public class ExecutionJobVertex extends Object implements AccessExecutionJobVertex, org.apache.flink.api.common.Archiveable<ArchivedExecutionJobVertex>
ExecutionJobVertex is part of the ExecutionGraph, and the peer to the JobVertex.
The ExecutionJobVertex corresponds to a parallelized operation. It contains an ExecutionVertex for each parallel instance of that operation.
| Constructor and Description |
|---|
ExecutionJobVertex(InternalExecutionGraphAccessor graph,
JobVertex jobVertex,
int maxPriorAttemptsHistoryLength,
org.apache.flink.api.common.time.Time timeout,
long createTimestamp,
VertexParallelismInformation parallelismInfo,
SubtaskAttemptNumberStore initialAttemptCounts) |
| Modifier and Type | Method and Description |
|---|---|
ArchivedExecutionJobVertex |
archive() |
void |
cancel()
Cancels all currently running vertex executions.
|
CompletableFuture<Void> |
cancelWithFuture()
Cancels all currently running vertex executions.
|
boolean |
canRescaleMaxParallelism(int desiredMaxParallelism) |
void |
connectToPredecessors(Map<IntermediateDataSetID,IntermediateResult> intermediateDataSets) |
void |
fail(Throwable t) |
StringifiedAccumulatorResult[] |
getAggregatedUserAccumulatorsStringified()
Returns the aggregated user-defined accumulators as strings.
|
static ExecutionState |
getAggregateJobVertexState(int[] verticesPerState,
int parallelism)
A utility function that computes an "aggregated" state for the vertex.
|
ExecutionState |
getAggregateState()
Returns the aggregated
ExecutionState for this job vertex. |
CoLocationGroup |
getCoLocationGroup() |
InternalExecutionGraphAccessor |
getGraph() |
List<IntermediateResult> |
getInputs() |
org.apache.flink.api.common.JobID |
getJobId() |
JobVertex |
getJobVertex() |
JobVertexID |
getJobVertexId()
Returns the
JobVertexID for this job vertex. |
int |
getMaxParallelism()
Returns the max parallelism for this job vertex.
|
String |
getName()
Returns the name for this job vertex.
|
Collection<OperatorCoordinatorHolder> |
getOperatorCoordinators() |
List<OperatorIDPair> |
getOperatorIDs()
Returns a list containing the ID pairs of all operators contained in this execution job
vertex.
|
int |
getParallelism()
Returns the parallelism for this job vertex.
|
IntermediateResult[] |
getProducedDataSets() |
ResourceProfile |
getResourceProfile()
Returns the resource profile for this job vertex.
|
SlotSharingGroup |
getSlotSharingGroup() |
org.apache.flink.core.io.InputSplitAssigner |
getSplitAssigner() |
org.apache.flink.types.Either<org.apache.flink.util.SerializedValue<TaskInformation>,PermanentBlobKey> |
getTaskInformationOrBlobKey() |
ExecutionVertex[] |
getTaskVertices()
Returns all execution vertices for this job vertex.
|
void |
setMaxParallelism(int maxParallelism) |
CompletableFuture<Void> |
suspend() |
@VisibleForTesting public ExecutionJobVertex(InternalExecutionGraphAccessor graph, JobVertex jobVertex, int maxPriorAttemptsHistoryLength, org.apache.flink.api.common.time.Time timeout, long createTimestamp, VertexParallelismInformation parallelismInfo, SubtaskAttemptNumberStore initialAttemptCounts) throws JobException
JobExceptionpublic List<OperatorIDPair> getOperatorIDs()
public void setMaxParallelism(int maxParallelism)
public InternalExecutionGraphAccessor getGraph()
public JobVertex getJobVertex()
public String getName()
AccessExecutionJobVertexgetName in interface AccessExecutionJobVertexpublic int getParallelism()
AccessExecutionJobVertexgetParallelism in interface AccessExecutionJobVertexpublic int getMaxParallelism()
AccessExecutionJobVertexgetMaxParallelism in interface AccessExecutionJobVertexpublic ResourceProfile getResourceProfile()
AccessExecutionJobVertexgetResourceProfile in interface AccessExecutionJobVertexpublic boolean canRescaleMaxParallelism(int desiredMaxParallelism)
public org.apache.flink.api.common.JobID getJobId()
public JobVertexID getJobVertexId()
AccessExecutionJobVertexJobVertexID for this job vertex.getJobVertexId in interface AccessExecutionJobVertexpublic ExecutionVertex[] getTaskVertices()
AccessExecutionJobVertexgetTaskVertices in interface AccessExecutionJobVertexpublic IntermediateResult[] getProducedDataSets()
public org.apache.flink.core.io.InputSplitAssigner getSplitAssigner()
public SlotSharingGroup getSlotSharingGroup()
@Nullable public CoLocationGroup getCoLocationGroup()
public List<IntermediateResult> getInputs()
public Collection<OperatorCoordinatorHolder> getOperatorCoordinators()
public org.apache.flink.types.Either<org.apache.flink.util.SerializedValue<TaskInformation>,PermanentBlobKey> getTaskInformationOrBlobKey() throws IOException
IOExceptionpublic ExecutionState getAggregateState()
AccessExecutionJobVertexExecutionState for this job vertex.getAggregateState in interface AccessExecutionJobVertexpublic void connectToPredecessors(Map<IntermediateDataSetID,IntermediateResult> intermediateDataSets) throws JobException
JobExceptionpublic void cancel()
public CompletableFuture<Void> cancelWithFuture()
public CompletableFuture<Void> suspend()
public void fail(Throwable t)
public StringifiedAccumulatorResult[] getAggregatedUserAccumulatorsStringified()
AccessExecutionJobVertexgetAggregatedUserAccumulatorsStringified in interface AccessExecutionJobVertexpublic ArchivedExecutionJobVertex archive()
archive in interface org.apache.flink.api.common.Archiveable<ArchivedExecutionJobVertex>public static ExecutionState getAggregateJobVertexState(int[] verticesPerState, int parallelism)
This state is not used anywhere in the coordination, but can be used for display in dashboards to as a summary for how the particular parallel operation represented by this ExecutionJobVertex is currently behaving.
For example, if at least one parallel task is failed, the aggregate state is failed. If not, and at least one parallel task is cancelling (or cancelled), the aggregate state is cancelling (or cancelled). If all tasks are finished, the aggregate state is finished, and so on.
verticesPerState - The number of vertices in each state (indexed by the ordinal of the
ExecutionState values).parallelism - The parallelism of the ExecutionJobVertexCopyright © 2014–2022 The Apache Software Foundation. All rights reserved.