ # Do not call pyspark.streaming.context.StreamingContext.stop
directly because
+ # we do not wait to shutdown py4j client.
+ self.ssc.stop()
+ self.sc.stop()
+ time.sleep(1)
+
+ @classmethod
+ def tearDownClass(cls):
+ # Make sure tp shutdown the callback server
+ SparkContext._gateway._shutdown_callback_server()
+
+
+class TestBasicOperations(PySparkStreamingTestCase):
+ """
+ 2 tests for each function for batach deserializer and unbatch
deserilizer because
+ the deserializer is not changed dunamically after streaming process
starts.
+ Default numInputPartitions is 2.
+ If the number of input element is over 3, that DStream use batach
deserializer.
+ If not, that DStream use unbatch deserializer.
+
+ All tests input should have list of lists(3 lists are default). This
list represents stream.
+ Every batch interval, the first object of list are chosen to make
DStream.
+ e.g The first list in the list is input of the first batch.
+ Please see the BasicTestSuits in Scala which is close to this
implementation.
+ """
+ def setUp(self):
+ PySparkStreamingTestCase.setUp(self)
+ self.timeout = 10 # seconds
+ self.numInputPartitions = 2
+
+ def test_map(self):
+ """Basic operation test for DStream.map."""
+ input = [range(1, 5), range(5, 9), range(9, 13)]
+
+ def func(dstream):
+ return dstream.map(str)
+ expected = map(lambda x: map(str, x), input)
+ self._test_func(input, func, expected)
+
+ def test_flatMap(self):
+ """Basic operation test for DStream.faltMap."""
+ input = [range(1, 5), range(5, 9), range(9, 13)]
+
+ def func(dstream):
+ return dstream.flatMap(lambda x: (x, x * 2))
+ expected = map(lambda x: list(chain.from_iterable((map(lambda y:
[y, y * 2], x)))),
+ input)
+ self._test_func(input, func, expected)
+
+ def test_filter(self):
+ """Basic operation test for DStream.filter."""
+ input = [range(1, 5), range(5, 9), range(9, 13)]
+
+ def func(dstream):
+ return dstream.filter(lambda x: x % 2 == 0)
+ expected = map(lambda x: filter(lambda y: y % 2 == 0, x), input)
+ self._test_func(input, func, expected)
+
+ def test_count(self):
+ """Basic operation test for DStream.count."""
+ input = [range(1, 5), range(1, 10), range(1, 20)]
+
+ def func(dstream):
+ return dstream.count()
+ expected = map(lambda x: [len(x)], input)
+ self._test_func(input, func, expected)
+
+ def test_reduce(self):
+ """Basic operation test for DStream.reduce."""
+ input = [range(1, 5), range(5, 9), range(9, 13)]
+
+ def func(dstream):
+ return dstream.reduce(operator.add)
+ expected = map(lambda x: [reduce(operator.add, x)], input)
+ self._test_func(input, func, expected)
+
+ def test_reduceByKey(self):
+ """Basic operation test for DStream.reduceByKey."""
+ input = [[("a", 1), ("a", 1), ("b", 1), ("b", 1)],
+ [("", 1), ("", 1), ("", 1), ("", 1)],
+ [(1, 1), (1, 1), (2, 1), (2, 1), (3, 1)]]
+
+ def func(dstream):
+ return dstream.reduceByKey(operator.add)
+ expected = [[("a", 2), ("b", 2)], [("", 4)], [(1, 2), (2, 2), (3,
1)]]
+ self._test_func(input, func, expected, sort=True)
+
+ def test_mapValues(self):
+ """Basic operation test for DStream.mapValues."""
+ input = [[("a", 2), ("b", 2), ("c", 1), ("d", 1)],
+ [("", 4), (1, 1), (2, 2), (3, 3)],
+ [(1, 1), (2, 1), (3, 1), (4, 1)]]
+
+ def func(dstream):
+ return dstream.mapValues(lambda x: x + 10)
+ expected = [[("a", 12), ("b", 12), ("c", 11), ("d", 11)],
+ [("", 14), (1, 11), (2, 12), (3, 13)],
+ [(1, 11), (2, 11), (3, 11), (4, 11)]]
+ self._test_func(input, func, expected, sort=True)
+
+ def test_flatMapValues(self):
+ """Basic operation test for DStream.flatMapValues."""
+ input = [[("a", 2), ("b", 2), ("c", 1), ("d", 1)],
+ [("", 4), (1, 1), (2, 1), (3, 1)],
+ [(1, 1), (2, 1), (3, 1), (4, 1)]]
+
+ def func(dstream):
+ return dstream.flatMapValues(lambda x: (x, x + 10))
+ expected = [[("a", 2), ("a", 12), ("b", 2), ("b", 12),
+ ("c", 1), ("c", 11), ("d", 1), ("d", 11)],
+ [("", 4), ("", 14), (1, 1), (1, 11), (2, 1), (2, 11),
(3, 1), (3, 11)],
+ [(1, 1), (1, 11), (2, 1), (2, 11), (3, 1), (3, 11),
(4, 1), (4, 11)]]
+ self._test_func(input, func, expected)
+
+ def test_glom(self):
+ """Basic operation test for DStream.glom."""
+ input = [range(1, 5), range(5, 9), range(9, 13)]
+ numSlices = 2
+
+ def func(dstream):
+ return dstream.glom()
+ expected = [[[1, 2], [3, 4]], [[5, 6], [7, 8]], [[9, 10], [11,
12]]]
+ self._test_func(input, func, expected, numSlices)
+
+ def test_mapPartitions(self):
+ """Basic operation test for DStream.mapPartitions."""
+ input = [range(1, 5), range(5, 9), range(9, 13)]
+ numSlices = 2
+
+ def func(dstream):
+ def f(iterator):
+ yield sum(iterator)
+ return dstream.mapPartitions(f)
+ expected = [[3, 7], [11, 15], [19, 23]]
+ self._test_func(input, func, expected, numSlices)
+
+ def test_countByValue(self):
+ """Basic operation test for DStream.countByValue."""
+ input = [range(1, 5) * 2, range(5, 7) + range(5, 9), ["a", "a",
"b", ""]]
+
+ def func(dstream):
+ return dstream.countByValue()
+ expected = [[4], [4], [3]]
+ self._test_func(input, func, expected)
+
+ def test_groupByKey(self):
+ """Basic operation test for DStream.groupByKey."""
+ input = [[(1, 1), (2, 1), (3, 1), (4, 1)],
+ [(1, 1), (1, 1), (1, 1), (2, 1), (2, 1), (3, 1)],
+ [("a", 1), ("a", 1), ("b", 1), ("", 1), ("", 1), ("", 1)]]
+
+ def func(dstream):
+ return dstream.groupByKey().mapValues(list)
+
+ expected = [[(1, [1]), (2, [1]), (3, [1]), (4, [1])],
+ [(1, [1, 1, 1]), (2, [1, 1]), (3, [1])],
+ [("a", [1, 1]), ("b", [1]), ("", [1, 1, 1])]]
+ self._test_func(input, func, expected, sort=True)
+
+ def test_combineByKey(self):
+ """Basic operation test for DStream.combineByKey."""
+ input = [[(1, 1), (2, 1), (3, 1), (4, 1)],
+ [(1, 1), (1, 1), (1, 1), (2, 1), (2, 1), (3, 1)],
+ [("a", 1), ("a", 1), ("b", 1), ("", 1), ("", 1), ("", 1)]]
+
+ def func(dstream):
+ def add(a, b):
+ return a + str(b)
+ return dstream.combineByKey(str, add, add)
+ expected = [[(1, "1"), (2, "1"), (3, "1"), (4, "1")],
+ [(1, "111"), (2, "11"), (3, "1")],
+ [("a", "11"), ("b", "1"), ("", "111")]]
+ self._test_func(input, func, expected, sort=True)
+
+ def test_union(self):
+ input1 = [range(3), range(5), range(1)]
+ input2 = [range(3, 6), range(5, 6), range(1, 6)]
+
+ d1 = self.ssc._makeStream(input1)
+ d2 = self.ssc._makeStream(input2)
+ d = d1.union(d2)
+ result = d.collect()
+ expected = [range(6), range(6), range(6)]
+
+ 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 * 2:
+ 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
+ self.assertEqual(expected, result)
+
+ def _sort_result_based_on_key(self, outputs):
+ """Sort the list base onf first value."""
--- End diff --
Sorry this may be my typo.
```
"""Sort the list base onf first value."""
```
based on the first value
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
