Modifier and Type | Method and Description |
---|---|
void |
CoGroupFunction.coGroup(Iterable<IN1> first,
Iterable<IN2> second,
Collector<O> out)
This method must be implemented to provide a user implementation of a
coGroup.
|
abstract void |
RichCoGroupFunction.coGroup(Iterable<IN1> first,
Iterable<IN2> second,
Collector<OUT> out) |
abstract void |
RichGroupCombineFunction.combine(Iterable<IN> values,
Collector<OUT> out) |
void |
GroupCombineFunction.combine(Iterable<IN> values,
Collector<OUT> out)
The combine method, called (potentially multiple timed) with subgroups of elements.
|
abstract void |
RichFlatMapFunction.flatMap(IN value,
Collector<OUT> out) |
void |
FlatMapFunction.flatMap(T value,
Collector<O> out)
The core method of the FlatMapFunction.
|
abstract void |
RichFlatJoinFunction.join(IN1 first,
IN2 second,
Collector<OUT> out) |
void |
FlatJoinFunction.join(IN1 first,
IN2 second,
Collector<OUT> out)
The join method, called once per joined pair of elements.
|
abstract void |
RichMapPartitionFunction.mapPartition(Iterable<I> values,
Collector<O> out) |
void |
MapPartitionFunction.mapPartition(Iterable<T> values,
Collector<O> out)
A user-implemented function that modifies or transforms an incoming object.
|
abstract void |
RichGroupReduceFunction.reduce(Iterable<IN> values,
Collector<OUT> out) |
void |
GroupReduceFunction.reduce(Iterable<T> values,
Collector<O> out)
The reduce method.
|
Modifier and Type | Class and Description |
---|---|
class |
CopyingListCollector<T> |
class |
ListCollector<T>
A
Collector that puts the collected elements into a given list. |
Modifier and Type | Method and Description |
---|---|
void |
BulkIterationBase.TerminationCriterionMapper.flatMap(X in,
Collector<X> out) |
Modifier and Type | Method and Description |
---|---|
void |
FirstReducer.combine(Iterable<T> values,
Collector<T> out) |
void |
FlatMapIterator.flatMap(IN value,
Collector<OUT> out)
Delegates calls to the
FlatMapIterator.flatMap(Object) method. |
void |
SampleInPartition.mapPartition(Iterable<T> values,
Collector<IntermediateSampleData<T>> out) |
void |
SampleWithFraction.mapPartition(Iterable<T> values,
Collector<T> out) |
void |
GroupReduceIterator.reduce(Iterable<IN> values,
Collector<OUT> out) |
void |
SampleInCoordinator.reduce(Iterable<IntermediateSampleData<T>> values,
Collector<T> out) |
void |
FirstReducer.reduce(Iterable<T> values,
Collector<T> out) |
Modifier and Type | Method and Description |
---|---|
void |
AggregateOperator.AggregatingUdf.combine(Iterable<T> records,
Collector<T> out) |
void |
JoinOperator.DefaultJoin.WrappingFlatJoinFunction.join(IN1 left,
IN2 right,
Collector<OUT> out) |
void |
JoinOperator.ProjectFlatJoinFunction.join(T1 in1,
T2 in2,
Collector<R> out) |
void |
JoinOperator.DefaultFlatJoinFunction.join(T1 first,
T2 second,
Collector<Tuple2<T1,T2>> out) |
void |
AggregateOperator.AggregatingUdf.reduce(Iterable<T> records,
Collector<T> out) |
Modifier and Type | Class and Description |
---|---|
class |
Tuple3WrappingCollector<IN,K1,K2>
Needed to wrap tuples to
Tuple3<groupKey, sortKey, value> for combine method of group reduce with key selector sorting |
class |
TupleWrappingCollector<IN,K>
Needed to wrap tuples to
Tuple2<key, value> pairs for combine method of group reduce with key selector function |
Modifier and Type | Method and Description |
---|---|
void |
PlanRightUnwrappingCoGroupOperator.TupleRightUnwrappingCoGrouper.coGroup(Iterable<I1> records1,
Iterable<Tuple2<K,I2>> records2,
Collector<OUT> out) |
void |
PlanLeftUnwrappingCoGroupOperator.TupleLeftUnwrappingCoGrouper.coGroup(Iterable<Tuple2<K,I1>> records1,
Iterable<I2> records2,
Collector<OUT> out) |
void |
PlanBothUnwrappingCoGroupOperator.TupleBothUnwrappingCoGrouper.coGroup(Iterable<Tuple2<K,I1>> records1,
Iterable<Tuple2<K,I2>> records2,
Collector<OUT> out) |
void |
RichCombineToGroupCombineWrapper.combine(Iterable<IN> values,
Collector<IN> out) |
void |
CombineToGroupCombineWrapper.combine(Iterable<IN> values,
Collector<IN> out) |
void |
PlanUnwrappingGroupCombineOperator.TupleUnwrappingGroupCombiner.combine(Iterable<Tuple2<K,IN>> values,
Collector<OUT> out) |
void |
PlanUnwrappingReduceGroupOperator.TupleUnwrappingGroupCombinableGroupReducer.combine(Iterable<Tuple2<K,IN>> values,
Collector<Tuple2<K,IN>> out) |
void |
PlanUnwrappingSortedGroupCombineOperator.TupleUnwrappingGroupReducer.combine(Iterable<Tuple3<K1,K2,IN>> values,
Collector<OUT> out) |
void |
PlanUnwrappingSortedReduceGroupOperator.TupleUnwrappingGroupCombinableGroupReducer.combine(Iterable<Tuple3<K1,K2,IN>> values,
Collector<Tuple3<K1,K2,IN>> out) |
void |
PlanFilterOperator.FlatMapFilter.flatMap(T value,
Collector<T> out) |
void |
TupleRightUnwrappingJoiner.join(I1 value1,
Tuple2<K,I2> value2,
Collector<OUT> collector) |
void |
TupleLeftUnwrappingJoiner.join(Tuple2<K,I1> value1,
I2 value2,
Collector<OUT> collector) |
void |
TupleUnwrappingJoiner.join(Tuple2<K,I1> value1,
Tuple2<K,I2> value2,
Collector<OUT> collector) |
void |
RichCombineToGroupCombineWrapper.reduce(Iterable<IN> values,
Collector<OUT> out) |
void |
CombineToGroupCombineWrapper.reduce(Iterable<IN> values,
Collector<OUT> out) |
void |
PlanUnwrappingReduceGroupOperator.TupleUnwrappingGroupCombinableGroupReducer.reduce(Iterable<Tuple2<K,IN>> values,
Collector<OUT> out) |
void |
PlanUnwrappingReduceGroupOperator.TupleUnwrappingNonCombinableGroupReducer.reduce(Iterable<Tuple2<K,IN>> values,
Collector<OUT> out) |
void |
PlanUnwrappingSortedReduceGroupOperator.TupleUnwrappingGroupCombinableGroupReducer.reduce(Iterable<Tuple3<K1,K2,IN>> values,
Collector<OUT> out) |
void |
PlanUnwrappingSortedReduceGroupOperator.TupleUnwrappingNonCombinableGroupReducer.reduce(Iterable<Tuple3<K1,K2,IN>> values,
Collector<OUT> out) |
void |
TupleWrappingCollector.set(Collector<Tuple2<K,IN>> wrappedCollector) |
void |
Tuple3WrappingCollector.set(Collector<Tuple3<K1,K2,IN>> wrappedCollector) |
Modifier and Type | Method and Description |
---|---|
<O> DataSet<O> |
CoGroupDataSet.apply(scala.Function3<scala.collection.Iterator<L>,scala.collection.Iterator<R>,Collector<O>,scala.runtime.BoxedUnit> fun,
TypeInformation<O> evidence$3,
scala.reflect.ClassTag<O> evidence$4)
Creates a new
DataSet where the result for each pair of co-grouped element lists is the
result of the given function. |
<O> DataSet<O> |
JoinDataSet.apply(scala.Function3<L,R,Collector<O>,scala.runtime.BoxedUnit> fun,
TypeInformation<O> evidence$3,
scala.reflect.ClassTag<O> evidence$4)
Creates a new
DataSet by passing each pair of joined values to the given function. |
<O> DataSet<O> |
JoinFunctionAssigner.apply(scala.Function3<L,R,Collector<O>,scala.runtime.BoxedUnit> fun,
TypeInformation<O> evidence$22,
scala.reflect.ClassTag<O> evidence$23) |
<R> DataSet<R> |
GroupedDataSet.combineGroup(scala.Function2<scala.collection.Iterator<T>,Collector<R>,scala.runtime.BoxedUnit> fun,
TypeInformation<R> evidence$10,
scala.reflect.ClassTag<R> evidence$11)
Applies a CombineFunction on a grouped
DataSet . |
<R> DataSet<R> |
DataSet.combineGroup(scala.Function2<scala.collection.Iterator<T>,Collector<R>,scala.runtime.BoxedUnit> fun,
TypeInformation<R> evidence$26,
scala.reflect.ClassTag<R> evidence$27)
Applies a GroupCombineFunction on a grouped
DataSet . |
<R> DataSet<R> |
DataSet.flatMap(scala.Function2<T,Collector<R>,scala.runtime.BoxedUnit> fun,
TypeInformation<R> evidence$14,
scala.reflect.ClassTag<R> evidence$15)
Creates a new DataSet by applying the given function to every element and flattening
the results.
|
<R> DataSet<R> |
DataSet.mapPartition(scala.Function2<scala.collection.Iterator<T>,Collector<R>,scala.runtime.BoxedUnit> fun,
TypeInformation<R> evidence$8,
scala.reflect.ClassTag<R> evidence$9)
Creates a new DataSet by applying the given function to each parallel partition of the
DataSet.
|
<R> DataSet<R> |
GroupedDataSet.reduceGroup(scala.Function2<scala.collection.Iterator<T>,Collector<R>,scala.runtime.BoxedUnit> fun,
TypeInformation<R> evidence$6,
scala.reflect.ClassTag<R> evidence$7)
Creates a new
DataSet by passing for each group (elements with the same key) the list
of elements to the group reduce function. |
<R> DataSet<R> |
DataSet.reduceGroup(scala.Function2<scala.collection.Iterator<T>,Collector<R>,scala.runtime.BoxedUnit> fun,
TypeInformation<R> evidence$20,
scala.reflect.ClassTag<R> evidence$21)
Creates a new
DataSet by passing all elements in this DataSet to the group reduce function. |
Modifier and Type | Method and Description |
---|---|
void |
ScalaAggregateOperator.AggregatingUdf.combine(Iterable<T> records,
Collector<T> out) |
void |
ScalaAggregateOperator.AggregatingUdf.reduce(Iterable<T> records,
Collector<T> out) |
Modifier and Type | Method and Description |
---|---|
void |
PatternFlatSelectFunction.flatSelect(Map<String,IN> pattern,
Collector<OUT> out)
Generates zero or more resulting elements given a map of detected pattern events.
|
void |
PatternFlatTimeoutFunction.timeout(Map<String,IN> pattern,
long timeoutTimestamp,
Collector<OUT> out)
Generates zero or more resulting timeout elements given a map of partial pattern events and
the timestamp of the timeout.
|
Modifier and Type | Method and Description |
---|---|
<R> DataStream<R> |
PatternStream.flatSelect(scala.Function2<scala.collection.mutable.Map<String,T>,Collector<R>,scala.runtime.BoxedUnit> patternFlatSelectFun,
TypeInformation<R> evidence$10)
Applies a flat select function to the detected pattern sequence.
|
<L,R> DataStream<scala.util.Either<L,R>> |
PatternStream.flatSelect(scala.Function3<scala.collection.mutable.Map<String,T>,Object,Collector<L>,scala.runtime.BoxedUnit> patternFlatTimeoutFunction,
scala.Function2<scala.collection.mutable.Map<String,T>,Collector<R>,scala.runtime.BoxedUnit> patternFlatSelectFunction,
TypeInformation<L> evidence$11,
TypeInformation<R> evidence$12)
Applies a flat select function to the detected pattern sequence.
|
<L,R> DataStream<scala.util.Either<L,R>> |
PatternStream.flatSelect(scala.Function3<scala.collection.mutable.Map<String,T>,Object,Collector<L>,scala.runtime.BoxedUnit> patternFlatTimeoutFunction,
scala.Function2<scala.collection.mutable.Map<String,T>,Collector<R>,scala.runtime.BoxedUnit> patternFlatSelectFunction,
TypeInformation<L> evidence$11,
TypeInformation<R> evidence$12)
Applies a flat select function to the detected pattern sequence.
|
Modifier and Type | Method and Description |
---|---|
void |
ConnectedComponents.UndirectEdge.flatMap(Tuple2<Long,Long> edge,
Collector<Tuple2<Long,Long>> out) |
void |
PageRank.JoinVertexWithEdgesMatch.flatMap(Tuple2<Tuple2<Long,Double>,Tuple2<Long,Long[]>> value,
Collector<Tuple2<Long,Double>> out) |
void |
ConnectedComponents.ComponentIdFilter.join(Tuple2<Long,Long> candidate,
Tuple2<Long,Long> old,
Collector<Tuple2<Long,Long>> out) |
void |
PageRank.BuildOutgoingEdgeList.reduce(Iterable<Tuple2<Long,Long>> values,
Collector<Tuple2<Long,Long[]>> out) |
Modifier and Type | Method and Description |
---|---|
void |
WebLogAnalysis.AntiJoinVisits.coGroup(Iterable<Tuple3<Integer,String,Integer>> ranks,
Iterable<Tuple1<String>> visits,
Collector<Tuple3<Integer,String,Integer>> out)
If the visit iterator is empty, all pairs of the rank iterator are emitted.
|
Modifier and Type | Method and Description |
---|---|
void |
WordCount.Tokenizer.flatMap(String value,
Collector<Tuple2<String,Integer>> out) |
void |
WordCountPojo.Tokenizer.flatMap(String value,
Collector<WordCountPojo.Word> out) |
Modifier and Type | Method and Description |
---|---|
void |
EnumTriangles.TriadBuilder.reduce(Iterable<EnumTriangles.Edge> edges,
Collector<EnumTriangles.Triad> out) |
Modifier and Type | Method and Description |
---|---|
void |
EdgesFunction.iterateEdges(Iterable<Tuple2<K,Edge<K,EV>>> edges,
Collector<O> out)
This method is called per vertex and can iterate over all of its neighboring edges
with the specified direction.
|
void |
EdgesFunctionWithVertexValue.iterateEdges(Vertex<K,VV> vertex,
Iterable<Edge<K,EV>> edges,
Collector<O> out)
This method is called per vertex and can iterate over all of its neighboring edges
with the specified direction.
|
void |
NeighborsFunction.iterateNeighbors(Iterable<Tuple3<K,Edge<K,EV>,Vertex<K,VV>>> neighbors,
Collector<O> out)
This method is called per vertex and can iterate over all of its neighbors
with the specified direction.
|
void |
NeighborsFunctionWithVertexValue.iterateNeighbors(Vertex<K,VV> vertex,
Iterable<Tuple2<Edge<K,EV>,Vertex<K,VV>>> neighbors,
Collector<O> out)
This method is called per vertex and can iterate over all of its neighbors
with the specified direction.
|
Modifier and Type | Method and Description |
---|---|
void |
MusicProfiles.FilterOutMismatches.coGroup(Iterable<Tuple3<String,String,Integer>> triplets,
Iterable<Tuple1<String>> invalidSongs,
Collector<Tuple3<String,String,Integer>> out) |
void |
MusicProfiles.GetTopSongPerUser.iterateEdges(Vertex<String,NullValue> vertex,
Iterable<Edge<String,Integer>> edges,
Collector<Tuple2<String,String>> out) |
void |
MusicProfiles.CreateSimilarUserEdges.reduce(Iterable<Edge<String,Integer>> edges,
Collector<Edge<String,NullValue>> out) |
Modifier and Type | Method and Description |
---|---|
void |
StarGraph.LinkVertexToCenter.flatMap(LongValue leaf,
Collector<Edge<LongValue,NullValue>> out) |
void |
GridGraph.LinkVertexToNeighbors.flatMap(LongValue source,
Collector<Edge<LongValue,NullValue>> out) |
void |
CompleteGraph.LinkVertexToAll.flatMap(LongValue source,
Collector<Edge<LongValue,NullValue>> out) |
Modifier and Type | Method and Description |
---|---|
void |
ApplyFunction.setOutput(Vertex<K,VV> vertex,
Collector<Vertex<K,VV>> out) |
Modifier and Type | Method and Description |
---|---|
void |
VertexCentricIteration.MessageCombinerUdf.combine(Iterable<Tuple2<K,Either<NullValue,Message>>> values,
Collector<Tuple2<K,Either<NullValue,Message>>> out) |
void |
VertexCentricIteration.MessageCombinerUdf.reduce(Iterable<Tuple2<K,Either<NullValue,Message>>> messages,
Collector<Tuple2<K,Either<NullValue,Message>>> out) |
Modifier and Type | Method and Description |
---|---|
abstract void |
EdgesFunction.iterateEdges(scala.collection.Iterable<scala.Tuple2<K,Edge<K,EV>>> edges,
Collector<T> out) |
void |
EdgesFunction.iterateEdges(Iterable<Tuple2<K,Edge<K,EV>>> edges,
Collector<T> out) |
abstract void |
EdgesFunctionWithVertexValue.iterateEdges(Vertex<K,VV> v,
scala.collection.Iterable<Edge<K,EV>> edges,
Collector<T> out) |
void |
EdgesFunctionWithVertexValue.iterateEdges(Vertex<K,VV> v,
Iterable<Edge<K,EV>> edges,
Collector<T> out) |
abstract void |
NeighborsFunction.iterateNeighbors(scala.collection.Iterable<scala.Tuple3<K,Edge<K,EV>,Vertex<K,VV>>> neighbors,
Collector<T> out) |
void |
NeighborsFunction.iterateNeighbors(Iterable<Tuple3<K,Edge<K,EV>,Vertex<K,VV>>> neighbors,
Collector<T> out) |
abstract void |
NeighborsFunctionWithVertexValue.iterateNeighbors(Vertex<K,VV> vertex,
scala.collection.Iterable<scala.Tuple2<Edge<K,EV>,Vertex<K,VV>>> neighbors,
Collector<T> out) |
void |
NeighborsFunctionWithVertexValue.iterateNeighbors(Vertex<K,VV> vertex,
Iterable<Tuple2<Edge<K,EV>,Vertex<K,VV>>> neighbors,
Collector<T> out) |
Modifier and Type | Method and Description |
---|---|
void |
HadoopReduceCombineFunction.combine(Iterable<Tuple2<KEYIN,VALUEIN>> values,
Collector<Tuple2<KEYIN,VALUEIN>> out) |
void |
HadoopMapFunction.flatMap(Tuple2<KEYIN,VALUEIN> value,
Collector<Tuple2<KEYOUT,VALUEOUT>> out) |
void |
HadoopReduceFunction.reduce(Iterable<Tuple2<KEYIN,VALUEIN>> values,
Collector<Tuple2<KEYOUT,VALUEOUT>> out) |
void |
HadoopReduceCombineFunction.reduce(Iterable<Tuple2<KEYIN,VALUEIN>> values,
Collector<Tuple2<KEYOUT,VALUEOUT>> out) |
Modifier and Type | Method and Description |
---|---|
void |
HadoopOutputCollector.setFlinkCollector(Collector<Tuple2<KEY,VALUE>> flinkCollector)
Set the wrapped Flink collector.
|
Modifier and Type | Method and Description |
---|---|
void |
PythonCoGroup.coGroup(Iterable<IN1> first,
Iterable<IN2> second,
Collector<OUT> out)
Calls the external python function.
|
void |
PythonMapPartition.mapPartition(Iterable<IN> values,
Collector<OUT> out) |
Modifier and Type | Method and Description |
---|---|
void |
IdentityGroupReduce.reduce(Iterable<IN> values,
Collector<IN> out) |
Modifier and Type | Method and Description |
---|---|
void |
PythonReceiver.collectBuffer(Collector c,
int bufferSize)
Reads a buffer of the given size from the memory-mapped file, and collects all records contained.
|
void |
PythonStreamer.streamBufferWithGroups(Iterator i1,
Iterator i2,
Collector c)
Sends all values contained in both iterators to the external process and collects all results.
|
void |
PythonStreamer.streamBufferWithoutGroups(Iterator i,
Collector c)
Sends all values contained in the iterator to the external process and collects all results.
|
Modifier and Type | Class and Description |
---|---|
class |
SolutionSetFastUpdateOutputCollector<T>
A
Collector to update the solution set of a workset iteration. |
class |
SolutionSetObjectsUpdateOutputCollector<T>
A
Collector to update the solution set of a workset iteration. |
class |
SolutionSetUpdateOutputCollector<T>
A
Collector to update the solution set of a workset iteration. |
class |
WorksetUpdateOutputCollector<T>
A
Collector to update the iteration workset (partial solution for bulk iterations). |
Constructor and Description |
---|
SolutionSetFastUpdateOutputCollector(CompactingHashTable<T> solutionSet,
Collector<T> delegate) |
SolutionSetObjectsUpdateOutputCollector(JoinHashMap<T> hashMap,
Collector<T> delegate) |
SolutionSetUpdateOutputCollector(CompactingHashTable<T> solutionSet,
Collector<T> delegate) |
WorksetUpdateOutputCollector(DataOutputView outputView,
TypeSerializer<T> serializer,
Collector<T> delegate) |
Modifier and Type | Method and Description |
---|---|
protected Collector<OT> |
AbstractIterativeTask.createSolutionSetUpdateOutputCollector(Collector<OT> delegate)
Creates a new solution set update output collector.
|
protected Collector<OT> |
AbstractIterativeTask.createWorksetUpdateOutputCollector() |
protected Collector<OT> |
AbstractIterativeTask.createWorksetUpdateOutputCollector(Collector<OT> delegate)
Creates a new
WorksetUpdateOutputCollector . |
Modifier and Type | Method and Description |
---|---|
protected Collector<OT> |
AbstractIterativeTask.createSolutionSetUpdateOutputCollector(Collector<OT> delegate)
Creates a new solution set update output collector.
|
protected Collector<OT> |
AbstractIterativeTask.createWorksetUpdateOutputCollector(Collector<OT> delegate)
Creates a new
WorksetUpdateOutputCollector . |
Modifier and Type | Class and Description |
---|---|
class |
NoOpChainedDriver<IT>
A chained driver that just passes on the input as the output
|
Modifier and Type | Field and Description |
---|---|
protected Collector<OT> |
BatchTask.output
The collector that forwards the user code's results.
|
Modifier and Type | Method and Description |
---|---|
protected Collector<OT> |
BatchTask.getLastOutputCollector() |
Collector<OT> |
TaskContext.getOutputCollector() |
Collector<OT> |
BatchTask.getOutputCollector() |
static <T> Collector<T> |
BatchTask.getOutputCollector(AbstractInvokable task,
TaskConfig config,
ClassLoader cl,
List<RecordWriter<?>> eventualOutputs,
int outputOffset,
int numOutputs)
Creates the
Collector for the given task, as described by the given configuration. |
static <T> Collector<T> |
BatchTask.initOutputs(AbstractInvokable containingTask,
ClassLoader cl,
TaskConfig config,
List<ChainedDriver<?,?>> chainedTasksTarget,
List<RecordWriter<?>> eventualOutputs,
ExecutionConfig executionConfig,
Map<String,Accumulator<?,?>> accumulatorMap)
Creates a writer for each output.
|
Modifier and Type | Method and Description |
---|---|
protected void |
BatchTask.setLastOutputCollector(Collector<OT> newOutputCollector)
|
Modifier and Type | Class and Description |
---|---|
class |
ChainedAllReduceDriver<IT> |
class |
ChainedDriver<IT,OT>
The interface to be implemented by drivers that do not run in an own task context, but are chained to other
tasks.
|
class |
ChainedFlatMapDriver<IT,OT> |
class |
ChainedMapDriver<IT,OT> |
class |
ChainedReduceCombineDriver<T>
Chained version of ReduceCombineDriver.
|
class |
ChainedTerminationCriterionDriver<IT,OT> |
class |
GroupCombineChainedDriver<IN,OUT>
Chained variant of the GroupReduceCombineDriver
Acts like a combiner with a custom output type OUT.
|
class |
SynchronousChainedCombineDriver<IN,OUT>
The chained variant of the combine driver which is also implemented in GroupReduceCombineDriver.
|
Modifier and Type | Field and Description |
---|---|
protected Collector<OT> |
ChainedDriver.outputCollector |
Modifier and Type | Method and Description |
---|---|
Collector<OT> |
ChainedDriver.getOutputCollector() |
Modifier and Type | Method and Description |
---|---|
void |
ChainedDriver.setOutputCollector(Collector<?> outputCollector) |
void |
ChainedDriver.setup(TaskConfig config,
String taskName,
Collector<OT> outputCollector,
AbstractInvokable parent,
ClassLoader userCodeClassLoader,
ExecutionConfig executionConfig,
Map<String,Accumulator<?,?>> accumulatorMap) |
Modifier and Type | Method and Description |
---|---|
boolean |
ReusingBuildSecondHashJoinIterator.callWithNextKey(FlatJoinFunction<V1,V2,O> matchFunction,
Collector<O> collector) |
boolean |
ReusingBuildFirstHashJoinIterator.callWithNextKey(FlatJoinFunction<V1,V2,O> matchFunction,
Collector<O> collector) |
boolean |
NonReusingBuildSecondHashJoinIterator.callWithNextKey(FlatJoinFunction<V1,V2,O> matchFunction,
Collector<O> collector) |
boolean |
NonReusingBuildFirstHashJoinIterator.callWithNextKey(FlatJoinFunction<V1,V2,O> matchFunction,
Collector<O> collector) |
Constructor and Description |
---|
ReduceFacade(ReduceFunction<T> reducer,
Collector<T> outputCollector,
boolean objectReuseEnabled) |
Modifier and Type | Class and Description |
---|---|
class |
OutputCollector<T>
The OutputCollector collects records, and emits them to the
RecordWriter s. |
Modifier and Type | Method and Description |
---|---|
boolean |
AbstractMergeOuterJoinIterator.callWithNextKey(FlatJoinFunction<T1,T2,O> joinFunction,
Collector<O> collector)
Calls the
JoinFunction#join() method for all two key-value pairs that share the same key and come
from different inputs. |
abstract boolean |
AbstractMergeIterator.callWithNextKey(FlatJoinFunction<T1,T2,O> joinFunction,
Collector<O> collector)
Calls the
JoinFunction#join() method for all two key-value pairs that share the same key and come
from different inputs. |
boolean |
AbstractMergeInnerJoinIterator.callWithNextKey(FlatJoinFunction<T1,T2,O> joinFunction,
Collector<O> collector)
Calls the
JoinFunction#join() method for all two key-value pairs that share the same key and come
from different inputs. |
protected void |
AbstractMergeIterator.crossMatchingGroup(Iterator<T1> values1,
Iterator<T2> values2,
FlatJoinFunction<T1,T2,O> joinFunction,
Collector<O> collector) |
Modifier and Type | Method and Description |
---|---|
void |
AssignRangeIndex.mapPartition(Iterable<IN> values,
Collector<Tuple2<Integer,IN>> out) |
void |
RangeBoundaryBuilder.mapPartition(Iterable<T> values,
Collector<Object[][]> out) |
Modifier and Type | Method and Description |
---|---|
boolean |
JoinTaskIterator.callWithNextKey(FlatJoinFunction<V1,V2,O> matchFunction,
Collector<O> collector)
Moves the internal pointer to the next key that both inputs share.
|
Modifier and Type | Class and Description |
---|---|
class |
CountingCollector<OUT> |
Constructor and Description |
---|
CountingCollector(Collector<OUT> collector,
Counter numRecordsOut) |
Modifier and Type | Method and Description |
---|---|
void |
SpoutSourceWordCount.Tokenizer.flatMap(String value,
Collector<Tuple2<String,Integer>> out) |
Modifier and Type | Class and Description |
---|---|
class |
CopyingDirectedOutput<OUT>
Special version of
DirectedOutput that performs a shallow copy of the
StreamRecord to ensure that multi-chaining works correctly. |
class |
DirectedOutput<OUT> |
Modifier and Type | Method and Description |
---|---|
void |
ProcessFunction.onTimer(long timestamp,
ProcessFunction.OnTimerContext ctx,
Collector<O> out)
Called when a timer set using
TimerService fires. |
void |
ProcessFunction.processElement(I value,
ProcessFunction.Context ctx,
Collector<O> out)
Process one element from the input stream.
|
Modifier and Type | Method and Description |
---|---|
void |
CoFlatMapFunction.flatMap1(IN1 value,
Collector<OUT> out)
This method is called for each element in the first of the connected streams.
|
void |
CoFlatMapFunction.flatMap2(IN2 value,
Collector<OUT> out)
This method is called for each element in the second of the connected streams.
|
void |
CoProcessFunction.onTimer(long timestamp,
CoProcessFunction.OnTimerContext ctx,
Collector<OUT> out)
Called when a timer set using
TimerService fires. |
void |
CoProcessFunction.processElement1(IN1 value,
CoProcessFunction.Context ctx,
Collector<OUT> out)
This method is called for each element in the first of the connected streams.
|
void |
CoProcessFunction.processElement2(IN2 value,
CoProcessFunction.Context ctx,
Collector<OUT> out)
This method is called for each element in the second of the connected streams.
|
Modifier and Type | Method and Description |
---|---|
void |
FileReadFunction.flatMap(Tuple3<String,Long,Long> value,
Collector<String> out)
Deprecated.
|
Modifier and Type | Method and Description |
---|---|
void |
WindowFunction.apply(KEY key,
W window,
Iterable<IN> input,
Collector<OUT> out)
Evaluates the window and outputs none or several elements.
|
void |
ReduceApplyWindowFunction.apply(K k,
W window,
Iterable<T> input,
Collector<R> out) |
void |
FoldApplyWindowFunction.apply(K key,
W window,
Iterable<T> values,
Collector<R> out) |
void |
ReduceIterableWindowFunction.apply(K k,
W window,
Iterable<T> input,
Collector<T> out) |
void |
PassThroughWindowFunction.apply(K k,
W window,
Iterable<T> input,
Collector<T> out) |
void |
AllWindowFunction.apply(W window,
Iterable<IN> values,
Collector<OUT> out)
Evaluates the window and outputs none or several elements.
|
void |
ReduceApplyAllWindowFunction.apply(W window,
Iterable<T> input,
Collector<R> out) |
void |
FoldApplyAllWindowFunction.apply(W window,
Iterable<T> values,
Collector<R> out) |
void |
ReduceIterableAllWindowFunction.apply(W window,
Iterable<T> input,
Collector<T> out) |
void |
PassThroughAllWindowFunction.apply(W window,
Iterable<T> input,
Collector<T> out) |
Modifier and Type | Interface and Description |
---|---|
interface |
Output<T>
A
StreamOperator is supplied with an object
of this interface that can be used to emit elements and other messages, such as barriers
and watermarks, from an operator. |
Modifier and Type | Class and Description |
---|---|
class |
AbstractStreamOperator.CountingOutput |
class |
TimestampedCollector<T>
|
Modifier and Type | Method and Description |
---|---|
<R> DataStream<R> |
AllWindowedStream.apply(scala.Function2<T,T,T> preAggregator,
scala.Function3<W,scala.collection.Iterable<T>,Collector<R>,scala.runtime.BoxedUnit> windowFunction,
TypeInformation<R> evidence$12)
Deprecated.
Use
reduce(ReduceFunction, AllWindowFunction) instead. |
<R> DataStream<R> |
WindowedStream.apply(scala.Function2<T,T,T> preAggregator,
scala.Function4<K,W,scala.collection.Iterable<T>,Collector<R>,scala.runtime.BoxedUnit> windowFunction,
TypeInformation<R> evidence$12)
Deprecated.
Use
reduce(ReduceFunction, WindowFunction) instead. |
<O> DataStream<O> |
CoGroupedStreams.Where.EqualTo.WithWindow.apply(scala.Function3<scala.collection.Iterator<T1>,scala.collection.Iterator<T2>,Collector<O>,scala.runtime.BoxedUnit> fun,
TypeInformation<O> evidence$3)
Completes the co-group operation with the user function that is executed
for windowed groups.
|
<O> DataStream<O> |
JoinedStreams.Where.EqualTo.WithWindow.apply(scala.Function3<T1,T2,Collector<O>,scala.runtime.BoxedUnit> fun,
TypeInformation<O> evidence$3)
Completes the join operation with the user function that is executed
for windowed groups.
|
<R> DataStream<R> |
AllWindowedStream.apply(scala.Function3<W,scala.collection.Iterable<T>,Collector<R>,scala.runtime.BoxedUnit> function,
TypeInformation<R> evidence$10)
Applies the given window function to each window.
|
<R> DataStream<R> |
WindowedStream.apply(scala.Function4<K,W,scala.collection.Iterable<T>,Collector<R>,scala.runtime.BoxedUnit> function,
TypeInformation<R> evidence$10)
Applies the given window function to each window.
|
<R> DataStream<R> |
AllWindowedStream.apply(R initialValue,
scala.Function2<R,T,R> preAggregator,
scala.Function3<W,scala.collection.Iterable<R>,Collector<R>,scala.runtime.BoxedUnit> windowFunction,
TypeInformation<R> evidence$14)
Deprecated.
Use
fold(R, FoldFunction, AllWindowFunction instead. |
<R> DataStream<R> |
WindowedStream.apply(R initialValue,
scala.Function2<R,T,R> foldFunction,
scala.Function4<K,W,scala.collection.Iterable<R>,Collector<R>,scala.runtime.BoxedUnit> windowFunction,
TypeInformation<R> evidence$14)
Deprecated.
Use
fold(R, FoldFunction, WindowFunction) instead. |
<R> DataStream<R> |
ConnectedStreams.flatMap(scala.Function2<IN1,Collector<R>,scala.runtime.BoxedUnit> fun1,
scala.Function2<IN2,Collector<R>,scala.runtime.BoxedUnit> fun2,
TypeInformation<R> evidence$5)
Applies a CoFlatMap transformation on the connected streams.
|
<R> DataStream<R> |
ConnectedStreams.flatMap(scala.Function2<IN1,Collector<R>,scala.runtime.BoxedUnit> fun1,
scala.Function2<IN2,Collector<R>,scala.runtime.BoxedUnit> fun2,
TypeInformation<R> evidence$5)
Applies a CoFlatMap transformation on the connected streams.
|
<R> DataStream<R> |
DataStream.flatMap(scala.Function2<T,Collector<R>,scala.runtime.BoxedUnit> fun,
TypeInformation<R> evidence$9)
Creates a new DataStream by applying the given function to every element and flattening
the results.
|
<ACC,R> DataStream<R> |
AllWindowedStream.fold(ACC initialValue,
scala.Function2<ACC,T,ACC> preAggregator,
scala.Function3<W,scala.collection.Iterable<ACC>,Collector<R>,scala.runtime.BoxedUnit> windowFunction,
TypeInformation<ACC> evidence$7,
TypeInformation<R> evidence$8)
Applies the given window function to each window.
|
<ACC,R> DataStream<R> |
WindowedStream.fold(ACC initialValue,
scala.Function2<ACC,T,ACC> foldFunction,
scala.Function4<K,W,scala.collection.Iterable<ACC>,Collector<R>,scala.runtime.BoxedUnit> windowFunction,
TypeInformation<ACC> evidence$7,
TypeInformation<R> evidence$8)
Applies the given window function to each window.
|
<R> DataStream<R> |
AllWindowedStream.reduce(scala.Function2<T,T,T> preAggregator,
scala.Function3<W,scala.collection.Iterable<T>,Collector<R>,scala.runtime.BoxedUnit> windowFunction,
TypeInformation<R> evidence$2)
Applies the given window function to each window.
|
<R> DataStream<R> |
WindowedStream.reduce(scala.Function2<T,T,T> preAggregator,
scala.Function4<K,W,scala.collection.Iterable<T>,Collector<R>,scala.runtime.BoxedUnit> windowFunction,
TypeInformation<R> evidence$2)
Applies the given window function to each window.
|
Modifier and Type | Method and Description |
---|---|
void |
WindowFunction.apply(KEY key,
W window,
scala.collection.Iterable<IN> input,
Collector<OUT> out)
Evaluates the window and outputs none or several elements.
|
void |
AllWindowFunction.apply(W window,
scala.collection.Iterable<IN> input,
Collector<OUT> out)
Evaluates the window and outputs none or several elements.
|
Modifier and Type | Method and Description |
---|---|
void |
ScalaWindowFunctionWrapper.apply(KEY key,
W window,
Iterable<IN> input,
Collector<OUT> out) |
void |
ScalaWindowFunction.apply(KEY key,
W window,
Iterable<IN> input,
Collector<OUT> out) |
void |
ScalaAllWindowFunctionWrapper.apply(W window,
Iterable<IN> input,
Collector<OUT> out) |
void |
ScalaAllWindowFunction.apply(W window,
Iterable<IN> input,
Collector<OUT> out) |
Constructor and Description |
---|
ScalaAllWindowFunction(scala.Function3<W,scala.collection.Iterable<IN>,Collector<OUT>,scala.runtime.BoxedUnit> function) |
ScalaWindowFunction(scala.Function4<KEY,W,scala.collection.Iterable<IN>,Collector<OUT>,scala.runtime.BoxedUnit> function) |
Modifier and Type | Method and Description |
---|---|
void |
IncrementalLearningSkeleton.PartialModelBuilder.apply(TimeWindow window,
Iterable<Integer> values,
Collector<Double[]> out) |
Modifier and Type | Method and Description |
---|---|
void |
TwitterExample.SelectEnglishAndTokenizeFlatMap.flatMap(String value,
Collector<Tuple2<String,Integer>> out)
Select the language from the incoming JSON text
|
Modifier and Type | Method and Description |
---|---|
void |
GroupedProcessingTimeWindowExample.SummingWindowFunction.apply(Long key,
Window window,
Iterable<Tuple2<Long,Long>> values,
Collector<Tuple2<Long,Long>> out) |
Modifier and Type | Method and Description |
---|---|
void |
PojoExample.Tokenizer.flatMap(String value,
Collector<PojoExample.Word> out) |
void |
WordCount.Tokenizer.flatMap(String value,
Collector<Tuple2<String,Integer>> out) |
Modifier and Type | Class and Description |
---|---|
class |
RecordWriterOutput<OUT>
Implementation of
Output that sends data using a RecordWriter . |
Modifier and Type | Method and Description |
---|---|
void |
AccumulatingKeyedTimePanes.evaluateWindow(Collector<Result> out,
TimeWindow window,
AbstractStreamOperator<Result> operator) |
abstract void |
AbstractKeyedTimePanes.evaluateWindow(Collector<Result> out,
TimeWindow window,
AbstractStreamOperator<Result> operator) |
void |
AggregatingKeyedTimePanes.evaluateWindow(Collector<Type> out,
TimeWindow window,
AbstractStreamOperator<Type> operator) |
Modifier and Type | Method and Description |
---|---|
void |
InternalSingleValueAllWindowFunction.apply(Byte key,
W window,
IN input,
Collector<OUT> out) |
void |
InternalIterableAllWindowFunction.apply(Byte key,
W window,
Iterable<IN> input,
Collector<OUT> out) |
void |
InternalWindowFunction.apply(KEY key,
W window,
IN input,
Collector<OUT> out)
Evaluates the window and outputs none or several elements.
|
void |
InternalSingleValueWindowFunction.apply(KEY key,
W window,
IN input,
Collector<OUT> out) |
void |
InternalIterableWindowFunction.apply(KEY key,
W window,
Iterable<IN> input,
Collector<OUT> out) |
Modifier and Type | Method and Description |
---|---|
void |
TableFunction.setCollector(Collector<T> collector)
Internal use.
|
Modifier and Type | Class and Description |
---|---|
class |
TableFunctionCollector<T>
The basic implementation of collector for
TableFunction . |
Modifier and Type | Method and Description |
---|---|
Collector<?> |
TableFunctionCollector.getCollector()
Gets the internal collector which used to emit the final row.
|
Modifier and Type | Method and Description |
---|---|
void |
MinusCoGroupFunction.coGroup(Iterable<T> first,
Iterable<T> second,
Collector<T> out) |
void |
IntersectCoGroupFunction.coGroup(Iterable<T> first,
Iterable<T> second,
Collector<T> out) |
void |
MapJoinLeftRunner.flatMap(IN1 multiInput,
Collector<OUT> out) |
void |
MapJoinRightRunner.flatMap(IN2 multiInput,
Collector<OUT> out) |
void |
CorrelateFlatMapRunner.flatMap(IN in,
Collector<OUT> out) |
void |
FlatMapRunner.flatMap(IN in,
Collector<OUT> out) |
void |
FlatJoinRunner.join(IN1 first,
IN2 second,
Collector<OUT> out) |
void |
CountPartitionFunction.mapPartition(Iterable<IN> value,
Collector<scala.Tuple2<Object,Object>> out) |
void |
TableFunctionCollector.setCollector(Collector<?> collector)
Sets the current collector, which used to emit the final row.
|
Modifier and Type | Class and Description |
---|---|
class |
TimeWindowPropertyCollector
Adds TimeWindow properties to specified fields of a row before it emits the row to a wrapped
collector.
|
Modifier and Type | Method and Description |
---|---|
Collector<Row> |
TimeWindowPropertyCollector.wrappedCollector() |
Modifier and Type | Method and Description |
---|---|
void |
AggregateAllTimeWindowFunction.apply(TimeWindow window,
Iterable<Row> input,
Collector<Row> out) |
void |
IncrementalAggregateAllTimeWindowFunction.apply(TimeWindow window,
Iterable<Row> records,
Collector<Row> out) |
void |
IncrementalAggregateTimeWindowFunction.apply(Tuple key,
TimeWindow window,
Iterable<Row> records,
Collector<Row> out) |
void |
AggregateTimeWindowFunction.apply(Tuple key,
TimeWindow window,
Iterable<Row> input,
Collector<Row> out) |
void |
IncrementalAggregateWindowFunction.apply(Tuple key,
W window,
Iterable<Row> records,
Collector<Row> out)
Calculate aggregated values output by aggregate buffer, and set them into output
Row based on the mapping relation between intermediate aggregate data and output data.
|
void |
AggregateWindowFunction.apply(Tuple key,
W window,
Iterable<Row> input,
Collector<Row> out) |
void |
IncrementalAggregateAllWindowFunction.apply(W window,
Iterable<Row> records,
Collector<Row> out)
Calculate aggregated values output by aggregate buffer, and set them into output
Row based on the mapping relation between intermediate aggregate data and output data.
|
void |
AggregateAllWindowFunction.apply(W window,
Iterable<Row> input,
Collector<Row> out) |
void |
AggregateReduceGroupFunction.reduce(Iterable<Row> records,
Collector<Row> out)
For grouped intermediate aggregate Rows, merge all of them into aggregate buffer,
calculate aggregated values output by aggregate buffer, and set them into output
Row based on the mapping relation between intermediate aggregate data and output data.
|
Copyright © 2014–2017 The Apache Software Foundation. All rights reserved.