本文整理了Java中org.apache.flink.streaming.api.datastream.AllWindowedStream.getProcessAllWindowFunctionReturnType()方法的一些代码示例，展示了AllWindowedStream.getProcessAllWindowFunctionReturnType()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。AllWindowedStream.getProcessAllWindowFunctionReturnType()方法的具体详情如下：
包路径：org.apache.flink.streaming.api.datastream.AllWindowedStream
类名称：AllWindowedStream
方法名：getProcessAllWindowFunctionReturnType

AllWindowedStream.getProcessAllWindowFunctionReturnType介绍

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代码示例

代码示例来源：origin: apache/flink

/**
 * 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.
 * @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 = getProcessAllWindowFunctionReturnType(function, input.getType());
  return reduce(reduceFunction, function, resultType);
}

代码示例来源：origin: apache/flink

/**
 * 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 window function.
 * @return The data stream that is the result of applying the window function to the window.
 *
 * @deprecated use {@link #aggregate(AggregateFunction, ProcessAllWindowFunction)} instead
 */
@PublicEvolving
@Deprecated
public <ACC, R> SingleOutputStreamOperator<R> fold(ACC initialValue, FoldFunction<T, ACC> foldFunction, ProcessAllWindowFunction<ACC, R, W> function) {
  TypeInformation<ACC> foldAccumulatorType = TypeExtractor.getFoldReturnTypes(foldFunction, input.getType(),
    Utils.getCallLocationName(), true);
  TypeInformation<R> resultType = getProcessAllWindowFunctionReturnType(function, foldAccumulatorType);
  return fold(initialValue, foldFunction, function, foldAccumulatorType, resultType);
}

代码示例来源：origin: apache/flink

/**
 * Applies the given window function to each window. The window function is called for each
 * evaluation of the window. The output of the window function is
 * interpreted as a regular non-windowed stream.
 *
 * <p>Not that this function requires that all data in the windows is buffered until the window
 * is evaluated, as the function provides no means of incremental aggregation.
 *
 * @param function The process window function.
 * @return The data stream that is the result of applying the window function to the window.
 */
@PublicEvolving
public <R> SingleOutputStreamOperator<R> process(ProcessAllWindowFunction<T, R, W> function) {
  String callLocation = Utils.getCallLocationName();
  function = input.getExecutionEnvironment().clean(function);
  TypeInformation<R> resultType = getProcessAllWindowFunctionReturnType(function, getInputType());
  return apply(new InternalIterableProcessAllWindowFunction<>(function), resultType, callLocation);
}

代码示例来源：origin: apache/flink

aggFunction, input.getType(), null, false);
TypeInformation<R> resultType = getProcessAllWindowFunctionReturnType(windowFunction, aggResultType);

代码示例来源：origin: org.apache.flink/flink-streaming-java_2.11

/**
 * 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.
 * @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 = getProcessAllWindowFunctionReturnType(function, input.getType());
  return reduce(reduceFunction, function, resultType);
}

代码示例来源：origin: org.apache.flink/flink-streaming-java_2.10

/**
 * 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.
 * @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 = getProcessAllWindowFunctionReturnType(function, input.getType());
  return reduce(reduceFunction, function, resultType);
}

代码示例来源：origin: org.apache.flink/flink-streaming-java

/**
 * 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.
 * @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 = getProcessAllWindowFunctionReturnType(function, input.getType());
  return reduce(reduceFunction, function, resultType);
}

代码示例来源：origin: org.apache.flink/flink-streaming-java_2.10

/**
 * 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 window function.
 * @return The data stream that is the result of applying the window function to the window.
 *
 * @deprecated use {@link #aggregate(AggregateFunction, ProcessAllWindowFunction)} instead
 */
@PublicEvolving
@Deprecated
public <ACC, R> SingleOutputStreamOperator<R> fold(ACC initialValue, FoldFunction<T, ACC> foldFunction, ProcessAllWindowFunction<ACC, R, W> function) {
  TypeInformation<ACC> foldAccumulatorType = TypeExtractor.getFoldReturnTypes(foldFunction, input.getType(),
    Utils.getCallLocationName(), true);
  TypeInformation<R> resultType = getProcessAllWindowFunctionReturnType(function, foldAccumulatorType);
  return fold(initialValue, foldFunction, function, foldAccumulatorType, resultType);
}

代码示例来源：origin: org.apache.flink/flink-streaming-java_2.11

/**
 * 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 window function.
 * @return The data stream that is the result of applying the window function to the window.
 *
 * @deprecated use {@link #aggregate(AggregateFunction, ProcessAllWindowFunction)} instead
 */
@PublicEvolving
@Deprecated
public <ACC, R> SingleOutputStreamOperator<R> fold(ACC initialValue, FoldFunction<T, ACC> foldFunction, ProcessAllWindowFunction<ACC, R, W> function) {
  TypeInformation<ACC> foldAccumulatorType = TypeExtractor.getFoldReturnTypes(foldFunction, input.getType(),
    Utils.getCallLocationName(), true);
  TypeInformation<R> resultType = getProcessAllWindowFunctionReturnType(function, foldAccumulatorType);
  return fold(initialValue, foldFunction, function, foldAccumulatorType, resultType);
}

代码示例来源：origin: org.apache.flink/flink-streaming-java

/**
 * 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 window function.
 * @return The data stream that is the result of applying the window function to the window.
 *
 * @deprecated use {@link #aggregate(AggregateFunction, ProcessAllWindowFunction)} instead
 */
@PublicEvolving
@Deprecated
public <ACC, R> SingleOutputStreamOperator<R> fold(ACC initialValue, FoldFunction<T, ACC> foldFunction, ProcessAllWindowFunction<ACC, R, W> function) {
  TypeInformation<ACC> foldAccumulatorType = TypeExtractor.getFoldReturnTypes(foldFunction, input.getType(),
    Utils.getCallLocationName(), true);
  TypeInformation<R> resultType = getProcessAllWindowFunctionReturnType(function, foldAccumulatorType);
  return fold(initialValue, foldFunction, function, foldAccumulatorType, resultType);
}

代码示例来源：origin: org.apache.flink/flink-streaming-java_2.10

/**
 * Applies the given window function to each window. The window function is called for each
 * evaluation of the window. The output of the window function is
 * interpreted as a regular non-windowed stream.
 *
 * <p>Not that this function requires that all data in the windows is buffered until the window
 * is evaluated, as the function provides no means of incremental aggregation.
 *
 * @param function The process window function.
 * @return The data stream that is the result of applying the window function to the window.
 */
@PublicEvolving
public <R> SingleOutputStreamOperator<R> process(ProcessAllWindowFunction<T, R, W> function) {
  String callLocation = Utils.getCallLocationName();
  function = input.getExecutionEnvironment().clean(function);
  TypeInformation<R> resultType = getProcessAllWindowFunctionReturnType(function, getInputType());
  return apply(new InternalIterableProcessAllWindowFunction<>(function), resultType, callLocation);
}

代码示例来源：origin: org.apache.flink/flink-streaming-java_2.11

/**
 * Applies the given window function to each window. The window function is called for each
 * evaluation of the window. The output of the window function is
 * interpreted as a regular non-windowed stream.
 *
 * <p>Not that this function requires that all data in the windows is buffered until the window
 * is evaluated, as the function provides no means of incremental aggregation.
 *
 * @param function The process window function.
 * @return The data stream that is the result of applying the window function to the window.
 */
@PublicEvolving
public <R> SingleOutputStreamOperator<R> process(ProcessAllWindowFunction<T, R, W> function) {
  String callLocation = Utils.getCallLocationName();
  function = input.getExecutionEnvironment().clean(function);
  TypeInformation<R> resultType = getProcessAllWindowFunctionReturnType(function, getInputType());
  return apply(new InternalIterableProcessAllWindowFunction<>(function), resultType, callLocation);
}

代码示例来源：origin: org.apache.flink/flink-streaming-java

/**
 * Applies the given window function to each window. The window function is called for each
 * evaluation of the window. The output of the window function is
 * interpreted as a regular non-windowed stream.
 *
 * <p>Not that this function requires that all data in the windows is buffered until the window
 * is evaluated, as the function provides no means of incremental aggregation.
 *
 * @param function The process window function.
 * @return The data stream that is the result of applying the window function to the window.
 */
@PublicEvolving
public <R> SingleOutputStreamOperator<R> process(ProcessAllWindowFunction<T, R, W> function) {
  String callLocation = Utils.getCallLocationName();
  function = input.getExecutionEnvironment().clean(function);
  TypeInformation<R> resultType = getProcessAllWindowFunctionReturnType(function, getInputType());
  return apply(new InternalIterableProcessAllWindowFunction<>(function), resultType, callLocation);
}

代码示例来源：origin: org.apache.flink/flink-streaming-java_2.11

aggFunction, input.getType(), null, false);
TypeInformation<R> resultType = getProcessAllWindowFunctionReturnType(windowFunction, aggResultType);

代码示例来源：origin: org.apache.flink/flink-streaming-java_2.10

aggFunction, input.getType(), null, false);
TypeInformation<R> resultType = getProcessAllWindowFunctionReturnType(windowFunction, aggResultType);

代码示例来源：origin: org.apache.flink/flink-streaming-java

aggFunction, input.getType(), null, false);
TypeInformation<R> resultType = getProcessAllWindowFunctionReturnType(windowFunction, aggResultType);