Examples with InternalSingleValueProcessAllWindowFunction org.apache.flink.streaming.runtime.operators.windowing.functions.InternalSingleValueProcessAllWindowFunction used on opensource projects

Example 1 with InternalSingleValueProcessAllWindowFunction

use of org.apache.flink.streaming.runtime.operators.windowing.functions.InternalSingleValueProcessAllWindowFunction in project flink by apache.

the class InternalWindowFunctionTest method testInternalSingleValueProcessAllWindowFunction.

@SuppressWarnings("unchecked")
@Test
public void testInternalSingleValueProcessAllWindowFunction() throws Exception {
    ProcessAllWindowFunctionMock mock = mock(ProcessAllWindowFunctionMock.class);
    InternalSingleValueProcessAllWindowFunction<Long, String, TimeWindow> windowFunction = new InternalSingleValueProcessAllWindowFunction<>(mock);
    // check setOutputType
    TypeInformation<String> stringType = BasicTypeInfo.STRING_TYPE_INFO;
    ExecutionConfig execConf = new ExecutionConfig();
    execConf.setParallelism(42);
    StreamingFunctionUtils.setOutputType(windowFunction, stringType, execConf);
    verify(mock).setOutputType(stringType, execConf);
    // check open
    Configuration config = new Configuration();
    windowFunction.open(config);
    verify(mock).open(config);
    // check setRuntimeContext
    RuntimeContext rCtx = mock(RuntimeContext.class);
    windowFunction.setRuntimeContext(rCtx);
    verify(mock).setRuntimeContext(rCtx);
    // check apply
    TimeWindow w = mock(TimeWindow.class);
    Collector<String> c = (Collector<String>) mock(Collector.class);
    InternalWindowFunction.InternalWindowContext ctx = mock(InternalWindowFunction.InternalWindowContext.class);
    windowFunction.process(((byte) 0), w, ctx, 23L, c);
    verify(mock).process((ProcessAllWindowFunctionMock.Context) anyObject(), (Iterable<Long>) argThat(IsIterableContainingInOrder.contains(23L)), eq(c));
    // check close
    windowFunction.close();
    verify(mock).close();
}

Example 2 with InternalSingleValueProcessAllWindowFunction

use of org.apache.flink.streaming.runtime.operators.windowing.functions.InternalSingleValueProcessAllWindowFunction in project flink by apache.

the class AllWindowedStream method reduce.

/**
 * Applies the given window function to each window. The window function is called for each
 * evaluation of the window for each key individually. The output of the window function is
 * interpreted as a regular non-windowed stream.
 *
 * <p>Arriving data is incrementally aggregated using the given reducer.
 *
 * @param reduceFunction The reduce function that is used for incremental aggregation.
 * @param function The process window function.
 * @param resultType Type information for the result type of the window function
 * @return The data stream that is the result of applying the window function to the window.
 */
@PublicEvolving
public <R> SingleOutputStreamOperator<R> reduce(ReduceFunction<T> reduceFunction, ProcessAllWindowFunction<T, R, W> function, TypeInformation<R> resultType) {
    if (reduceFunction instanceof RichFunction) {
        throw new UnsupportedOperationException("ReduceFunction of reduce can not be a RichFunction.");
    }
    // clean the closures
    function = input.getExecutionEnvironment().clean(function);
    reduceFunction = input.getExecutionEnvironment().clean(reduceFunction);
    String callLocation = Utils.getCallLocationName();
    String udfName = "AllWindowedStream." + callLocation;
    String opName;
    KeySelector<T, Byte> keySel = input.getKeySelector();
    OneInputStreamOperator<T, R> operator;
    if (evictor != null) {
        @SuppressWarnings({ "unchecked", "rawtypes" }) TypeSerializer<StreamRecord<T>> streamRecordSerializer = (TypeSerializer<StreamRecord<T>>) new StreamElementSerializer(input.getType().createSerializer(getExecutionEnvironment().getConfig()));
        ListStateDescriptor<StreamRecord<T>> stateDesc = new ListStateDescriptor<>("window-contents", streamRecordSerializer);
        opName = "TriggerWindow(" + windowAssigner + ", " + stateDesc + ", " + trigger + ", " + evictor + ", " + udfName + ")";
        operator = new EvictingWindowOperator<>(windowAssigner, windowAssigner.getWindowSerializer(getExecutionEnvironment().getConfig()), keySel, input.getKeyType().createSerializer(getExecutionEnvironment().getConfig()), stateDesc, new InternalIterableProcessAllWindowFunction<>(new ReduceApplyProcessAllWindowFunction<>(reduceFunction, function)), trigger, evictor, allowedLateness, lateDataOutputTag);
    } else {
        ReducingStateDescriptor<T> stateDesc = new ReducingStateDescriptor<>("window-contents", reduceFunction, input.getType().createSerializer(getExecutionEnvironment().getConfig()));
        opName = "TriggerWindow(" + windowAssigner + ", " + stateDesc + ", " + trigger + ", " + udfName + ")";
        operator = new WindowOperator<>(windowAssigner, windowAssigner.getWindowSerializer(getExecutionEnvironment().getConfig()), keySel, input.getKeyType().createSerializer(getExecutionEnvironment().getConfig()), stateDesc, new InternalSingleValueProcessAllWindowFunction<>(function), trigger, allowedLateness, lateDataOutputTag);
    }
    return input.transform(opName, resultType, operator).forceNonParallel();
}

Example 3 with InternalSingleValueProcessAllWindowFunction

use of org.apache.flink.streaming.runtime.operators.windowing.functions.InternalSingleValueProcessAllWindowFunction in project flink by apache.

the class AllWindowedStream method fold.

/**
	 * Applies the given window function to each window. The window function is called for each
	 * evaluation of the window for each key individually. The output of the window function is
	 * interpreted as a regular non-windowed stream.
	 *
	 * <p>
	 * Arriving data is incrementally aggregated using the given fold function.
	 *
	 * @param initialValue The initial value of the fold.
	 * @param foldFunction The fold function that is used for incremental aggregation.
	 * @param function The process window function.
	 * @param foldAccumulatorType Type information for the result type of the fold function
	 * @param resultType Type information for the result type of the window function
	 * @return The data stream that is the result of applying the window function to the window.
	 */
@PublicEvolving
public <ACC, R> SingleOutputStreamOperator<R> fold(ACC initialValue, FoldFunction<T, ACC> foldFunction, ProcessAllWindowFunction<ACC, R, W> function, TypeInformation<ACC> foldAccumulatorType, TypeInformation<R> resultType) {
    if (foldFunction instanceof RichFunction) {
        throw new UnsupportedOperationException("FoldFunction of fold can not be a RichFunction.");
    }
    if (windowAssigner instanceof MergingWindowAssigner) {
        throw new UnsupportedOperationException("Fold cannot be used with a merging WindowAssigner.");
    }
    //clean the closures
    function = input.getExecutionEnvironment().clean(function);
    foldFunction = input.getExecutionEnvironment().clean(foldFunction);
    String callLocation = Utils.getCallLocationName();
    String udfName = "AllWindowedStream." + callLocation;
    String opName;
    KeySelector<T, Byte> keySel = input.getKeySelector();
    OneInputStreamOperator<T, R> operator;
    if (evictor != null) {
        @SuppressWarnings({ "unchecked", "rawtypes" }) TypeSerializer<StreamRecord<T>> streamRecordSerializer = (TypeSerializer<StreamRecord<T>>) new StreamElementSerializer(input.getType().createSerializer(getExecutionEnvironment().getConfig()));
        ListStateDescriptor<StreamRecord<T>> stateDesc = new ListStateDescriptor<>("window-contents", streamRecordSerializer);
        opName = "TriggerWindow(" + windowAssigner + ", " + stateDesc + ", " + trigger + ", " + evictor + ", " + udfName + ")";
        operator = new EvictingWindowOperator<>(windowAssigner, windowAssigner.getWindowSerializer(getExecutionEnvironment().getConfig()), keySel, input.getKeyType().createSerializer(getExecutionEnvironment().getConfig()), stateDesc, new InternalIterableProcessAllWindowFunction<>(new FoldApplyProcessAllWindowFunction<>(initialValue, foldFunction, function, foldAccumulatorType)), trigger, evictor, allowedLateness, lateDataOutputTag);
    } else {
        FoldingStateDescriptor<T, ACC> stateDesc = new FoldingStateDescriptor<>("window-contents", initialValue, foldFunction, foldAccumulatorType.createSerializer(getExecutionEnvironment().getConfig()));
        opName = "TriggerWindow(" + windowAssigner + ", " + stateDesc + ", " + trigger + ", " + udfName + ")";
        operator = new WindowOperator<>(windowAssigner, windowAssigner.getWindowSerializer(getExecutionEnvironment().getConfig()), keySel, input.getKeyType().createSerializer(getExecutionEnvironment().getConfig()), stateDesc, new InternalSingleValueProcessAllWindowFunction<>(function), trigger, allowedLateness, lateDataOutputTag);
    }
    return input.transform(opName, resultType, operator).forceNonParallel();
}

Example 4 with InternalSingleValueProcessAllWindowFunction

use of org.apache.flink.streaming.runtime.operators.windowing.functions.InternalSingleValueProcessAllWindowFunction in project flink by apache.

the class AllWindowedStream method aggregate.

/**
 * Applies the given window function to each window. The window function is called for each
 * evaluation of the window for each key individually. The output of the window function is
 * interpreted as a regular non-windowed stream.
 *
 * <p>Arriving data is incrementally aggregated using the given aggregate function. This means
 * that the window function typically has only a single value to process when called.
 *
 * @param aggregateFunction The aggregation function that is used for incremental aggregation.
 * @param windowFunction The process window function.
 * @param accumulatorType Type information for the internal accumulator type of the aggregation
 *     function
 * @param resultType Type information for the result type of the window function
 * @return The data stream that is the result of applying the window function to the window.
 * @param <ACC> The type of the AggregateFunction's accumulator
 * @param <V> The type of AggregateFunction's result, and the WindowFunction's input
 * @param <R> The type of the elements in the resulting stream, equal to the WindowFunction's
 *     result type
 */
@PublicEvolving
public <ACC, V, R> SingleOutputStreamOperator<R> aggregate(AggregateFunction<T, ACC, V> aggregateFunction, ProcessAllWindowFunction<V, R, W> windowFunction, TypeInformation<ACC> accumulatorType, TypeInformation<V> aggregateResultType, TypeInformation<R> resultType) {
    checkNotNull(aggregateFunction, "aggregateFunction");
    checkNotNull(windowFunction, "windowFunction");
    checkNotNull(accumulatorType, "accumulatorType");
    checkNotNull(aggregateResultType, "aggregateResultType");
    checkNotNull(resultType, "resultType");
    if (aggregateFunction instanceof RichFunction) {
        throw new UnsupportedOperationException("This aggregate function cannot be a RichFunction.");
    }
    // clean the closures
    windowFunction = input.getExecutionEnvironment().clean(windowFunction);
    aggregateFunction = input.getExecutionEnvironment().clean(aggregateFunction);
    final String callLocation = Utils.getCallLocationName();
    final String udfName = "AllWindowedStream." + callLocation;
    final String opName = windowAssigner.getClass().getSimpleName();
    final String opDescription;
    final KeySelector<T, Byte> keySel = input.getKeySelector();
    OneInputStreamOperator<T, R> operator;
    if (evictor != null) {
        @SuppressWarnings({ "unchecked", "rawtypes" }) TypeSerializer<StreamRecord<T>> streamRecordSerializer = (TypeSerializer<StreamRecord<T>>) new StreamElementSerializer(input.getType().createSerializer(getExecutionEnvironment().getConfig()));
        ListStateDescriptor<StreamRecord<T>> stateDesc = new ListStateDescriptor<>("window-contents", streamRecordSerializer);
        opDescription = "TriggerWindow(" + windowAssigner + ", " + stateDesc + ", " + trigger + ", " + evictor + ", " + udfName + ")";
        operator = new EvictingWindowOperator<>(windowAssigner, windowAssigner.getWindowSerializer(getExecutionEnvironment().getConfig()), keySel, input.getKeyType().createSerializer(getExecutionEnvironment().getConfig()), stateDesc, new InternalAggregateProcessAllWindowFunction<>(aggregateFunction, windowFunction), trigger, evictor, allowedLateness, lateDataOutputTag);
    } else {
        AggregatingStateDescriptor<T, ACC, V> stateDesc = new AggregatingStateDescriptor<>("window-contents", aggregateFunction, accumulatorType.createSerializer(getExecutionEnvironment().getConfig()));
        opDescription = "TriggerWindow(" + windowAssigner + ", " + stateDesc + ", " + trigger + ", " + udfName + ")";
        operator = new WindowOperator<>(windowAssigner, windowAssigner.getWindowSerializer(getExecutionEnvironment().getConfig()), keySel, input.getKeyType().createSerializer(getExecutionEnvironment().getConfig()), stateDesc, new InternalSingleValueProcessAllWindowFunction<>(windowFunction), trigger, allowedLateness, lateDataOutputTag);
    }
    return input.transform(opName, resultType, operator).setDescription(opDescription).forceNonParallel();
}