@Internal public class CollectStreamSink<T> extends DataStreamSink<T>
DataStreamSink
which is used to collect results of a data stream. It completely
overwrites DataStreamSink
so that its own transformation is manipulated.Constructor and Description |
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CollectStreamSink(DataStream<T> inputStream,
CollectSinkOperatorFactory<T> factory) |
Modifier and Type | Method and Description |
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DataStreamSink<T> |
disableChaining()
Turns off chaining for this operator so thread co-location will not be used as an
optimization.
|
LegacySinkTransformation<T> |
getTransformation()
Returns the transformation that contains the actual sink operator of this sink.
|
DataStreamSink<T> |
name(String name)
Sets the name of this sink.
|
DataStreamSink<T> |
setParallelism(int parallelism)
Sets the parallelism for this sink.
|
DataStreamSink<T> |
setUidHash(String uidHash)
Sets an user provided hash for this operator.
|
DataStreamSink<T> |
slotSharingGroup(String slotSharingGroup)
Sets the slot sharing group of this operation.
|
DataStreamSink<T> |
uid(String uid)
Sets an ID for this operator.
|
public CollectStreamSink(DataStream<T> inputStream, CollectSinkOperatorFactory<T> factory)
public LegacySinkTransformation<T> getTransformation()
DataStreamSink
getTransformation
in class DataStreamSink<T>
public DataStreamSink<T> name(String name)
DataStreamSink
name
in class DataStreamSink<T>
public DataStreamSink<T> uid(String uid)
DataStreamSink
The specified ID is used to assign the same operator ID across job submissions (for example when starting a job from a savepoint).
Important: this ID needs to be unique per transformation and job. Otherwise, job submission will fail.
uid
in class DataStreamSink<T>
uid
- The unique user-specified ID of this transformation.public DataStreamSink<T> setUidHash(String uidHash)
DataStreamSink
The user provided hash is an alternative to the generated hashes, that is considered when identifying an operator through the default hash mechanics fails (e.g. because of changes between Flink versions).
Important: this should be used as a workaround or for trouble shooting. The provided hash needs to be unique per transformation and job. Otherwise, job submission will fail. Furthermore, you cannot assign user-specified hash to intermediate nodes in an operator chain and trying so will let your job fail.
A use case for this is in migration between Flink versions or changing the jobs in a way that changes the automatically generated hashes. In this case, providing the previous hashes directly through this method (e.g. obtained from old logs) can help to reestablish a lost mapping from states to their target operator.
setUidHash
in class DataStreamSink<T>
uidHash
- The user provided hash for this operator. This will become the JobVertexID,
which is shown in the logs and web ui.public DataStreamSink<T> setParallelism(int parallelism)
DataStreamSink
setParallelism
in class DataStreamSink<T>
parallelism
- The parallelism for this sink.public DataStreamSink<T> disableChaining()
DataStreamSink
Chaining can be turned off for the whole job by StreamExecutionEnvironment.disableOperatorChaining()
however it is not advised for performance considerations.
disableChaining
in class DataStreamSink<T>
public DataStreamSink<T> slotSharingGroup(String slotSharingGroup)
DataStreamSink
Operations inherit the slot sharing group of input operations if all input operations are in the same slot sharing group and no slot sharing group was explicitly specified.
Initially an operation is in the default slot sharing group. An operation can be put into
the default group explicitly by setting the slot sharing group to "default"
.
slotSharingGroup
in class DataStreamSink<T>
slotSharingGroup
- The slot sharing group name.Copyright © 2014–2021 The Apache Software Foundation. All rights reserved.