use of org.apache.flink.api.common.functions.RichFunction in project flink by apache.
the class AllWindowedStream method apply.
/**
* 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 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.
* @deprecated Use {@link #reduce(ReduceFunction, AllWindowFunction, TypeInformation)} instead.
*/
@Deprecated
public <R> SingleOutputStreamOperator<R> apply(ReduceFunction<T> reduceFunction, AllWindowFunction<T, R, W> function, TypeInformation<R> resultType) {
if (reduceFunction instanceof RichFunction) {
throw new UnsupportedOperationException("ReduceFunction of apply 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 InternalIterableAllWindowFunction<>(new ReduceApplyAllWindowFunction<>(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 InternalSingleValueAllWindowFunction<>(function), trigger, allowedLateness, lateDataOutputTag);
}
return input.transform(opName, resultType, operator).forceNonParallel();
}
use of org.apache.flink.api.common.functions.RichFunction 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();
}
use of org.apache.flink.api.common.functions.RichFunction 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();
}
use of org.apache.flink.api.common.functions.RichFunction in project flink by apache.
the class AllWindowedStream method apply.
/**
* 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.
* @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.
*
* @deprecated Use {@link #fold(Object, FoldFunction, AllWindowFunction, TypeInformation, TypeInformation)} instead.
*/
@Deprecated
public <R> SingleOutputStreamOperator<R> apply(R initialValue, FoldFunction<T, R> foldFunction, AllWindowFunction<R, R, W> function, TypeInformation<R> resultType) {
if (foldFunction instanceof RichFunction) {
throw new UnsupportedOperationException("ReduceFunction of apply 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 InternalIterableAllWindowFunction<>(new FoldApplyAllWindowFunction<>(initialValue, foldFunction, function, resultType)), trigger, evictor, allowedLateness, lateDataOutputTag);
} else {
FoldingStateDescriptor<T, R> stateDesc = new FoldingStateDescriptor<>("window-contents", initialValue, foldFunction, resultType.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 InternalSingleValueAllWindowFunction<>(function), trigger, allowedLateness, lateDataOutputTag);
}
return input.transform(opName, resultType, operator).forceNonParallel();
}
use of org.apache.flink.api.common.functions.RichFunction in project flink by apache.
the class WindowedStream method apply.
/**
* 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 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.
*
* @deprecated Use {@link #reduce(ReduceFunction, WindowFunction, TypeInformation)} instead.
*/
@Deprecated
public <R> SingleOutputStreamOperator<R> apply(ReduceFunction<T> reduceFunction, WindowFunction<T, R, K, W> function, TypeInformation<R> resultType) {
if (reduceFunction instanceof RichFunction) {
throw new UnsupportedOperationException("ReduceFunction of apply can not be a RichFunction.");
}
//clean the closures
function = input.getExecutionEnvironment().clean(function);
reduceFunction = input.getExecutionEnvironment().clean(reduceFunction);
String callLocation = Utils.getCallLocationName();
String udfName = "WindowedStream." + callLocation;
String opName;
KeySelector<T, K> 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 InternalIterableWindowFunction<>(new ReduceApplyWindowFunction<>(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 InternalSingleValueWindowFunction<>(function), trigger, allowedLateness, lateDataOutputTag);
}
return input.transform(opName, resultType, operator);
}
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