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Example 31 with Tuple2

use of org.apache.flink.api.java.tuple.Tuple2 in project flink by apache.

the class WindowOperatorTest method testSessionWindows.

@Test
@SuppressWarnings("unchecked")
public void testSessionWindows() throws Exception {
    closeCalled.set(0);
    final int SESSION_SIZE = 3;
    TypeInformation<Tuple2<String, Integer>> inputType = TypeInfoParser.parse("Tuple2<String, Integer>");
    ListStateDescriptor<Tuple2<String, Integer>> stateDesc = new ListStateDescriptor<>("window-contents", inputType.createSerializer(new ExecutionConfig()));
    WindowOperator<String, Tuple2<String, Integer>, Iterable<Tuple2<String, Integer>>, Tuple3<String, Long, Long>, TimeWindow> operator = new WindowOperator<>(EventTimeSessionWindows.withGap(Time.seconds(SESSION_SIZE)), new TimeWindow.Serializer(), new TupleKeySelector(), BasicTypeInfo.STRING_TYPE_INFO.createSerializer(new ExecutionConfig()), stateDesc, new InternalIterableWindowFunction<>(new SessionWindowFunction()), EventTimeTrigger.create(), 0, null);
    OneInputStreamOperatorTestHarness<Tuple2<String, Integer>, Tuple3<String, Long, Long>> testHarness = new KeyedOneInputStreamOperatorTestHarness<>(operator, new TupleKeySelector(), BasicTypeInfo.STRING_TYPE_INFO);
    ConcurrentLinkedQueue<Object> expectedOutput = new ConcurrentLinkedQueue<>();
    testHarness.open();
    // add elements out-of-order
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 0));
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 2), 1000));
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 3), 2500));
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key1", 1), 10));
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key1", 2), 1000));
    // do a snapshot, close and restore again
    OperatorStateHandles snapshot = testHarness.snapshot(0L, 0L);
    testHarness.close();
    testHarness.setup();
    testHarness.initializeState(snapshot);
    testHarness.open();
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key1", 3), 2500));
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 4), 5501));
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 5), 6000));
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 5), 6000));
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 6), 6050));
    testHarness.processWatermark(new Watermark(12000));
    expectedOutput.add(new StreamRecord<>(new Tuple3<>("key1-6", 10L, 5500L), 5499));
    expectedOutput.add(new StreamRecord<>(new Tuple3<>("key2-6", 0L, 5500L), 5499));
    expectedOutput.add(new StreamRecord<>(new Tuple3<>("key2-20", 5501L, 9050L), 9049));
    expectedOutput.add(new Watermark(12000));
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 10), 15000));
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 20), 15000));
    testHarness.processWatermark(new Watermark(17999));
    expectedOutput.add(new StreamRecord<>(new Tuple3<>("key2-30", 15000L, 18000L), 17999));
    expectedOutput.add(new Watermark(17999));
    TestHarnessUtil.assertOutputEqualsSorted("Output was not correct.", expectedOutput, testHarness.getOutput(), new Tuple3ResultSortComparator());
    testHarness.close();
}
Also used : ListStateDescriptor(org.apache.flink.api.common.state.ListStateDescriptor) ExecutionConfig(org.apache.flink.api.common.ExecutionConfig) KeyedOneInputStreamOperatorTestHarness(org.apache.flink.streaming.util.KeyedOneInputStreamOperatorTestHarness) OperatorStateHandles(org.apache.flink.streaming.runtime.tasks.OperatorStateHandles) TimeWindow(org.apache.flink.streaming.api.windowing.windows.TimeWindow) AtomicInteger(java.util.concurrent.atomic.AtomicInteger) Tuple2(org.apache.flink.api.java.tuple.Tuple2) Tuple3(org.apache.flink.api.java.tuple.Tuple3) ConcurrentLinkedQueue(java.util.concurrent.ConcurrentLinkedQueue) Watermark(org.apache.flink.streaming.api.watermark.Watermark) Test(org.junit.Test)

Example 32 with Tuple2

use of org.apache.flink.api.java.tuple.Tuple2 in project flink by apache.

the class WindowOperatorTest method testNotSideOutputDueToLatenessSessionWithHugeLatenessPurgingTrigger.

@Test
public void testNotSideOutputDueToLatenessSessionWithHugeLatenessPurgingTrigger() throws Exception {
    final int GAP_SIZE = 3;
    final long LATENESS = 10000;
    TypeInformation<Tuple2<String, Integer>> inputType = TypeInfoParser.parse("Tuple2<String, Integer>");
    ReducingStateDescriptor<Tuple2<String, Integer>> stateDesc = new ReducingStateDescriptor<>("window-contents", new SumReducer(), inputType.createSerializer(new ExecutionConfig()));
    WindowOperator<String, Tuple2<String, Integer>, Tuple2<String, Integer>, Tuple3<String, Long, Long>, TimeWindow> operator = new WindowOperator<>(EventTimeSessionWindows.withGap(Time.seconds(GAP_SIZE)), new TimeWindow.Serializer(), new TupleKeySelector(), BasicTypeInfo.STRING_TYPE_INFO.createSerializer(new ExecutionConfig()), stateDesc, new InternalSingleValueWindowFunction<>(new ReducedSessionWindowFunction()), PurgingTrigger.of(EventTimeTrigger.create()), LATENESS, null);
    OneInputStreamOperatorTestHarness<Tuple2<String, Integer>, Tuple3<String, Long, Long>> testHarness = new KeyedOneInputStreamOperatorTestHarness<>(operator, new TupleKeySelector(), BasicTypeInfo.STRING_TYPE_INFO);
    testHarness.open();
    ConcurrentLinkedQueue<Object> expected = new ConcurrentLinkedQueue<>();
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 1000));
    testHarness.processWatermark(new Watermark(1999));
    expected.add(new Watermark(1999));
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 2000));
    testHarness.processWatermark(new Watermark(4998));
    expected.add(new Watermark(4998));
    // this will not be sideoutput because the session we're adding two has maxTimestamp
    // after the current watermark
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 4500));
    // new session
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 8500));
    testHarness.processWatermark(new Watermark(7400));
    expected.add(new Watermark(7400));
    // this will merge the two sessions into one
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 7000));
    testHarness.processWatermark(new Watermark(11501));
    expected.add(new StreamRecord<>(new Tuple3<>("key2-5", 1000L, 11500L), 11499));
    expected.add(new Watermark(11501));
    // new session
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 11600));
    testHarness.processWatermark(new Watermark(14600));
    expected.add(new StreamRecord<>(new Tuple3<>("key2-1", 11600L, 14600L), 14599));
    expected.add(new Watermark(14600));
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 10000));
    expected.add(new StreamRecord<>(new Tuple3<>("key2-1", 1000L, 14600L), 14599));
    ConcurrentLinkedQueue<Object> actual = testHarness.getOutput();
    ConcurrentLinkedQueue<StreamRecord<Tuple2<String, Integer>>> sideActual = testHarness.getSideOutput(lateOutputTag);
    TestHarnessUtil.assertOutputEqualsSorted("Output was not correct.", expected, actual, new Tuple3ResultSortComparator());
    assertEquals(null, sideActual);
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 14500));
    testHarness.processWatermark(new Watermark(20000));
    expected.add(new StreamRecord<>(new Tuple3<>("key2-1", 1000L, 17500L), 17499));
    expected.add(new Watermark(20000));
    testHarness.processWatermark(new Watermark(100000));
    expected.add(new Watermark(100000));
    actual = testHarness.getOutput();
    sideActual = testHarness.getSideOutput(lateOutputTag);
    TestHarnessUtil.assertOutputEqualsSorted("Output was not correct.", expected, actual, new Tuple3ResultSortComparator());
    assertEquals(null, sideActual);
    testHarness.close();
}
Also used : ExecutionConfig(org.apache.flink.api.common.ExecutionConfig) KeyedOneInputStreamOperatorTestHarness(org.apache.flink.streaming.util.KeyedOneInputStreamOperatorTestHarness) ReducingStateDescriptor(org.apache.flink.api.common.state.ReducingStateDescriptor) StreamRecord(org.apache.flink.streaming.runtime.streamrecord.StreamRecord) TimeWindow(org.apache.flink.streaming.api.windowing.windows.TimeWindow) AtomicInteger(java.util.concurrent.atomic.AtomicInteger) Tuple2(org.apache.flink.api.java.tuple.Tuple2) Tuple3(org.apache.flink.api.java.tuple.Tuple3) ConcurrentLinkedQueue(java.util.concurrent.ConcurrentLinkedQueue) Watermark(org.apache.flink.streaming.api.watermark.Watermark) Test(org.junit.Test)

Example 33 with Tuple2

use of org.apache.flink.api.java.tuple.Tuple2 in project flink by apache.

the class WindowOperatorTest method testSideOutputDueToLatenessSessionZeroLatenessPurgingTrigger.

@Test
public void testSideOutputDueToLatenessSessionZeroLatenessPurgingTrigger() throws Exception {
    final int GAP_SIZE = 3;
    final long LATENESS = 0;
    TypeInformation<Tuple2<String, Integer>> inputType = TypeInfoParser.parse("Tuple2<String, Integer>");
    ReducingStateDescriptor<Tuple2<String, Integer>> stateDesc = new ReducingStateDescriptor<>("window-contents", new SumReducer(), inputType.createSerializer(new ExecutionConfig()));
    WindowOperator<String, Tuple2<String, Integer>, Tuple2<String, Integer>, Tuple3<String, Long, Long>, TimeWindow> operator = new WindowOperator<>(EventTimeSessionWindows.withGap(Time.seconds(GAP_SIZE)), new TimeWindow.Serializer(), new TupleKeySelector(), BasicTypeInfo.STRING_TYPE_INFO.createSerializer(new ExecutionConfig()), stateDesc, new InternalSingleValueWindowFunction<>(new ReducedSessionWindowFunction()), PurgingTrigger.of(EventTimeTrigger.create()), LATENESS, lateOutputTag);
    OneInputStreamOperatorTestHarness<Tuple2<String, Integer>, Tuple3<String, Long, Long>> testHarness = new KeyedOneInputStreamOperatorTestHarness<>(operator, new TupleKeySelector(), BasicTypeInfo.STRING_TYPE_INFO);
    testHarness.open();
    ConcurrentLinkedQueue<Object> expected = new ConcurrentLinkedQueue<>();
    ConcurrentLinkedQueue<Object> sideExpected = new ConcurrentLinkedQueue<>();
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 1000));
    testHarness.processWatermark(new Watermark(1999));
    expected.add(new Watermark(1999));
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 2000));
    testHarness.processWatermark(new Watermark(4998));
    expected.add(new Watermark(4998));
    // this will not be dropped because the session we're adding two has maxTimestamp
    // after the current watermark
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 4500));
    // new session
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 8500));
    testHarness.processWatermark(new Watermark(7400));
    expected.add(new Watermark(7400));
    // this will merge the two sessions into one
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 7000));
    testHarness.processWatermark(new Watermark(11501));
    expected.add(new StreamRecord<>(new Tuple3<>("key2-5", 1000L, 11500L), 11499));
    expected.add(new Watermark(11501));
    // new session
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 11600));
    testHarness.processWatermark(new Watermark(14600));
    expected.add(new StreamRecord<>(new Tuple3<>("key2-1", 11600L, 14600L), 14599));
    expected.add(new Watermark(14600));
    // this is side output as late
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 10000));
    sideExpected.add(new StreamRecord<>(new Tuple2<>("key2", 1), 10000));
    // this is also side output as late (we test that they are not accidentally merged)
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 10100));
    sideExpected.add(new StreamRecord<>(new Tuple2<>("key2", 1), 10100));
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 14500));
    testHarness.processWatermark(new Watermark(20000));
    expected.add(new StreamRecord<>(new Tuple3<>("key2-1", 14500L, 17500L), 17499));
    expected.add(new Watermark(20000));
    testHarness.processWatermark(new Watermark(100000));
    expected.add(new Watermark(100000));
    ConcurrentLinkedQueue<Object> actual = testHarness.getOutput();
    ConcurrentLinkedQueue<StreamRecord<Tuple2<String, Integer>>> sideActual = testHarness.getSideOutput(lateOutputTag);
    TestHarnessUtil.assertOutputEqualsSorted("Output was not correct.", expected, actual, new Tuple2ResultSortComparator());
    TestHarnessUtil.assertOutputEqualsSorted("SideOutput was not correct.", sideExpected, (Iterable) sideActual, new Tuple2ResultSortComparator());
    testHarness.close();
}
Also used : ExecutionConfig(org.apache.flink.api.common.ExecutionConfig) KeyedOneInputStreamOperatorTestHarness(org.apache.flink.streaming.util.KeyedOneInputStreamOperatorTestHarness) ReducingStateDescriptor(org.apache.flink.api.common.state.ReducingStateDescriptor) StreamRecord(org.apache.flink.streaming.runtime.streamrecord.StreamRecord) TimeWindow(org.apache.flink.streaming.api.windowing.windows.TimeWindow) AtomicInteger(java.util.concurrent.atomic.AtomicInteger) Tuple2(org.apache.flink.api.java.tuple.Tuple2) Tuple3(org.apache.flink.api.java.tuple.Tuple3) ConcurrentLinkedQueue(java.util.concurrent.ConcurrentLinkedQueue) Watermark(org.apache.flink.streaming.api.watermark.Watermark) Test(org.junit.Test)

Example 34 with Tuple2

use of org.apache.flink.api.java.tuple.Tuple2 in project flink by apache.

the class WindowOperatorTest method testLateness.

@Test
public void testLateness() throws Exception {
    final int WINDOW_SIZE = 2;
    final long LATENESS = 500;
    TypeInformation<Tuple2<String, Integer>> inputType = TypeInfoParser.parse("Tuple2<String, Integer>");
    ReducingStateDescriptor<Tuple2<String, Integer>> stateDesc = new ReducingStateDescriptor<>("window-contents", new SumReducer(), inputType.createSerializer(new ExecutionConfig()));
    WindowOperator<String, Tuple2<String, Integer>, Tuple2<String, Integer>, Tuple2<String, Integer>, TimeWindow> operator = new WindowOperator<>(TumblingEventTimeWindows.of(Time.of(WINDOW_SIZE, TimeUnit.SECONDS)), new TimeWindow.Serializer(), new TupleKeySelector(), BasicTypeInfo.STRING_TYPE_INFO.createSerializer(new ExecutionConfig()), stateDesc, new InternalSingleValueWindowFunction<>(new PassThroughWindowFunction<String, TimeWindow, Tuple2<String, Integer>>()), PurgingTrigger.of(EventTimeTrigger.create()), LATENESS, lateOutputTag);
    OneInputStreamOperatorTestHarness<Tuple2<String, Integer>, Tuple2<String, Integer>> testHarness = new KeyedOneInputStreamOperatorTestHarness<>(operator, new TupleKeySelector(), BasicTypeInfo.STRING_TYPE_INFO);
    testHarness.open();
    ConcurrentLinkedQueue<Object> expected = new ConcurrentLinkedQueue<>();
    ConcurrentLinkedQueue<Object> lateExpected = new ConcurrentLinkedQueue<>();
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 500));
    testHarness.processWatermark(new Watermark(1500));
    expected.add(new Watermark(1500));
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 1300));
    testHarness.processWatermark(new Watermark(2300));
    expected.add(new StreamRecord<>(new Tuple2<>("key2", 2), 1999));
    expected.add(new Watermark(2300));
    // this will not be sideoutput because window.maxTimestamp() + allowedLateness > currentWatermark
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 1997));
    testHarness.processWatermark(new Watermark(6000));
    // this is 1 and not 3 because the trigger fires and purges
    expected.add(new StreamRecord<>(new Tuple2<>("key2", 1), 1999));
    expected.add(new Watermark(6000));
    // this will be side output because window.maxTimestamp() + allowedLateness < currentWatermark
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 1998));
    testHarness.processWatermark(new Watermark(7000));
    lateExpected.add(new StreamRecord<>(new Tuple2<>("key2", 1), 1998));
    expected.add(new Watermark(7000));
    TestHarnessUtil.assertOutputEqualsSorted("Output was not correct.", expected, testHarness.getOutput(), new Tuple2ResultSortComparator());
    TestHarnessUtil.assertOutputEqualsSorted("SideOutput was not correct.", lateExpected, (Iterable) testHarness.getSideOutput(lateOutputTag), new Tuple2ResultSortComparator());
    testHarness.close();
}
Also used : ExecutionConfig(org.apache.flink.api.common.ExecutionConfig) KeyedOneInputStreamOperatorTestHarness(org.apache.flink.streaming.util.KeyedOneInputStreamOperatorTestHarness) ReducingStateDescriptor(org.apache.flink.api.common.state.ReducingStateDescriptor) TimeWindow(org.apache.flink.streaming.api.windowing.windows.TimeWindow) AtomicInteger(java.util.concurrent.atomic.AtomicInteger) PassThroughWindowFunction(org.apache.flink.streaming.api.functions.windowing.PassThroughWindowFunction) Tuple2(org.apache.flink.api.java.tuple.Tuple2) ConcurrentLinkedQueue(java.util.concurrent.ConcurrentLinkedQueue) Watermark(org.apache.flink.streaming.api.watermark.Watermark) Test(org.junit.Test)

Example 35 with Tuple2

use of org.apache.flink.api.java.tuple.Tuple2 in project flink by apache.

the class WindowOperatorTest method testSlidingEventTimeWindows.

private void testSlidingEventTimeWindows(OneInputStreamOperatorTestHarness<Tuple2<String, Integer>, Tuple2<String, Integer>> testHarness) throws Exception {
    ConcurrentLinkedQueue<Object> expectedOutput = new ConcurrentLinkedQueue<>();
    // add elements out-of-order
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 3999));
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 3000));
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key1", 1), 20));
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key1", 1), 0));
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key1", 1), 999));
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 1998));
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 1999));
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 1000));
    testHarness.processWatermark(new Watermark(999));
    expectedOutput.add(new StreamRecord<>(new Tuple2<>("key1", 3), 999));
    expectedOutput.add(new Watermark(999));
    TestHarnessUtil.assertOutputEqualsSorted("Output was not correct.", expectedOutput, testHarness.getOutput(), new Tuple2ResultSortComparator());
    testHarness.processWatermark(new Watermark(1999));
    expectedOutput.add(new StreamRecord<>(new Tuple2<>("key1", 3), 1999));
    expectedOutput.add(new StreamRecord<>(new Tuple2<>("key2", 3), 1999));
    expectedOutput.add(new Watermark(1999));
    TestHarnessUtil.assertOutputEqualsSorted("Output was not correct.", expectedOutput, testHarness.getOutput(), new Tuple2ResultSortComparator());
    testHarness.processWatermark(new Watermark(2999));
    expectedOutput.add(new StreamRecord<>(new Tuple2<>("key1", 3), 2999));
    expectedOutput.add(new StreamRecord<>(new Tuple2<>("key2", 3), 2999));
    expectedOutput.add(new Watermark(2999));
    TestHarnessUtil.assertOutputEqualsSorted("Output was not correct.", expectedOutput, testHarness.getOutput(), new Tuple2ResultSortComparator());
    // do a snapshot, close and restore again
    OperatorStateHandles snapshot = testHarness.snapshot(0L, 0L);
    testHarness.close();
    testHarness.setup();
    testHarness.initializeState(snapshot);
    testHarness.open();
    testHarness.processWatermark(new Watermark(3999));
    expectedOutput.add(new StreamRecord<>(new Tuple2<>("key2", 5), 3999));
    expectedOutput.add(new Watermark(3999));
    TestHarnessUtil.assertOutputEqualsSorted("Output was not correct.", expectedOutput, testHarness.getOutput(), new Tuple2ResultSortComparator());
    testHarness.processWatermark(new Watermark(4999));
    expectedOutput.add(new StreamRecord<>(new Tuple2<>("key2", 2), 4999));
    expectedOutput.add(new Watermark(4999));
    TestHarnessUtil.assertOutputEqualsSorted("Output was not correct.", expectedOutput, testHarness.getOutput(), new Tuple2ResultSortComparator());
    testHarness.processWatermark(new Watermark(5999));
    expectedOutput.add(new StreamRecord<>(new Tuple2<>("key2", 2), 5999));
    expectedOutput.add(new Watermark(5999));
    TestHarnessUtil.assertOutputEqualsSorted("Output was not correct.", expectedOutput, testHarness.getOutput(), new Tuple2ResultSortComparator());
    // those don't have any effect...
    testHarness.processWatermark(new Watermark(6999));
    testHarness.processWatermark(new Watermark(7999));
    expectedOutput.add(new Watermark(6999));
    expectedOutput.add(new Watermark(7999));
    TestHarnessUtil.assertOutputEqualsSorted("Output was not correct.", expectedOutput, testHarness.getOutput(), new Tuple2ResultSortComparator());
}
Also used : OperatorStateHandles(org.apache.flink.streaming.runtime.tasks.OperatorStateHandles) Tuple2(org.apache.flink.api.java.tuple.Tuple2) ConcurrentLinkedQueue(java.util.concurrent.ConcurrentLinkedQueue) Watermark(org.apache.flink.streaming.api.watermark.Watermark)

Aggregations

Tuple2 (org.apache.flink.api.java.tuple.Tuple2)813 Test (org.junit.Test)643 ExecutionEnvironment (org.apache.flink.api.java.ExecutionEnvironment)373 StreamExecutionEnvironment (org.apache.flink.streaming.api.environment.StreamExecutionEnvironment)192 Tuple3 (org.apache.flink.api.java.tuple.Tuple3)130 Plan (org.apache.flink.api.common.Plan)100 TimeWindow (org.apache.flink.streaming.api.windowing.windows.TimeWindow)99 OptimizedPlan (org.apache.flink.optimizer.plan.OptimizedPlan)96 OneInputTransformation (org.apache.flink.streaming.api.transformations.OneInputTransformation)81 ExecutionConfig (org.apache.flink.api.common.ExecutionConfig)72 SinkPlanNode (org.apache.flink.optimizer.plan.SinkPlanNode)65 ArrayList (java.util.ArrayList)54 ListStateDescriptor (org.apache.flink.api.common.state.ListStateDescriptor)52 TestData (org.apache.flink.runtime.operators.testutils.TestData)51 KeyedOneInputStreamOperatorTestHarness (org.apache.flink.streaming.util.KeyedOneInputStreamOperatorTestHarness)44 EventTimeTrigger (org.apache.flink.streaming.api.windowing.triggers.EventTimeTrigger)42 ConcurrentLinkedQueue (java.util.concurrent.ConcurrentLinkedQueue)40 InvalidProgramException (org.apache.flink.api.common.InvalidProgramException)38 SingleInputPlanNode (org.apache.flink.optimizer.plan.SingleInputPlanNode)38 ReducingStateDescriptor (org.apache.flink.api.common.state.ReducingStateDescriptor)37