[FLINK-26444][python] Move all window tests into test_window.py

This closes apache#18957.

Author: cun8cun8

flink-python/pyflink/datastream/tests/test_window.py

@@ -0,0 +1,182 @@
+################################################################################
+#  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.
+################################################################################
+
+from typing import Iterable
+
+from pyflink.common.time import Time
+from pyflink.common.typeinfo import Types
+from pyflink.common.watermark_strategy import WatermarkStrategy, TimestampAssigner
+from pyflink.datastream.data_stream import DataStream
+from pyflink.datastream.functions import (ProcessWindowFunction, WindowFunction)
+from pyflink.datastream.window import (TumblingEventTimeWindows,
+                                       SlidingEventTimeWindows, EventTimeSessionWindows,
+                                       CountSlidingWindowAssigner, SessionWindowTimeGapExtractor,
+                                       CountWindow)
+from pyflink.datastream.tests.test_util import DataStreamTestSinkFunction
+from pyflink.testing.test_case_utils import PyFlinkStreamingTestCase
+
+
+class WindowTests(PyFlinkStreamingTestCase):
+
+    def setUp(self) -> None:
+        super(WindowTests, self).setUp()
+        self.test_sink = DataStreamTestSinkFunction()
+
+    def tearDown(self) -> None:
+        self.test_sink.clear()
+
+    def assert_equals_sorted(self, expected, actual):
+        expected.sort()
+        actual.sort()
+        self.assertEqual(expected, actual)
+
+    def test_event_time_tumbling_window(self):
+        data_stream = self.env.from_collection([
+            ('hi', 1), ('hi', 2), ('hi', 3), ('hi', 4), ('hi', 5), ('hi', 8), ('hi', 9),
+            ('hi', 15)],
+            type_info=Types.TUPLE([Types.STRING(), Types.INT()]))  # type: DataStream
+        watermark_strategy = WatermarkStrategy.for_monotonous_timestamps() \
+            .with_timestamp_assigner(SecondColumnTimestampAssigner())
+        data_stream.assign_timestamps_and_watermarks(watermark_strategy) \
+            .key_by(lambda x: x[0], key_type=Types.STRING()) \
+            .window(TumblingEventTimeWindows.of(Time.milliseconds(5))) \
+            .process(CountWindowProcessFunction(), Types.TUPLE([Types.STRING(), Types.INT()])) \
+            .add_sink(self.test_sink)
+
+        self.env.execute('test_event_time_tumbling_window')
+        results = self.test_sink.get_results()
+        expected = ['(hi,4)', '(hi,3)', '(hi,1)']
+        self.assert_equals_sorted(expected, results)
+
+    def test_count_tumbling_window(self):
+        data_stream = self.env.from_collection([
+            (1, 'hi'), (2, 'hello'), (3, 'hi'), (4, 'hello'), (5, 'hi'), (6, 'hello'),
+            (6, 'hello')],
+            type_info=Types.TUPLE([Types.INT(), Types.STRING()]))  # type: DataStream
+        data_stream.key_by(lambda x: x[1], key_type=Types.STRING()) \
+            .count_window(3) \
+            .apply(SumWindowFunction(), Types.TUPLE([Types.STRING(), Types.INT()])) \
+            .add_sink(self.test_sink)
+
+        self.env.execute('test_count_tumbling_window')
+        results = self.test_sink.get_results()
+        expected = ['(hi,9)', '(hello,12)']
+        self.assert_equals_sorted(expected, results)
+
+    def test_event_time_sliding_window(self):
+        data_stream = self.env.from_collection([
+            ('hi', 1), ('hi', 2), ('hi', 3), ('hi', 4), ('hi', 5), ('hi', 8), ('hi', 9),
+            ('hi', 15)],
+            type_info=Types.TUPLE([Types.STRING(), Types.INT()]))  # type: DataStream
+        watermark_strategy = WatermarkStrategy.for_monotonous_timestamps() \
+            .with_timestamp_assigner(SecondColumnTimestampAssigner())
+
+        data_stream.assign_timestamps_and_watermarks(watermark_strategy) \
+            .key_by(lambda x: x[0], key_type=Types.STRING()) \
+            .window(SlidingEventTimeWindows.of(Time.milliseconds(5), Time.milliseconds(2))) \
+            .process(CountWindowProcessFunction(), Types.TUPLE([Types.STRING(), Types.INT()])) \
+            .add_sink(self.test_sink)
+
+        self.env.execute('test_event_time_sliding_window')
+        results = self.test_sink.get_results()
+        expected = ['(hi,2)', '(hi,4)', '(hi,4)', '(hi,3)', '(hi,2)', '(hi,2)', '(hi,1)', '(hi,1)']
+        self.assert_equals_sorted(expected, results)
+
+    def test_count_sliding_window(self):
+        data_stream = self.env.from_collection([
+            (1, 'hi'), (2, 'hello'), (3, 'hi'), (4, 'hello'), (5, 'hi'), (6, 'hello')],
+            type_info=Types.TUPLE([Types.INT(), Types.STRING()]))  # type: DataStream
+        data_stream.key_by(lambda x: x[1], key_type=Types.STRING()) \
+            .window(CountSlidingWindowAssigner(2, 1)) \
+            .apply(SumWindowFunction(), Types.TUPLE([Types.STRING(), Types.INT()])) \
+            .add_sink(self.test_sink)
+
+        self.env.execute('test_count_sliding_window')
+        results = self.test_sink.get_results()
+        expected = ['(hello,6)', '(hi,8)', '(hi,4)', '(hello,10)']
+        self.assert_equals_sorted(expected, results)
+
+    def test_event_time_session_window(self):
+        data_stream = self.env.from_collection([
+            ('hi', 1), ('hi', 2), ('hi', 3), ('hi', 4), ('hi', 8), ('hi', 9), ('hi', 15)],
+            type_info=Types.TUPLE([Types.STRING(), Types.INT()]))  # type: DataStream
+        watermark_strategy = WatermarkStrategy.for_monotonous_timestamps() \
+            .with_timestamp_assigner(SecondColumnTimestampAssigner())
+
+        data_stream.assign_timestamps_and_watermarks(watermark_strategy) \
+            .key_by(lambda x: x[0], key_type=Types.STRING()) \
+            .window(EventTimeSessionWindows.with_gap(Time.milliseconds(5))) \
+            .process(CountWindowProcessFunction(), Types.TUPLE([Types.STRING(), Types.INT()])) \
+            .add_sink(self.test_sink)
+
+        self.env.execute('test_event_time_session_window')
+        results = self.test_sink.get_results()
+        expected = ['(hi,1)', '(hi,6)']
+        self.assert_equals_sorted(expected, results)
+
+    def test_event_time_dynamic_gap_session_window(self):
+        self.env.set_parallelism(1)
+        data_stream = self.env.from_collection([
+            ('hi', 1), ('hi', 2), ('hi', 3), ('hi', 4), ('hi', 9), ('hi', 9), ('hi', 15)],
+            type_info=Types.TUPLE([Types.STRING(), Types.INT()]))  # type: DataStream
+        watermark_strategy = WatermarkStrategy.for_monotonous_timestamps() \
+            .with_timestamp_assigner(SecondColumnTimestampAssigner())
+
+        data_stream.assign_timestamps_and_watermarks(watermark_strategy) \
+            .key_by(lambda x: x[0], key_type=Types.STRING()) \
+            .window(EventTimeSessionWindows.with_dynamic_gap(MySessionWindowTimeGapExtractor())) \
+            .process(CountWindowProcessFunction(), Types.TUPLE([Types.STRING(), Types.INT()])) \
+            .add_sink(self.test_sink)
+
+        self.env.execute('test_event_time_dynamic_gap_session_window')
+        results = self.test_sink.get_results()
+        expected = ['(hi,3)', '(hi,4)']
+        self.assert_equals_sorted(expected, results)
+
+
+class SecondColumnTimestampAssigner(TimestampAssigner):
+
+    def extract_timestamp(self, value, record_timestamp) -> int:
+        return int(value[1])
+
+
+class MySessionWindowTimeGapExtractor(SessionWindowTimeGapExtractor):
+
+    def extract(self, element: tuple) -> int:
+        return element[1]
+
+
+class SumWindowFunction(WindowFunction[tuple, tuple, str, CountWindow]):
+
+    def apply(self, key: str, window: CountWindow, inputs: Iterable[tuple]):
+        result = 0
+        for i in inputs:
+            result += i[0]
+        return [(key, result)]
+
+
+class CountWindowProcessFunction(ProcessWindowFunction[tuple, tuple, str, CountWindow]):
+
+    def process(self,
+                key: str,
+                content: ProcessWindowFunction.Context,
+                elements: Iterable[tuple]) -> Iterable[tuple]:
+        return [(key, len([e for e in elements]))]
+
+    def clear(self, context: ProcessWindowFunction.Context) -> None:
+        pass