HBASE-26337 Optimization for weighted random generators (#3732)
Signed-off-by: Duo Zhang <zhangduo@apache.org>
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@ -79,4 +79,4 @@ abstract class CostFromRegionLoadFunction extends CostFunction {
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}
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protected abstract double getCostFromRl(BalancerRegionLoad rl);
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}
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}
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@ -83,6 +83,16 @@ abstract class CostFunction {
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protected abstract double cost();
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/**
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* Add the cost of this cost function to the weight of the candidate generator that is optimized
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* for this cost function. By default it is the RandomCandiateGenerator for a cost function.
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* Called once per init or after postAction.
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* @param weights the weights for every generator.
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*/
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public void updateWeight(double[] weights) {
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weights[StochasticLoadBalancer.GeneratorType.RANDOM.ordinal()] += cost();
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}
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/**
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* Scale the value between 0 and 1.
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* @param min Min value
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@ -90,6 +90,14 @@ public class FavoredStochasticBalancer extends StochasticLoadBalancer implements
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return fnPickers;
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}
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/**
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* @return any candidate generator in random
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*/
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@Override
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protected CandidateGenerator getRandomGenerator() {
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return candidateGenerators.get(ThreadLocalRandom.current().nextInt(candidateGenerators.size()));
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}
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/**
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* Round robin assignment: Segregate the regions into two types:
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*
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@ -88,4 +88,8 @@ abstract class LocalityBasedCostFunction extends CostFunction {
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return cluster.getOrComputeWeightedLocality(region, entity, type);
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}
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}
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@Override
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public final void updateWeight(double[] weights) {
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weights[StochasticLoadBalancer.GeneratorType.LOCALITY.ordinal()] += cost();
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}
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}
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@ -59,4 +59,9 @@ class RegionCountSkewCostFunction extends CostFunction {
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costs[newServer] = cluster.regionsPerServer[newServer].length;
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});
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}
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@Override
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public final void updateWeight(double[] weights) {
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weights[StochasticLoadBalancer.GeneratorType.LOAD.ordinal()] += cost();
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}
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}
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@ -74,6 +74,11 @@ abstract class RegionReplicaGroupingCostFunction extends CostFunction {
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return scale(0, maxCost, totalCost);
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}
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@Override
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public final void updateWeight(double[] weights) {
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weights[StochasticLoadBalancer.GeneratorType.RACK.ordinal()] += cost();
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}
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/**
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* For each primary region, it computes the total number of replicas in the array (numReplicas)
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* and returns a sum of numReplicas-1 squared. For example, if the server hosts regions a, b, c,
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@ -129,7 +129,6 @@ public class StochasticLoadBalancer extends BaseLoadBalancer {
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private int numRegionLoadsToRemember = 15;
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private float minCostNeedBalance = 0.025f;
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private List<CandidateGenerator> candidateGenerators;
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private List<CostFunction> costFunctions; // FindBugs: Wants this protected; IS2_INCONSISTENT_SYNC
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// To save currently configed sum of multiplier. Defaulted at 1 for cases that carry high cost
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private float sumMultiplier;
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@ -137,6 +136,7 @@ public class StochasticLoadBalancer extends BaseLoadBalancer {
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private double curOverallCost = 0d;
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private double[] tempFunctionCosts;
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private double[] curFunctionCosts;
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private double[] weightsOfGenerators;
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// Keep locality based picker and cost function to alert them
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// when new services are offered
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@ -146,6 +146,12 @@ public class StochasticLoadBalancer extends BaseLoadBalancer {
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private RegionReplicaHostCostFunction regionReplicaHostCostFunction;
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private RegionReplicaRackCostFunction regionReplicaRackCostFunction;
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protected List<CandidateGenerator> candidateGenerators;
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public enum GeneratorType {
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RANDOM, LOAD, LOCALITY, RACK
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}
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/**
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* The constructor that pass a MetricsStochasticBalancer to BaseLoadBalancer to replace its
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* default MetricsBalancer
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@ -204,10 +210,11 @@ public class StochasticLoadBalancer extends BaseLoadBalancer {
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protected List<CandidateGenerator> createCandidateGenerators() {
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List<CandidateGenerator> candidateGenerators = new ArrayList<CandidateGenerator>(4);
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candidateGenerators.add(new RandomCandidateGenerator());
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candidateGenerators.add(new LoadCandidateGenerator());
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candidateGenerators.add(localityCandidateGenerator);
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candidateGenerators.add(new RegionReplicaRackCandidateGenerator());
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candidateGenerators.add(GeneratorType.RANDOM.ordinal(), new RandomCandidateGenerator());
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candidateGenerators.add(GeneratorType.LOAD.ordinal(), new LoadCandidateGenerator());
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candidateGenerators.add(GeneratorType.LOCALITY.ordinal(), localityCandidateGenerator);
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candidateGenerators.add(GeneratorType.RACK.ordinal(),
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new RegionReplicaRackCandidateGenerator());
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return candidateGenerators;
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}
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@ -380,8 +387,33 @@ public class StochasticLoadBalancer extends BaseLoadBalancer {
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@RestrictedApi(explanation = "Should only be called in tests", link = "",
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allowedOnPath = ".*(/src/test/.*|StochasticLoadBalancer).java")
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BalanceAction nextAction(BalancerClusterState cluster) {
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return candidateGenerators.get(ThreadLocalRandom.current().nextInt(candidateGenerators.size()))
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.generate(cluster);
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return getRandomGenerator().generate(cluster);
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}
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/**
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* Select the candidate generator to use based on the cost of cost functions. The chance of
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* selecting a candidate generator is propotional to the share of cost of all cost functions among
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* all cost functions that benefit from it.
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*/
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protected CandidateGenerator getRandomGenerator() {
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double sum = 0;
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for (int i = 0; i < weightsOfGenerators.length; i++) {
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sum += weightsOfGenerators[i];
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weightsOfGenerators[i] = sum;
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}
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if (sum == 0) {
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return candidateGenerators.get(0);
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}
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for (int i = 0; i < weightsOfGenerators.length; i++) {
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weightsOfGenerators[i] /= sum;
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}
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double rand = ThreadLocalRandom.current().nextDouble();
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for (int i = 0; i < weightsOfGenerators.length; i++) {
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if (rand <= weightsOfGenerators[i]) {
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return candidateGenerators.get(i);
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}
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}
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return candidateGenerators.get(candidateGenerators.size() - 1);
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}
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@RestrictedApi(explanation = "Should only be called in tests", link = "",
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@ -474,7 +506,7 @@ public class StochasticLoadBalancer extends BaseLoadBalancer {
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}
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cluster.doAction(action);
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updateCostsWithAction(cluster, action);
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updateCostsAndWeightsWithAction(cluster, action);
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newCost = computeCost(cluster, currentCost);
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@ -490,7 +522,7 @@ public class StochasticLoadBalancer extends BaseLoadBalancer {
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// TODO: undo by remembering old values
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BalanceAction undoAction = action.undoAction();
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cluster.doAction(undoAction);
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updateCostsWithAction(cluster, undoAction);
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updateCostsAndWeightsWithAction(cluster, undoAction);
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}
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if (EnvironmentEdgeManager.currentTime() - startTime >
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@ -685,17 +717,28 @@ public class StochasticLoadBalancer extends BaseLoadBalancer {
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@RestrictedApi(explanation = "Should only be called in tests", link = "",
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allowedOnPath = ".*(/src/test/.*|StochasticLoadBalancer).java")
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void initCosts(BalancerClusterState cluster) {
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// Initialize the weights of generator every time
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weightsOfGenerators = new double[this.candidateGenerators.size()];
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for (CostFunction c : costFunctions) {
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c.prepare(cluster);
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c.updateWeight(weightsOfGenerators);
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}
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}
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/**
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* Update both the costs of costfunctions and the weights of candidate generators
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*/
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@RestrictedApi(explanation = "Should only be called in tests", link = "",
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allowedOnPath = ".*(/src/test/.*|StochasticLoadBalancer).java")
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void updateCostsWithAction(BalancerClusterState cluster, BalanceAction action) {
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void updateCostsAndWeightsWithAction(BalancerClusterState cluster, BalanceAction action) {
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// Reset all the weights to 0
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for (int i = 0; i < weightsOfGenerators.length; i++) {
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weightsOfGenerators[i] = 0;
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}
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for (CostFunction c : costFunctions) {
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if (c.isNeeded()) {
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c.postAction(action);
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c.updateWeight(weightsOfGenerators);
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}
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}
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}
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@ -39,7 +39,8 @@ public class StochasticBalancerTestBase extends BalancerTestBase {
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protected static StochasticLoadBalancer loadBalancer;
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protected static DummyMetricsStochasticBalancer dummyMetricsStochasticBalancer = new DummyMetricsStochasticBalancer();
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protected static DummyMetricsStochasticBalancer dummyMetricsStochasticBalancer = new
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DummyMetricsStochasticBalancer();
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@BeforeClass
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public static void beforeAllTests() throws Exception {
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@ -58,7 +59,17 @@ public class StochasticBalancerTestBase extends BalancerTestBase {
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boolean assertFullyBalancedForReplicas) {
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Map<ServerName, List<RegionInfo>> serverMap =
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createServerMap(numNodes, numRegions, numRegionsPerServer, replication, numTables);
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testWithCluster(serverMap, null, assertFullyBalanced, assertFullyBalancedForReplicas);
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testWithCluster(serverMap, null, assertFullyBalanced,
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assertFullyBalancedForReplicas);
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}
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protected void testWithClusterWithIteration(int numNodes, int numRegions, int numRegionsPerServer,
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int replication, int numTables, boolean assertFullyBalanced,
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boolean assertFullyBalancedForReplicas) {
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Map<ServerName, List<RegionInfo>> serverMap =
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createServerMap(numNodes, numRegions, numRegionsPerServer, replication, numTables);
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testWithClusterWithIteration(serverMap, null, assertFullyBalanced,
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assertFullyBalancedForReplicas);
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}
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protected void testWithCluster(Map<ServerName, List<RegionInfo>> serverMap,
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@ -102,7 +113,8 @@ public class StochasticBalancerTestBase extends BalancerTestBase {
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loadBalancer.setRackManager(rackManager);
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// Run the balancer.
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Map<TableName, Map<ServerName, List<RegionInfo>>> LoadOfAllTable = (Map) mockClusterServersWithTables(serverMap);
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Map<TableName, Map<ServerName, List<RegionInfo>>> LoadOfAllTable =
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(Map) mockClusterServersWithTables(serverMap);
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List<RegionPlan> plans = loadBalancer.balanceCluster(LoadOfAllTable);
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assertNotNull("Initial cluster balance should produce plans.", plans);
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@ -464,10 +464,10 @@ public class TestStochasticLoadBalancer extends StochasticBalancerTestBase {
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final double expectedCost = loadBalancer.computeCost(cluster, Double.MAX_VALUE);
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BalanceAction action = loadBalancer.nextAction(cluster);
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cluster.doAction(action);
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loadBalancer.updateCostsWithAction(cluster, action);
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loadBalancer.updateCostsAndWeightsWithAction(cluster, action);
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BalanceAction undoAction = action.undoAction();
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cluster.doAction(undoAction);
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loadBalancer.updateCostsWithAction(cluster, undoAction);
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loadBalancer.updateCostsAndWeightsWithAction(cluster, undoAction);
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final double actualCost = loadBalancer.computeCost(cluster, Double.MAX_VALUE);
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assertEquals(expectedCost, actualCost, 0);
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}
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@ -77,10 +77,9 @@ public class TestStochasticLoadBalancerHeterogeneousCost extends StochasticBalan
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RULES_FILE = HTU.getDataTestDir(DEFAULT_RULES_FILE_NAME).toString();
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conf.set(HeterogeneousRegionCountCostFunction.HBASE_MASTER_BALANCER_HETEROGENEOUS_RULES_FILE,
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RULES_FILE);
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loadBalancer = new StochasticLoadBalancer();
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loadBalancer = new StochasticLoadTestBalancer();
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loadBalancer.setClusterInfoProvider(new DummyClusterInfoProvider(conf));
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loadBalancer.initialize();
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loadBalancer.getCandidateGenerators().add(new FairRandomCandidateGenerator());
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}
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@Test
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@ -302,4 +301,14 @@ public class TestStochasticLoadBalancerHeterogeneousCost extends StochasticBalan
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return super.generate(cluster);
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}
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}
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static class StochasticLoadTestBalancer extends StochasticLoadBalancer {
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private FairRandomCandidateGenerator fairRandomCandidateGenerator =
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new FairRandomCandidateGenerator();
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@Override
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protected CandidateGenerator getRandomGenerator() {
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return fairRandomCandidateGenerator;
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}
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}
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}
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@ -40,6 +40,7 @@ public class TestStochasticLoadBalancerLargeCluster extends StochasticBalancerTe
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int replication = 1;
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conf.setLong("hbase.master.balancer.stochastic.maxRunningTime", 6 * 60 * 1000);
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loadBalancer.onConfigurationChange(conf);
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testWithCluster(numNodes, numRegions, numRegionsPerServer, replication, numTables, true, true);
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testWithClusterWithIteration(numNodes, numRegions, numRegionsPerServer, replication, numTables,
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true, true);
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}
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}
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