void markFinished(
Map<AccumulatorRegistry.Metric, Accumulator<?, ?>> flinkAccumulators,
Map<String, Accumulator<?, ?>> userAccumulators) {
// this call usually comes during RUNNING, but may also come while still in deploying (very fast
// tasks!)
while (true) {
ExecutionState current = this.state;
if (current == RUNNING || current == DEPLOYING) {
if (transitionState(current, FINISHED)) {
try {
for (IntermediateResultPartition finishedPartition :
getVertex().finishAllBlockingPartitions()) {
IntermediateResultPartition[] allPartitions =
finishedPartition.getIntermediateResult().getPartitions();
for (IntermediateResultPartition partition : allPartitions) {
scheduleOrUpdateConsumers(partition.getConsumers());
}
}
synchronized (accumulatorLock) {
this.flinkAccumulators = flinkAccumulators;
this.userAccumulators = userAccumulators;
}
assignedResource.releaseSlot();
vertex.getExecutionGraph().deregisterExecution(this);
} finally {
vertex.executionFinished();
}
return;
}
} else if (current == CANCELING) {
// we sent a cancel call, and the task manager finished before it arrived. We
// will never get a CANCELED call back from the job manager
cancelingComplete();
return;
} else if (current == CANCELED || current == FAILED) {
if (LOG.isDebugEnabled()) {
LOG.debug("Task FINISHED, but concurrently went to state " + state);
}
return;
} else {
// this should not happen, we need to fail this
markFailed(new Exception("Vertex received FINISHED message while being in state " + state));
return;
}
}
}
void scheduleOrUpdateConsumers(List<List<ExecutionEdge>> allConsumers) {
final int numConsumers = allConsumers.size();
if (numConsumers > 1) {
fail(
new IllegalStateException(
"Currently, only a single consumer group per partition is supported."));
} else if (numConsumers == 0) {
return;
}
for (ExecutionEdge edge : allConsumers.get(0)) {
final ExecutionVertex consumerVertex = edge.getTarget();
final Execution consumer = consumerVertex.getCurrentExecutionAttempt();
final ExecutionState consumerState = consumer.getState();
final IntermediateResultPartition partition = edge.getSource();
// ----------------------------------------------------------------
// Consumer is created => try to deploy and cache input channel
// descriptors if there is a deployment race
// ----------------------------------------------------------------
if (consumerState == CREATED) {
final Execution partitionExecution = partition.getProducer().getCurrentExecutionAttempt();
consumerVertex.cachePartitionInfo(
PartialInputChannelDeploymentDescriptor.fromEdge(partition, partitionExecution));
// When deploying a consuming task, its task deployment descriptor will contain all
// deployment information available at the respective time. It is possible that some
// of the partitions to be consumed have not been created yet. These are updated
// runtime via the update messages.
//
// TODO The current approach may send many update messages even though the consuming
// task has already been deployed with all necessary information. We have to check
// whether this is a problem and fix it, if it is.
future(
new Callable<Boolean>() {
@Override
public Boolean call() throws Exception {
try {
consumerVertex.scheduleForExecution(
consumerVertex.getExecutionGraph().getScheduler(),
consumerVertex.getExecutionGraph().isQueuedSchedulingAllowed());
} catch (Throwable t) {
fail(
new IllegalStateException(
"Could not schedule consumer " + "vertex " + consumerVertex, t));
}
return true;
}
},
executionContext);
// double check to resolve race conditions
if (consumerVertex.getExecutionState() == RUNNING) {
consumerVertex.sendPartitionInfos();
}
}
// ----------------------------------------------------------------
// Consumer is running => send update message now
// ----------------------------------------------------------------
else {
if (consumerState == RUNNING) {
final SimpleSlot consumerSlot = consumer.getAssignedResource();
if (consumerSlot == null) {
// The consumer has been reset concurrently
continue;
}
final Instance consumerInstance = consumerSlot.getInstance();
final ResultPartitionID partitionId =
new ResultPartitionID(partition.getPartitionId(), attemptId);
final Instance partitionInstance =
partition.getProducer().getCurrentAssignedResource().getInstance();
final ResultPartitionLocation partitionLocation;
if (consumerInstance.equals(partitionInstance)) {
// Consuming task is deployed to the same instance as the partition => local
partitionLocation = ResultPartitionLocation.createLocal();
} else {
// Different instances => remote
final ConnectionID connectionId =
new ConnectionID(
partitionInstance.getInstanceConnectionInfo(),
partition.getIntermediateResult().getConnectionIndex());
partitionLocation = ResultPartitionLocation.createRemote(connectionId);
}
final InputChannelDeploymentDescriptor descriptor =
new InputChannelDeploymentDescriptor(partitionId, partitionLocation);
final UpdatePartitionInfo updateTaskMessage =
new UpdateTaskSinglePartitionInfo(
consumer.getAttemptId(), partition.getIntermediateResult().getId(), descriptor);
sendUpdatePartitionInfoRpcCall(consumerSlot, updateTaskMessage);
}
// ----------------------------------------------------------------
// Consumer is scheduled or deploying => cache input channel
// deployment descriptors and send update message later
// ----------------------------------------------------------------
else if (consumerState == SCHEDULED || consumerState == DEPLOYING) {
final Execution partitionExecution = partition.getProducer().getCurrentExecutionAttempt();
consumerVertex.cachePartitionInfo(
PartialInputChannelDeploymentDescriptor.fromEdge(partition, partitionExecution));
// double check to resolve race conditions
if (consumerVertex.getExecutionState() == RUNNING) {
consumerVertex.sendPartitionInfos();
}
}
}
}
}