Examples with Tuple4 org.apache.flink.api.java.tuple.Tuple4 used on opensource projects

Example 41 with Tuple4

use of org.apache.flink.api.java.tuple.Tuple4 in project flink by apache.

the class AbstractEventTimeWindowCheckpointingITCase method testTumblingTimeWindow.

// ------------------------------------------------------------------------
@Test
public void testTumblingTimeWindow() {
    final int NUM_ELEMENTS_PER_KEY = numElementsPerKey();
    final int WINDOW_SIZE = windowSize();
    final int NUM_KEYS = numKeys();
    FailingSource.reset();
    try {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.createRemoteEnvironment("localhost", cluster.getLeaderRPCPort());
        env.setParallelism(PARALLELISM);
        env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime);
        env.enableCheckpointing(100);
        env.setRestartStrategy(RestartStrategies.fixedDelayRestart(3, 0));
        env.getConfig().disableSysoutLogging();
        env.setStateBackend(this.stateBackend);
        env.addSource(new FailingSource(NUM_KEYS, NUM_ELEMENTS_PER_KEY, NUM_ELEMENTS_PER_KEY / 3)).rebalance().keyBy(0).timeWindow(Time.of(WINDOW_SIZE, MILLISECONDS)).apply(new RichWindowFunction<Tuple2<Long, IntType>, Tuple4<Long, Long, Long, IntType>, Tuple, TimeWindow>() {

            private boolean open = false;

            @Override
            public void open(Configuration parameters) {
                assertEquals(PARALLELISM, getRuntimeContext().getNumberOfParallelSubtasks());
                open = true;
            }

            @Override
            public void apply(Tuple tuple, TimeWindow window, Iterable<Tuple2<Long, IntType>> values, Collector<Tuple4<Long, Long, Long, IntType>> out) {
                // validate that the function has been opened properly
                assertTrue(open);
                int sum = 0;
                long key = -1;
                for (Tuple2<Long, IntType> value : values) {
                    sum += value.f1.value;
                    key = value.f0;
                }
                out.collect(new Tuple4<>(key, window.getStart(), window.getEnd(), new IntType(sum)));
            }
        }).addSink(new ValidatingSink(NUM_KEYS, NUM_ELEMENTS_PER_KEY / WINDOW_SIZE)).setParallelism(1);
        tryExecute(env, "Tumbling Window Test");
    } catch (Exception e) {
        e.printStackTrace();
        fail(e.getMessage());
    }
}

Example 42 with Tuple4

use of org.apache.flink.api.java.tuple.Tuple4 in project flink by apache.

the class AbstractEventTimeWindowCheckpointingITCase method testSlidingTimeWindow.

@Test
public void testSlidingTimeWindow() {
    final int NUM_ELEMENTS_PER_KEY = numElementsPerKey();
    final int WINDOW_SIZE = windowSize();
    final int WINDOW_SLIDE = windowSlide();
    final int NUM_KEYS = numKeys();
    FailingSource.reset();
    try {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.createRemoteEnvironment("localhost", cluster.getLeaderRPCPort());
        env.setParallelism(PARALLELISM);
        env.setMaxParallelism(2 * PARALLELISM);
        env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime);
        env.enableCheckpointing(100);
        env.setRestartStrategy(RestartStrategies.fixedDelayRestart(3, 0));
        env.getConfig().disableSysoutLogging();
        env.setStateBackend(this.stateBackend);
        env.addSource(new FailingSource(NUM_KEYS, NUM_ELEMENTS_PER_KEY, NUM_ELEMENTS_PER_KEY / 3)).rebalance().keyBy(0).timeWindow(Time.of(WINDOW_SIZE, MILLISECONDS), Time.of(WINDOW_SLIDE, MILLISECONDS)).apply(new RichWindowFunction<Tuple2<Long, IntType>, Tuple4<Long, Long, Long, IntType>, Tuple, TimeWindow>() {

            private boolean open = false;

            @Override
            public void open(Configuration parameters) {
                assertEquals(PARALLELISM, getRuntimeContext().getNumberOfParallelSubtasks());
                open = true;
            }

            @Override
            public void apply(Tuple tuple, TimeWindow window, Iterable<Tuple2<Long, IntType>> values, Collector<Tuple4<Long, Long, Long, IntType>> out) {
                // validate that the function has been opened properly
                assertTrue(open);
                int sum = 0;
                long key = -1;
                for (Tuple2<Long, IntType> value : values) {
                    sum += value.f1.value;
                    key = value.f0;
                }
                out.collect(new Tuple4<>(key, window.getStart(), window.getEnd(), new IntType(sum)));
            }
        }).addSink(new ValidatingSink(NUM_KEYS, NUM_ELEMENTS_PER_KEY / WINDOW_SLIDE)).setParallelism(1);
        tryExecute(env, "Tumbling Window Test");
    } catch (Exception e) {
        e.printStackTrace();
        fail(e.getMessage());
    }
}

Example 43 with Tuple4

use of org.apache.flink.api.java.tuple.Tuple4 in project flink by apache.

the class AbstractSortMergeOuterJoinIteratorITCase method computeOuterJoin.

@SuppressWarnings("unchecked, rawtypes")
private List<Tuple4<String, String, String, Object>> computeOuterJoin(ResettableMutableObjectIterator<Tuple2<String, String>> input1, ResettableMutableObjectIterator<Tuple2<String, Integer>> input2, OuterJoinType outerJoinType) throws Exception {
    input1.reset();
    input2.reset();
    AbstractMergeOuterJoinIterator iterator = createOuterJoinIterator(outerJoinType, input1, input2, serializer1, comparator1, serializer2, comparator2, pairComp, this.memoryManager, this.ioManager, PAGES_FOR_BNLJN, this.parentTask);
    List<Tuple4<String, String, String, Object>> actual = new ArrayList<>();
    ListCollector<Tuple4<String, String, String, Object>> collector = new ListCollector<>(actual);
    while (iterator.callWithNextKey(new SimpleTupleJoinFunction(), collector)) ;
    iterator.close();
    return actual;
}