public void connectToPredecessors(
Map<IntermediateDataSetID, IntermediateResult> intermediateDataSets) throws JobException {
List<JobEdge> inputs = jobVertex.getInputs();
if (LOG.isDebugEnabled()) {
LOG.debug(
String.format(
"Connecting ExecutionJobVertex %s (%s) to %d predecessors.",
jobVertex.getID(), jobVertex.getName(), inputs.size()));
}
for (int num = 0; num < inputs.size(); num++) {
JobEdge edge = inputs.get(num);
if (LOG.isDebugEnabled()) {
if (edge.getSource() == null) {
LOG.debug(
String.format(
"Connecting input %d of vertex %s (%s) to intermediate result referenced via ID %s.",
num, jobVertex.getID(), jobVertex.getName(), edge.getSourceId()));
} else {
LOG.debug(
String.format(
"Connecting input %d of vertex %s (%s) to intermediate result referenced via predecessor %s (%s).",
num,
jobVertex.getID(),
jobVertex.getName(),
edge.getSource().getProducer().getID(),
edge.getSource().getProducer().getName()));
}
}
// fetch the intermediate result via ID. if it does not exist, then it either has not been
// created, or the order
// in which this method is called for the job vertices is not a topological order
IntermediateResult ires = intermediateDataSets.get(edge.getSourceId());
if (ires == null) {
throw new JobException(
"Cannot connect this job graph to the previous graph. No previous intermediate result found for ID "
+ edge.getSourceId());
}
this.inputs.add(ires);
int consumerIndex = ires.registerConsumer();
for (int i = 0; i < parallelism; i++) {
ExecutionVertex ev = taskVertices[i];
ev.connectSource(num, ires, edge, consumerIndex);
}
}
}
@Test
/**
* Tests that a blocking batch job fails if there are not enough resources left to schedule the
* succeeding tasks. This test case is related to [FLINK-4296] where finished producing tasks
* swallow the fail exception when scheduling a consumer task.
*/
public void testNoResourceAvailableFailure() throws Exception {
final JobID jobId = new JobID();
JobVertex v1 = new JobVertex("source");
JobVertex v2 = new JobVertex("sink");
int dop1 = 1;
int dop2 = 1;
v1.setParallelism(dop1);
v2.setParallelism(dop2);
v1.setInvokableClass(BatchTask.class);
v2.setInvokableClass(BatchTask.class);
v2.connectNewDataSetAsInput(
v1, DistributionPattern.POINTWISE, ResultPartitionType.BLOCKING, false);
// execution graph that executes actions synchronously
ExecutionGraph eg =
new ExecutionGraph(
TestingUtils.directExecutionContext(),
jobId,
"failing test job",
new Configuration(),
new SerializedValue<>(new ExecutionConfig()),
AkkaUtils.getDefaultTimeout(),
new NoRestartStrategy());
eg.setQueuedSchedulingAllowed(false);
List<JobVertex> ordered = Arrays.asList(v1, v2);
eg.attachJobGraph(ordered);
Scheduler scheduler = new Scheduler(TestingUtils.directExecutionContext());
for (int i = 0; i < dop1; i++) {
scheduler.newInstanceAvailable(
ExecutionGraphTestUtils.getInstance(
new ExecutionGraphTestUtils.SimpleActorGateway(
TestingUtils.directExecutionContext())));
}
assertEquals(dop1, scheduler.getNumberOfAvailableSlots());
// schedule, this triggers mock deployment
eg.scheduleForExecution(scheduler);
ExecutionAttemptID attemptID =
eg.getJobVertex(v1.getID())
.getTaskVertices()[0]
.getCurrentExecutionAttempt()
.getAttemptId();
eg.updateState(new TaskExecutionState(jobId, attemptID, ExecutionState.RUNNING));
eg.updateState(
new TaskExecutionState(
jobId,
attemptID,
ExecutionState.FINISHED,
null,
new AccumulatorSnapshot(
jobId,
attemptID,
new HashMap<AccumulatorRegistry.Metric, Accumulator<?, ?>>(),
new HashMap<String, Accumulator<?, ?>>())));
assertEquals(JobStatus.FAILED, eg.getState());
}
public ExecutionJobVertex(
ExecutionGraph graph,
JobVertex jobVertex,
int defaultParallelism,
Time timeout,
long createTimestamp)
throws JobException, IOException {
if (graph == null || jobVertex == null) {
throw new NullPointerException();
}
this.graph = graph;
this.jobVertex = jobVertex;
int vertexParallelism = jobVertex.getParallelism();
int numTaskVertices = vertexParallelism > 0 ? vertexParallelism : defaultParallelism;
this.parallelism = numTaskVertices;
int maxP = jobVertex.getMaxParallelism();
Preconditions.checkArgument(
maxP >= parallelism,
"The maximum parallelism ("
+ maxP
+ ") must be greater or equal than the parallelism ("
+ parallelism
+ ").");
this.maxParallelism = maxP;
this.serializedTaskInformation =
new SerializedValue<>(
new TaskInformation(
jobVertex.getID(),
jobVertex.getName(),
parallelism,
maxParallelism,
jobVertex.getInvokableClassName(),
jobVertex.getConfiguration()));
this.taskVertices = new ExecutionVertex[numTaskVertices];
this.inputs = new ArrayList<IntermediateResult>(jobVertex.getInputs().size());
// take the sharing group
this.slotSharingGroup = jobVertex.getSlotSharingGroup();
this.coLocationGroup = jobVertex.getCoLocationGroup();
// setup the coLocation group
if (coLocationGroup != null && slotSharingGroup == null) {
throw new JobException("Vertex uses a co-location constraint without using slot sharing");
}
// create the intermediate results
this.producedDataSets =
new IntermediateResult[jobVertex.getNumberOfProducedIntermediateDataSets()];
for (int i = 0; i < jobVertex.getProducedDataSets().size(); i++) {
final IntermediateDataSet result = jobVertex.getProducedDataSets().get(i);
this.producedDataSets[i] =
new IntermediateResult(result.getId(), this, numTaskVertices, result.getResultType());
}
Configuration jobConfiguration = graph.getJobConfiguration();
int maxPriorAttemptsHistoryLength =
jobConfiguration != null
? jobConfiguration.getInteger(JobManagerOptions.MAX_ATTEMPTS_HISTORY_SIZE)
: JobManagerOptions.MAX_ATTEMPTS_HISTORY_SIZE.defaultValue();
// create all task vertices
for (int i = 0; i < numTaskVertices; i++) {
ExecutionVertex vertex =
new ExecutionVertex(
this,
i,
this.producedDataSets,
timeout,
createTimestamp,
maxPriorAttemptsHistoryLength);
this.taskVertices[i] = vertex;
}
// sanity check for the double referencing between intermediate result partitions and execution
// vertices
for (IntermediateResult ir : this.producedDataSets) {
if (ir.getNumberOfAssignedPartitions() != parallelism) {
throw new RuntimeException(
"The intermediate result's partitions were not correctly assigned.");
}
}
// set up the input splits, if the vertex has any
try {
@SuppressWarnings("unchecked")
InputSplitSource<InputSplit> splitSource =
(InputSplitSource<InputSplit>) jobVertex.getInputSplitSource();
if (splitSource != null) {
Thread currentThread = Thread.currentThread();
ClassLoader oldContextClassLoader = currentThread.getContextClassLoader();
currentThread.setContextClassLoader(graph.getUserClassLoader());
try {
inputSplits = splitSource.createInputSplits(numTaskVertices);
if (inputSplits != null) {
splitAssigner = splitSource.getInputSplitAssigner(inputSplits);
}
} finally {
currentThread.setContextClassLoader(oldContextClassLoader);
}
} else {
inputSplits = null;
}
} catch (Throwable t) {
throw new JobException("Creating the input splits caused an error: " + t.getMessage(), t);
}
finishedSubtasks = new boolean[parallelism];
}
@Override
public JobVertexID getJobVertexId() {
return jobVertex.getID();
}
/*
* Test setup:
* - v1 is isolated, no slot sharing
* - v2 and v3 (not connected) share slots
* - v4 and v5 (connected) share slots
*/
@Test
public void testAssignSlotSharingGroup() {
try {
JobVertex v1 = new JobVertex("v1");
JobVertex v2 = new JobVertex("v2");
JobVertex v3 = new JobVertex("v3");
JobVertex v4 = new JobVertex("v4");
JobVertex v5 = new JobVertex("v5");
v1.setParallelism(4);
v2.setParallelism(5);
v3.setParallelism(7);
v4.setParallelism(1);
v5.setParallelism(11);
v2.connectNewDataSetAsInput(v1, DistributionPattern.POINTWISE);
v5.connectNewDataSetAsInput(v4, DistributionPattern.POINTWISE);
SlotSharingGroup jg1 = new SlotSharingGroup();
v2.setSlotSharingGroup(jg1);
v3.setSlotSharingGroup(jg1);
SlotSharingGroup jg2 = new SlotSharingGroup();
v4.setSlotSharingGroup(jg2);
v5.setSlotSharingGroup(jg2);
List<JobVertex> vertices = new ArrayList<JobVertex>(Arrays.asList(v1, v2, v3, v4, v5));
ExecutionGraph eg =
new ExecutionGraph(
TestingUtils.defaultExecutionContext(),
new JobID(),
"test job",
new Configuration(),
ExecutionConfigTest.getSerializedConfig(),
AkkaUtils.getDefaultTimeout(),
new NoRestartStrategy());
eg.attachJobGraph(vertices);
// verify that the vertices are all in the same slot sharing group
SlotSharingGroup group1 = null;
SlotSharingGroup group2 = null;
// verify that v1 tasks have no slot sharing group
assertNull(eg.getJobVertex(v1.getID()).getSlotSharingGroup());
// v2 and v3 are shared
group1 = eg.getJobVertex(v2.getID()).getSlotSharingGroup();
assertNotNull(group1);
assertEquals(group1, eg.getJobVertex(v3.getID()).getSlotSharingGroup());
assertEquals(2, group1.getJobVertexIds().size());
assertTrue(group1.getJobVertexIds().contains(v2.getID()));
assertTrue(group1.getJobVertexIds().contains(v3.getID()));
// v4 and v5 are shared
group2 = eg.getJobVertex(v4.getID()).getSlotSharingGroup();
assertNotNull(group2);
assertEquals(group2, eg.getJobVertex(v5.getID()).getSlotSharingGroup());
assertEquals(2, group1.getJobVertexIds().size());
assertTrue(group2.getJobVertexIds().contains(v4.getID()));
assertTrue(group2.getJobVertexIds().contains(v5.getID()));
} catch (Exception e) {
e.printStackTrace();
fail(e.getMessage());
}
}
