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[FLINK-31261][runtime] Make AdaptiveScheduler aware of local state size
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127 changes: 127 additions & 0 deletions
127
...c/main/java/org/apache/flink/runtime/scheduler/adaptive/allocator/StateSizeEstimates.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. | ||
| */ | ||
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| package org.apache.flink.runtime.scheduler.adaptive.allocator; | ||
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| import org.apache.flink.annotation.Internal; | ||
| import org.apache.flink.api.java.tuple.Tuple2; | ||
| import org.apache.flink.runtime.OperatorIDPair; | ||
| import org.apache.flink.runtime.checkpoint.CompletedCheckpoint; | ||
| import org.apache.flink.runtime.checkpoint.OperatorState; | ||
| import org.apache.flink.runtime.executiongraph.ExecutionGraph; | ||
| import org.apache.flink.runtime.executiongraph.ExecutionJobVertex; | ||
| import org.apache.flink.runtime.jobgraph.JobVertexID; | ||
| import org.apache.flink.runtime.jobgraph.OperatorID; | ||
| import org.apache.flink.runtime.state.KeyedStateHandle; | ||
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| import javax.annotation.Nullable; | ||
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| import java.util.Collections; | ||
| import java.util.Map; | ||
| import java.util.Optional; | ||
| import java.util.Set; | ||
| import java.util.stream.Collectors; | ||
| import java.util.stream.Stream; | ||
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| import static java.util.stream.Collectors.toMap; | ||
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| /** Managed Keyed State size estimates used to make scheduling decisions. */ | ||
| @Internal | ||
| public class StateSizeEstimates { | ||
| private final Map<JobVertexID, Long> averages; | ||
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| public StateSizeEstimates() { | ||
| this(Collections.emptyMap()); | ||
| } | ||
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| public StateSizeEstimates(Map<JobVertexID, Long> averages) { | ||
| this.averages = averages; | ||
| } | ||
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| public Optional<Long> estimate(JobVertexID jobVertexId) { | ||
| return Optional.ofNullable(averages.get(jobVertexId)); | ||
| } | ||
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| static StateSizeEstimates empty() { | ||
| return new StateSizeEstimates(); | ||
| } | ||
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| public static StateSizeEstimates fromGraph(@Nullable ExecutionGraph executionGraph) { | ||
| return Optional.ofNullable(executionGraph) | ||
| .flatMap(graph -> Optional.ofNullable(graph.getCheckpointCoordinator())) | ||
| .flatMap(coordinator -> Optional.ofNullable(coordinator.getCheckpointStore())) | ||
| .flatMap(store -> Optional.ofNullable(store.getLatestCheckpoint())) | ||
| .map( | ||
| cp -> | ||
| build( | ||
| fromCompletedCheckpoint(cp), | ||
| mapVerticesToOperators(executionGraph))) | ||
| .orElse(empty()); | ||
| } | ||
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| private static StateSizeEstimates build( | ||
| Map<OperatorID, Long> sizePerOperator, | ||
| Map<JobVertexID, Set<OperatorID>> verticesToOperators) { | ||
| Map<JobVertexID, Long> verticesToSizes = | ||
| verticesToOperators.entrySet().stream() | ||
| .collect( | ||
| toMap(Map.Entry::getKey, e -> size(e.getValue(), sizePerOperator))); | ||
| return new StateSizeEstimates(verticesToSizes); | ||
| } | ||
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| private static long size(Set<OperatorID> ids, Map<OperatorID, Long> sizes) { | ||
| return ids.stream().mapToLong(key -> sizes.getOrDefault(key, 0L)).sum(); | ||
| } | ||
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| private static Map<JobVertexID, Set<OperatorID>> mapVerticesToOperators( | ||
| ExecutionGraph executionGraph) { | ||
| return executionGraph.getAllVertices().entrySet().stream() | ||
| .collect(toMap(Map.Entry::getKey, e -> getOperatorIDS(e.getValue()))); | ||
| } | ||
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| private static Set<OperatorID> getOperatorIDS(ExecutionJobVertex v) { | ||
| return v.getOperatorIDs().stream() | ||
| .map(OperatorIDPair::getGeneratedOperatorID) | ||
| .collect(Collectors.toSet()); | ||
| } | ||
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| private static Map<OperatorID, Long> fromCompletedCheckpoint(CompletedCheckpoint cp) { | ||
| Stream<Map.Entry<OperatorID, OperatorState>> states = | ||
| cp.getOperatorStates().entrySet().stream(); | ||
| return states.collect( | ||
| toMap( | ||
| Map.Entry::getKey, | ||
| e -> calculateAverageKeyGroupStateSizeInBytes(e.getValue()))); | ||
| } | ||
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| private static long calculateAverageKeyGroupStateSizeInBytes(OperatorState state) { | ||
| Stream<KeyedStateHandle> handles = | ||
| state.getSubtaskStates().values().stream() | ||
| .flatMap(s -> s.getManagedKeyedState().stream()); | ||
| Stream<Tuple2<Long, Integer>> sizeAndCount = | ||
| handles.map( | ||
| h -> | ||
| Tuple2.of( | ||
| h.getStateSize(), | ||
| h.getKeyGroupRange().getNumberOfKeyGroups())); | ||
| Optional<Tuple2<Long, Integer>> totalSizeAndCount = | ||
| sizeAndCount.reduce( | ||
| (left, right) -> Tuple2.of(left.f0 + right.f0, left.f1 + right.f1)); | ||
| Optional<Long> average = totalSizeAndCount.filter(t2 -> t2.f1 > 0).map(t2 -> t2.f0 / t2.f1); | ||
| return average.orElse(0L); | ||
| } | ||
| } |
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