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Implement POC work greedy based constraint algorithm
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...java/org/apache/helix/controller/rebalancer/waged/algorithm/ConstraintBasedAlgorithm.java
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| package org.apache.helix.controller.rebalancer.waged.algorithm; | ||
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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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| import java.util.ArrayList; | ||
| import java.util.Comparator; | ||
| import java.util.HashMap; | ||
| import java.util.List; | ||
| import java.util.Map; | ||
| import java.util.Optional; | ||
| import java.util.Set; | ||
| import java.util.function.Function; | ||
| import java.util.stream.Collectors; | ||
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| import org.apache.helix.controller.rebalancer.waged.constraints.HardConstraint; | ||
| import org.apache.helix.controller.rebalancer.waged.constraints.SoftConstraint; | ||
| import org.apache.helix.controller.rebalancer.waged.model.AssignableNode; | ||
| import org.apache.helix.controller.rebalancer.waged.model.AssignableReplica; | ||
| import org.apache.helix.controller.rebalancer.waged.model.ClusterContext; | ||
| import org.apache.helix.controller.rebalancer.waged.model.ClusterModel; | ||
| import org.apache.helix.controller.rebalancer.waged.model.OptimalAssignment; | ||
| import org.slf4j.Logger; | ||
| import org.slf4j.LoggerFactory; | ||
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| /** | ||
| * The algorithm is based on a given set of constraints | ||
| * - HardConstraint: Approve or deny the assignment given its condition, any assignment cannot | ||
| * bypass any "hard constraint" | ||
| * - SoftConstraint: Evaluate the assignment by points/rewards/scores, a higher point means a better | ||
| * assignment | ||
| * <p> | ||
| * The goal is to accumulate the most points(rewards) from "soft constraints" while avoiding all | ||
| * "hard constraints" | ||
| */ | ||
| public class ConstraintBasedAlgorithm implements RebalanceAlgorithm { | ||
| private static final Logger LOG = LoggerFactory.getLogger(ConstraintBasedAlgorithm.class); | ||
| private final List<HardConstraint> _hardConstraints; | ||
| private final List<SoftConstraint> _softConstraints; | ||
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| public ConstraintBasedAlgorithm(List<HardConstraint> hardConstraints, | ||
| List<SoftConstraint> softConstraints) { | ||
| _hardConstraints = hardConstraints; | ||
| _softConstraints = softConstraints; | ||
| } | ||
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| @Override | ||
| public OptimalAssignment calculate(ClusterModel clusterModel) { | ||
| ClusterContext clusterContext = clusterModel.getContext(); | ||
| OptimalAssignment optimalAssignment = new OptimalAssignment(clusterContext); | ||
| Map<String, Set<AssignableReplica>> replicasByResource = clusterModel.getAssignableReplicaMap(); | ||
| List<AssignableNode> nodes = new ArrayList<>(clusterModel.getAssignableNodes().values()); | ||
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| for (String resource : replicasByResource.keySet()) { | ||
| for (AssignableReplica replica : replicasByResource.get(resource)) { | ||
| Optional<AssignableNode> maybeBestNode = | ||
| getNodeWithHighestPoints(replica, nodes, optimalAssignment); | ||
| // stop immediately if any replica cannot find best assignable node | ||
| if (optimalAssignment.hasAnyFailure()) { | ||
| LOG.error( | ||
| "Unable to find any available candidate node for partition {}; Fail reasons: {}", | ||
| replica.getPartitionName(), optimalAssignment.getFailures()); | ||
| return optimalAssignment; | ||
| } | ||
| maybeBestNode.ifPresent(node -> { | ||
| optimalAssignment.addAssignment(replica, node); | ||
| clusterModel.assign(replica.getResourceName(), | ||
| replica.getPartitionName(), replica.getReplicaState(), node.getInstanceName()); | ||
| }); | ||
| } | ||
| } | ||
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| return optimalAssignment; | ||
| } | ||
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| private Optional<AssignableNode> getNodeWithHighestPoints(AssignableReplica replica, | ||
| List<AssignableNode> assignableNodes, OptimalAssignment optimalAssignment) { | ||
| Map<AssignableNode, List<HardConstraint>> hardConstraintFailures = new HashMap<>(); | ||
| List<AssignableNode> candidateNodes = assignableNodes.stream().filter(candidateNode -> { | ||
| boolean isValid = true; | ||
| // evaluate all hard constraints and record all the failure reasons why one assignment fails | ||
| for (HardConstraint hardConstraint : _hardConstraints) { | ||
| if (!hardConstraint.isAssignmentValid(candidateNode, replica, | ||
| optimalAssignment.getClusterContext())) { | ||
| hardConstraintFailures.computeIfAbsent(candidateNode, node -> new ArrayList<>()) | ||
| .add(hardConstraint); | ||
| isValid = false; | ||
| } | ||
| } | ||
| return isValid; | ||
| }).collect(Collectors.toList()); | ||
| if (candidateNodes.isEmpty()) { | ||
| optimalAssignment.trackAssignmentFailure(replica, hardConstraintFailures); | ||
| return Optional.empty(); | ||
| } | ||
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| Function<AssignableNode, Double> calculatePoints = | ||
| (candidateNode) -> _softConstraints.stream().map(softConstraint -> softConstraint | ||
| .assignmentScore(candidateNode, replica, optimalAssignment.getClusterContext())) | ||
| .mapToDouble(score -> score).sum(); | ||
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| return candidateNodes.stream().max(Comparator.comparing(calculatePoints)); | ||
| } | ||
| } |
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49 changes: 0 additions & 49 deletions
49
...g/apache/helix/controller/rebalancer/waged/constraints/ConstraintsRebalanceAlgorithm.java
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