narendly commented on a change in pull request #381: Implement the POC work greedy constraint based algorithm URL: https://github.com/apache/helix/pull/381#discussion_r317843157
########## File path: helix-core/src/main/java/org/apache/helix/controller/rebalancer/waged/algorithm/ConstraintBasedAlgorithm.java ########## @@ -0,0 +1,117 @@ +package org.apache.helix.controller.rebalancer.waged.algorithm; + +/* + * 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. + */ + +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; + +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.ClusterModel; +import org.apache.helix.controller.rebalancer.waged.model.OptimalAssignment; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +/** + * 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; + + public ConstraintBasedAlgorithm(List<HardConstraint> hardConstraints, + List<SoftConstraint> softConstraints) { + _hardConstraints = hardConstraints; + _softConstraints = softConstraints; + } + + @Override + public OptimalAssignment calculate(ClusterModel clusterModel) { + OptimalAssignment optimalAssignment = new OptimalAssignment(clusterModel); + Map<String, Set<AssignableReplica>> replicasByResource = clusterModel.getAssignableReplicaMap(); + List<AssignableNode> nodes = new ArrayList<>(clusterModel.getAssignableNodes().values()); + + 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()); + }); + } + } + + return optimalAssignment; + } + + 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.getClusterModel().getContext())) { + hardConstraintFailures.computeIfAbsent(candidateNode, node -> new ArrayList<>()) + .add(hardConstraint); + isValid = false; + } + } + return isValid; + }).collect(Collectors.toList()); + if (candidateNodes.isEmpty()) { + optimalAssignment.trackAssignmentFailure(replica, hardConstraintFailures); Review comment: `trackAssignmentFailure` -> `recordHardConstraintFailures`? ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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