[GitHub] [flink] shuai-xu commented on a change in pull request #8486: [FLINK-12372] [runtime] implement ExecutionSlotAllocator

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shuai-xu commented on a change in pull request #8486: [FLINK-12372] [runtime] implement ExecutionSlotAllocator
URL: https://github.com/apache/flink/pull/8486#discussion_r290631586
 
 

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 File path: flink-runtime/src/main/java/org/apache/flink/runtime/scheduler/DefaultExecutionSlotAllocator.java
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+/*
+ * 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.scheduler;
+
+import org.apache.flink.annotation.VisibleForTesting;
+import org.apache.flink.api.common.time.Time;
+import org.apache.flink.runtime.clusterframework.types.AllocationID;
+import org.apache.flink.runtime.clusterframework.types.SlotProfile;
+import org.apache.flink.runtime.concurrent.FutureUtils;
+import org.apache.flink.runtime.instance.SlotSharingGroupId;
+import org.apache.flink.runtime.jobmanager.scheduler.ScheduledUnit;
+import org.apache.flink.runtime.jobmaster.LogicalSlot;
+import org.apache.flink.runtime.jobmaster.SlotRequestId;
+import org.apache.flink.runtime.jobmaster.slotpool.Scheduler;
+import org.apache.flink.runtime.jobmaster.slotpool.SlotProvider;
+import org.apache.flink.runtime.scheduler.strategy.ExecutionVertexID;
+import org.apache.flink.runtime.taskmanager.TaskManagerLocation;
+
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Collection;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.List;
+import java.util.Map;
+import java.util.Optional;
+import java.util.Set;
+import java.util.concurrent.CompletableFuture;
+
+import static org.apache.flink.runtime.executiongraph.ExecutionVertex.MAX_DISTINCT_LOCATIONS_TO_CONSIDER;
+import static org.apache.flink.util.Preconditions.checkNotNull;
+
+/**
+ * Default {@link ExecutionSlotAllocator} which will use {@link SlotProvider} to allocate slots and
+ * keep the unfulfilled requests for further cancellation.
+ */
+public class DefaultExecutionSlotAllocator implements ExecutionSlotAllocator {
+
+	static final Logger LOG = LoggerFactory.getLogger(DefaultExecutionSlotAllocator.class);
+
+	/**
+	 * Store the uncompleted slot assignments.
+	 */
+	private final Map<ExecutionVertexID, SlotExecutionVertexAssignment> pendingSlotAssignments;
+
+	private final SlotProvider slotProvider;
+
+	private final InputsLocationsRetriever inputsLocationsRetriever;
+
+	private final Time allocationTimeout;
+
+	private final Boolean isQueuedSchedulingAllowed;
+
+	public DefaultExecutionSlotAllocator(
+			SlotProvider slotProvider,
+			InputsLocationsRetriever inputsLocationsRetriever,
+			Time allocationTimeout,
+			boolean isQueuedSchedulingAllowed) {
+		this.slotProvider = checkNotNull(slotProvider);
+		this.inputsLocationsRetriever = checkNotNull(inputsLocationsRetriever);
+		this.allocationTimeout = checkNotNull(allocationTimeout);
+		this.isQueuedSchedulingAllowed = isQueuedSchedulingAllowed;
+
+		pendingSlotAssignments = new HashMap<>();
+	}
+
+	@Override
+	public Collection<SlotExecutionVertexAssignment> allocateSlotsFor(
+			Collection<ExecutionVertexSchedulingRequirements> executionVertexSchedulingRequirements) {
+
+		List<SlotExecutionVertexAssignment> slotExecutionVertexAssignments =
+				new ArrayList<>(executionVertexSchedulingRequirements.size());
+
+		Set<AllocationID> allPreviousAllocationIds =
+				computeAllPriorAllocationIdsIfRequiredByScheduling(executionVertexSchedulingRequirements);
+
+		for (ExecutionVertexSchedulingRequirements schedulingRequirements : executionVertexSchedulingRequirements) {
+			final ExecutionVertexID executionVertexId = schedulingRequirements.getExecutionVertexId();
+			final SlotRequestId slotRequestId = new SlotRequestId();
+			final SlotSharingGroupId slotSharingGroupId = schedulingRequirements.getSlotSharingGroupId();
+
+			if (LOG.isDebugEnabled()) {
+				LOG.debug("Allocate slot with id {} for execution {}", slotRequestId, executionVertexId);
+			}
+
+			// TODO: the calculation of preferred location should be refined.
+			CompletableFuture<LogicalSlot> slotFuture = calculatePreferredLocations(
+					executionVertexId,
+					schedulingRequirements.getPreferredLocations(),
+					inputsLocationsRetriever).thenCompose(
+							(Collection<TaskManagerLocation> preferredLocations) ->
+									slotProvider.allocateSlot(
+											slotRequestId,
+											new ScheduledUnit(
+													null,
+													executionVertexId.getJobVertexId(),
+													slotSharingGroupId,
+													schedulingRequirements.getCoLocationConstraint()),
+											new SlotProfile(
+													schedulingRequirements.getResourceProfile(),
+													preferredLocations,
+													Arrays.asList(schedulingRequirements.getPreviousAllocationId()),
+													allPreviousAllocationIds),
+											isQueuedSchedulingAllowed,
+											allocationTimeout));
+
+			SlotExecutionVertexAssignment slotExecutionVertexAssignment =
+					new SlotExecutionVertexAssignment(executionVertexId, slotFuture);
+			// add to map first to avoid the future completed before added.
+			pendingSlotAssignments.put(executionVertexId, slotExecutionVertexAssignment);
+
+			slotFuture.whenComplete(
+					(ignored, throwable) -> {
+						pendingSlotAssignments.remove(executionVertexId);
+						if (throwable != null) {
+							slotProvider.cancelSlotRequest(slotRequestId, slotSharingGroupId, throwable);
+						}
+					});
+
+			slotExecutionVertexAssignments.add(slotExecutionVertexAssignment);
+		}
+
+		return slotExecutionVertexAssignments;
+	}
+
+	@Override
+	public void cancel(ExecutionVertexID executionVertexId) {
+		SlotExecutionVertexAssignment slotExecutionVertexAssignment = pendingSlotAssignments.get(executionVertexId);
+		if (slotExecutionVertexAssignment != null) {
+			slotExecutionVertexAssignment.getLogicalSlotFuture().cancel(false);
+		}
+	}
+
+	@Override
+	public CompletableFuture<Void> stop() {
+		List<ExecutionVertexID> executionVertexIds = new ArrayList<>(pendingSlotAssignments.keySet());
+		executionVertexIds.stream().forEach(executionVertexID -> cancel(executionVertexID));
+
+		return CompletableFuture.completedFuture(null);
+	}
+
+	/**
+	 * Calculates the preferred locations for an execution.
+	 * It will first try to use preferred locations based on state,
+	 * if null, will use the preferred locations based on inputs.
+	 */
+	private static CompletableFuture<Collection<TaskManagerLocation>> calculatePreferredLocations(
+			ExecutionVertexID executionVertexId,
+			Collection<TaskManagerLocation> preferredLocationsBasedOnState,
+			InputsLocationsRetriever inputsLocationsRetriever) {
+
+		if (preferredLocationsBasedOnState != null && !preferredLocationsBasedOnState.isEmpty()) {
+			return CompletableFuture.completedFuture(preferredLocationsBasedOnState);
+		}
+
+		return getPreferredLocationsBasedOnInputs(executionVertexId, inputsLocationsRetriever);
+	}
+
+	/**
+	 * Gets the location preferences of the execution, as determined by the locations
+	 * of the predecessors from which it receives input data.
+	 * If there are more than {@link MAX_DISTINCT_LOCATIONS_TO_CONSIDER} different locations of source data,
+	 * or neither the sources have not been started nor will be started with the execution together,
+	 * this method returns an empty collection to indicate no location preference.
+	 *
+	 * @return The preferred locations based in input streams, or an empty iterable,
+	 *         if there is no input-based preference.
+	 */
+	@VisibleForTesting
+	static CompletableFuture<Collection<TaskManagerLocation>> getPreferredLocationsBasedOnInputs(
+			ExecutionVertexID executionVertexId,
+			InputsLocationsRetriever inputsLocationsRetriever) {
+		CompletableFuture<Collection<TaskManagerLocation>> preferredLocations = null;
+
+		Collection<CompletableFuture<TaskManagerLocation>> locationsFutures = new ArrayList<>();
+
+		Collection<Collection<ExecutionVertexID>> allProducers =
+				inputsLocationsRetriever.getConsumedResultPartitionsProducers(executionVertexId);
+		for (Collection<ExecutionVertexID> producers : allProducers) {
+			Set<TaskManagerLocation> inputLocations = new HashSet<>();
+			List<CompletableFuture<TaskManagerLocation>> inputLocationsFutures = new ArrayList<>();
+
+			for (ExecutionVertexID producer : producers) {
+				Optional<CompletableFuture<TaskManagerLocation>> optionalLocationFuture =
+						inputsLocationsRetriever.getTaskManagerLocation(producer);
+				optionalLocationFuture.ifPresent(
+						(locationFuture) -> {
+							locationsFutures.add(locationFuture);
+							TaskManagerLocation taskManagerLocation = locationFuture.getNow(null);
+							if (taskManagerLocation != null) {
+								inputLocations.add(taskManagerLocation);
+							} else {
+								inputLocationsFutures.add(locationFuture);
+							}
+						}
+				);
+				// If the parallelism is large, wait for all futures coming back may cost a long time,
+				// so using the unfulfilled future number here to speed up it.
+				if (inputLocations.size() > MAX_DISTINCT_LOCATIONS_TO_CONSIDER ||
+						inputLocationsFutures.size() > MAX_DISTINCT_LOCATIONS_TO_CONSIDER) {
+					locationsFutures.clear();
+					break;
+				}
+			}
+
+			if (!locationsFutures.isEmpty()) {
+				CompletableFuture<Collection<TaskManagerLocation>> uniqueLocationsFuture =
+						FutureUtils.combineAll(locationsFutures).thenApply(
+								(locations) -> {
+									Set<TaskManagerLocation> uniqueLocations = new HashSet<>(locations);
+									if (uniqueLocations.size() <= MAX_DISTINCT_LOCATIONS_TO_CONSIDER) {
+										return uniqueLocations;
+									} else {
+										return Collections.emptySet();
+									}
+								});
+				if (preferredLocations == null) {
+					preferredLocations = uniqueLocationsFuture;
+				} else {
+					preferredLocations = preferredLocations.thenCombine(
+							uniqueLocationsFuture,
+							(locationsOnOneEdge, locationsOnAnotherEdge) -> {
+								if ((!locationsOnOneEdge.isEmpty() && locationsOnAnotherEdge.size() > locationsOnOneEdge.size())
+										|| locationsOnAnotherEdge.isEmpty()) {
+									return locationsOnOneEdge;
+								} else {
+									return locationsOnAnotherEdge;
+								}
+							});
+				}
+				locationsFutures.clear();
+			}
+		}
+		return preferredLocations == null ? CompletableFuture.completedFuture(Collections.emptyList()) : preferredLocations;
+	}
+
+	/**
+	 * Returns the result of {@link #computeAllPriorAllocationIds}, but only if the scheduling really requires it.
+	 * Otherwise this method simply returns an empty set.
+	 */
+	private Set<AllocationID> computeAllPriorAllocationIdsIfRequiredByScheduling(
+			Collection<ExecutionVertexSchedulingRequirements> executionVertexSchedulingRequirements) {
+		// This is a temporary optimization to avoid computing all previous allocations if not required
+		// This can go away when we progress with the implementation of the Scheduler.
+		if (slotProvider instanceof Scheduler && ((Scheduler) slotProvider).requiresPreviousExecutionGraphAllocations()) {
 
 Review comment:
   it is just an optimization, we can remove it.

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