Github user tillrohrmann commented on a diff in the pull request:
https://github.com/apache/flink/pull/640#discussion_r29433574
--- 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 --
How do you know that the reply takes only a few milliseconds? You are
sending a message from the JM to the TM. Depending on how long it takes for the
message to be sent over the network, processing time at the TM and processing
time at the JM this can definitely take longer than a few milliseconds.
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