blob: e3b9523dd6e92a9d8c292231cf6ac184361b9fe0 [file] [log] [blame]
package org.apache.helix.controller.rebalancer.waged.constraints;
/*
* 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
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*/
import org.apache.helix.controller.rebalancer.waged.RebalanceAlgorithm;
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.apache.helix.model.Partition;
import org.apache.helix.model.ResourceAssignment;
import org.mockito.Mockito;
import java.util.Collections;
import java.util.HashMap;
import java.util.Iterator;
import java.util.Map;
import static org.mockito.Mockito.when;
/**
* A mock up rebalance algorithm for unit test.
* Note that the mock algorithm won't propagate the existing assignment to the output as a real
* algorithm will do. This is for the convenience of testing.
*/
public class MockRebalanceAlgorithm implements RebalanceAlgorithm {
Map<String, ResourceAssignment> _resultHistory = Collections.emptyMap();
@Override
public OptimalAssignment calculate(ClusterModel clusterModel) {
// If no predefined rebalance result setup, do card dealing.
Map<String, ResourceAssignment> result = new HashMap<>();
Iterator<AssignableNode> nodeIterator =
clusterModel.getAssignableNodes().values().stream().sorted().iterator();
for (String resource : clusterModel.getAssignableReplicaMap().keySet()) {
Iterator<AssignableReplica> replicaIterator =
clusterModel.getAssignableReplicaMap().get(resource).stream().sorted().iterator();
while (replicaIterator.hasNext()) {
AssignableReplica replica = replicaIterator.next();
if (!nodeIterator.hasNext()) {
nodeIterator = clusterModel.getAssignableNodes().values().stream().sorted().iterator();
}
AssignableNode node = nodeIterator.next();
// Put the assignment
ResourceAssignment assignment = result.computeIfAbsent(replica.getResourceName(),
resourceName -> new ResourceAssignment(resourceName));
Partition partition = new Partition(replica.getPartitionName());
if (assignment.getReplicaMap(partition).isEmpty()) {
assignment.addReplicaMap(partition, new HashMap<>());
}
assignment.getReplicaMap(partition).put(node.getInstanceName(), replica.getReplicaState());
}
}
_resultHistory = result;
// Mock the return value for supporting test.
OptimalAssignment optimalAssignment = Mockito.mock(OptimalAssignment.class);
when(optimalAssignment.getOptimalResourceAssignment()).thenReturn(result);
return optimalAssignment;
}
public Map<String, ResourceAssignment> getRebalanceResult() {
return new HashMap<>(_resultHistory);
}
}