Github user mxm commented on a diff in the pull request:
https://github.com/apache/flink/pull/640#discussion_r29432849
--- Diff:
flink-runtime/src/main/java/org/apache/flink/runtime/executiongraph/Backtracking.java
---
@@ -0,0 +1,252 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.flink.runtime.executiongraph;
+
+import akka.actor.ActorRef;
+import akka.dispatch.OnComplete;
+import akka.pattern.Patterns;
+import com.google.common.base.Preconditions;
+import org.apache.flink.runtime.akka.AkkaUtils;
+import org.apache.flink.runtime.execution.ExecutionState;
+import org.apache.flink.runtime.jobgraph.IntermediateResultPartitionID;
+import org.apache.flink.runtime.messages.TaskMessages;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import scala.concurrent.Future;
+
+import java.util.ArrayDeque;
+import java.util.Collection;
+import java.util.Deque;
+import java.util.HashMap;
+import java.util.Map;
+
+
+/**
+ * Backtracking is a mechanism to schedule only those Execution Vertices
of an Execution Graph which
+ * do not have an intermediate result available. This is in contrast to
the simple way of scheduling
+ * a job, where all Execution Vertices are executed starting from the
source. The Backtracking starts
+ * from the sinks and traverses the Execution Graph to the sources. It
only reaches the sources if
+ * no intermediate result could be found on the way.
+ *
+ * @see ExecutionGraph
+ * @see ExecutionVertex
+ * @see Execution
+ */
+public class Backtracking {
+
+ private static final Logger LOG =
LoggerFactory.getLogger(Backtracking.class);
+
+ private final Deque<TaskRequirement> taskRequirements = new
ArrayDeque<TaskRequirement>();
+
+ private final Map<IntermediateResultPartitionID, Boolean>
visitedPartitions = new HashMap<IntermediateResultPartitionID, Boolean>();
+
+ private ScheduleAction scheduleAction;
+ private Runnable postBacktrackingHook;
+
+ public Backtracking(Collection<ExecutionJobVertex> vertices) {
+ Preconditions.checkNotNull(vertices);
+
+ // add all sinks found to the stack
+ for (ExecutionJobVertex ejv : vertices) {
+ if (ejv.getJobVertex().isOutputVertex()) {
+ for (ExecutionVertex ev :
ejv.getTaskVertices()) {
+ if (ev.getExecutionState() ==
ExecutionState.CREATED) {
+ taskRequirements.add(new
TaskRequirement(ev));
+ }
+ }
+ }
+ }
+
+ this.scheduleAction = new ScheduleAction() {
+ @Override
+ public void schedule(ExecutionVertex ev) {}
+ };
+
+ this.postBacktrackingHook = new Runnable() {
+ @Override
+ public void run() {}
+ };
+ }
+
+ /**
+ * Scheduling to be performed when an ExecutionVertex is encountered
that cannot be resumed
+ */
+ public interface ScheduleAction {
+ void schedule(ExecutionVertex ev);
+ }
+
+ /**
+ * A TaskRequirement encaplusates an ExecutionVertex and its
IntermediateResultPartitions which
+ * are required for execution.
+ */
+ private class TaskRequirement {
+
+ private final ExecutionVertex executionVertex;
+ private final Deque<IntermediateResultPartition> pendingInputs
= new ArrayDeque<IntermediateResultPartition>();
+ private final int numInputs;
+
+ private int availableInputs = 0;
+
+ public TaskRequirement(ExecutionVertex executionVertex) {
+ this.executionVertex = executionVertex;
+ this.pendingInputs.addAll(executionVertex.getInputs());
+ this.numInputs = pendingInputs.size();
+ }
+
+ public ExecutionVertex getExecutionVertex() {
+ return executionVertex;
+ }
+
+ public boolean pendingRequirements() {
+ for (IntermediateResultPartition ir : pendingInputs) {
+ Boolean visitedPartition =
visitedPartitions.get(ir.getPartitionId());
+ if (visitedPartition == null) {
+ return true;
+ } else {
+ if (visitedPartition) {
+ availableInputs++;
+ }
+ pendingInputs.remove(ir);
+ }
+ }
+ return false;
+ }
+
+ public IntermediateResultPartition getNextRequirement() {
+ return pendingInputs.pop();
+ }
+
+ public boolean needsToBeScheduled() {
+ return numInputs == availableInputs;
+ }
+
+ public void inputFound() {
+ availableInputs++;
+ }
+
+ @Override
+ public String toString() {
+ return "TaskRequirement{" +
+ "executionVertex=" + executionVertex +
+ ", pendingInputs=" +
pendingInputs.size() +
+ '}';
+ }
+ }
+
+ /**
+ * Action to be performed on an ExecutionVertex when it is determined
to be scheduled.
+ * @param scheduleAction A ScheduleAction which receives an
ExecutionVertex.
+ */
+ public void setScheduleAction(ScheduleAction scheduleAction) {
+ Preconditions.checkNotNull(scheduleAction);
+ this.scheduleAction = scheduleAction;
+ }
+
+ /**
+ * Hook executed after backtracking finishes. Note that because of the
use of futures, this may
+ * not be when the scheduleUsingBacktracking() method returns.
+ * @param postBacktrackingHook A Runnable that is executed after
backtracking finishes.
+ */
+ public void setPostBacktrackingHook(Runnable postBacktrackingHook) {
+ Preconditions.checkNotNull(postBacktrackingHook);
+ this.postBacktrackingHook = postBacktrackingHook;
+ }
+
+ /* Visit the ExecutionGraph from the previously determined sinks using
a pre-order depth-first
+ * iterative traversal.
+ */
+ public void scheduleUsingBacktracking() {
+
+ while (!taskRequirements.isEmpty()) {
+
+ final TaskRequirement taskRequirement =
taskRequirements.peek();
+ final ExecutionVertex task =
taskRequirement.getExecutionVertex();
+ task.getCurrentExecutionAttempt().setScheduled();
+
+ if (task.getExecutionState() != ExecutionState.CREATED
&& task.getExecutionState() != ExecutionState.DEPLOYING) {
+ LOG.debug("Resetting ExecutionVertex {} from {}
to CREATED.", task, task.getExecutionState());
+ task.resetForNewExecution();
+
task.getCurrentExecutionAttempt().setScheduled();
+ }
+
+ if (taskRequirement.pendingRequirements()) {
+
+ final IntermediateResultPartition
resultRequired = taskRequirement.getNextRequirement();
+
+ if (resultRequired.isLocationAvailable()) {
+ ActorRef taskManager =
resultRequired.getLocation().getTaskManager();
+
+ LOG.debug("Requesting availability of
IntermediateResultPartition " + resultRequired.getPartitionId());
+ // pin ResulPartition for this
intermediate result
+ Future<Object> future = Patterns.ask(
+ taskManager,
+ new
TaskMessages.LockResultPartition(
+
resultRequired.getPartitionId(),
+ // We
lock this result for all consumers. We have to make sure
+ // to
release it once a job finishes.
+
resultRequired.getNumConsumers()
+ ),
+ 5000 // 5 seconds
timeout
--- End diff --
`akka.ask.timeout` currently defaults to 100 seconds. I thought that is
rather long but usually the reply should be there within a few milliseconds. So
I guess that is fine for now.
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