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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.
*/
package org.apache.hadoop.hbase.master.balancer;
import java.util.ArrayDeque;
import java.util.Collection;
import java.util.Deque;
import java.util.HashMap;
import java.util.LinkedList;
import java.util.List;
import java.util.Map;
import java.util.Map.Entry;
import java.util.Random;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.apache.commons.math.stat.descriptive.DescriptiveStatistics;
import org.apache.hadoop.hbase.classification.InterfaceAudience;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.hbase.ClusterStatus;
import org.apache.hadoop.hbase.HBaseInterfaceAudience;
import org.apache.hadoop.hbase.HRegionInfo;
import org.apache.hadoop.hbase.RegionLoad;
import org.apache.hadoop.hbase.ServerLoad;
import org.apache.hadoop.hbase.ServerName;
import org.apache.hadoop.hbase.master.MasterServices;
import org.apache.hadoop.hbase.master.RegionPlan;
import org.apache.hadoop.hbase.util.Bytes;
import org.apache.hadoop.hbase.util.EnvironmentEdgeManager;
import org.apache.hadoop.hbase.util.Pair;
/**
* This is a best effort load balancer. Given a Cost function F(C) => x It will
* randomly try and mutate the cluster to Cprime. If F(Cprime) < F(C) then the
* new cluster state becomes the plan. It includes costs functions to compute the cost of:
*
* - Region Load
* - Table Load
* - Data Locality
* - Memstore Sizes
* - Storefile Sizes
*
*
*
* Every cost function returns a number between 0 and 1 inclusive; where 0 is the lowest cost
* best solution, and 1 is the highest possible cost and the worst solution. The computed costs are
* scaled by their respective multipliers:
*
*
* - hbase.master.balancer.stochastic.regionLoadCost
* - hbase.master.balancer.stochastic.moveCost
* - hbase.master.balancer.stochastic.tableLoadCost
* - hbase.master.balancer.stochastic.localityCost
* - hbase.master.balancer.stochastic.memstoreSizeCost
* - hbase.master.balancer.stochastic.storefileSizeCost
*
*
* In addition to the above configurations, the balancer can be tuned by the following
* configuration values:
*
* - hbase.master.balancer.stochastic.maxMoveRegions which
* controls what the max number of regions that can be moved in a single invocation of this
* balancer.
* - hbase.master.balancer.stochastic.stepsPerRegion is the coefficient by which the number of
* regions is multiplied to try and get the number of times the balancer will
* mutate all servers.
* - hbase.master.balancer.stochastic.maxSteps which controls the maximum number of times that
* the balancer will try and mutate all the servers. The balancer will use the minimum of this
* value and the above computation.
*
*
* This balancer is best used with hbase.master.loadbalance.bytable set to false
* so that the balancer gets the full picture of all loads on the cluster.
*/
@InterfaceAudience.LimitedPrivate(HBaseInterfaceAudience.CONFIG)
public class StochasticLoadBalancer extends BaseLoadBalancer {
private static final String STEPS_PER_REGION_KEY =
"hbase.master.balancer.stochastic.stepsPerRegion";
private static final String MAX_STEPS_KEY =
"hbase.master.balancer.stochastic.maxSteps";
private static final String MAX_RUNNING_TIME_KEY =
"hbase.master.balancer.stochastic.maxRunningTime";
private static final String KEEP_REGION_LOADS =
"hbase.master.balancer.stochastic.numRegionLoadsToRemember";
private static final Random RANDOM = new Random(System.currentTimeMillis());
private static final Log LOG = LogFactory.getLog(StochasticLoadBalancer.class);
private final RegionLocationFinder regionFinder = new RegionLocationFinder();
private ClusterStatus clusterStatus = null;
Map> loads = new HashMap>();
// values are defaults
private int maxSteps = 1000000;
private int stepsPerRegion = 800;
private long maxRunningTime = 30 * 1000 * 1; // 30 seconds.
private int numRegionLoadsToRemember = 15;
private RegionPicker[] pickers;
private CostFromRegionLoadFunction[] regionLoadFunctions;
private CostFunction[] costFunctions;
// Keep locality based picker and cost function to alert them
// when new services are offered
private LocalityBasedPicker localityPicker;
private LocalityCostFunction localityCost;
@Override
public void setConf(Configuration conf) {
super.setConf(conf);
regionFinder.setConf(conf);
maxSteps = conf.getInt(MAX_STEPS_KEY, maxSteps);
stepsPerRegion = conf.getInt(STEPS_PER_REGION_KEY, stepsPerRegion);
maxRunningTime = conf.getLong(MAX_RUNNING_TIME_KEY, maxRunningTime);
numRegionLoadsToRemember = conf.getInt(KEEP_REGION_LOADS, numRegionLoadsToRemember);
localityPicker = new LocalityBasedPicker(services);
localityCost = new LocalityCostFunction(conf, services);
pickers = new RegionPicker[] {
new RandomRegionPicker(),
new LoadPicker(),
localityPicker
};
regionLoadFunctions = new CostFromRegionLoadFunction[] {
new ReadRequestCostFunction(conf),
new WriteRequestCostFunction(conf),
new MemstoreSizeCostFunction(conf),
new StoreFileCostFunction(conf)
};
costFunctions = new CostFunction[]{
new RegionCountSkewCostFunction(conf),
new MoveCostFunction(conf),
localityCost,
new TableSkewCostFunction(conf),
regionLoadFunctions[0],
regionLoadFunctions[1],
regionLoadFunctions[2],
regionLoadFunctions[3],
};
}
@Override
protected void setSlop(Configuration conf) {
this.slop = conf.getFloat("hbase.regions.slop", 0.001F);
}
@Override
public void setClusterStatus(ClusterStatus st) {
super.setClusterStatus(st);
regionFinder.setClusterStatus(st);
this.clusterStatus = st;
updateRegionLoad();
for(CostFromRegionLoadFunction cost : regionLoadFunctions) {
cost.setClusterStatus(st);
}
}
@Override
public void setMasterServices(MasterServices masterServices) {
super.setMasterServices(masterServices);
this.regionFinder.setServices(masterServices);
this.localityCost.setServices(masterServices);
this.localityPicker.setServices(masterServices);
}
/**
* Given the cluster state this will try and approach an optimal balance. This
* should always approach the optimal state given enough steps.
*/
@Override
public List balanceCluster(Map> clusterState) {
if (!needsBalance(new ClusterLoadState(clusterState))) {
return null;
}
long startTime = EnvironmentEdgeManager.currentTimeMillis();
// On clusters with lots of HFileLinks or lots of reference files,
// instantiating the storefile infos can be quite expensive.
// Allow turning this feature off if the locality cost is not going to
// be used in any computations.
RegionLocationFinder finder = null;
if (this.localityCost != null && this.localityCost.getMultiplier() > 0) {
finder = this.regionFinder;
}
// Keep track of servers to iterate through them.
Cluster cluster = new Cluster(clusterState, loads, finder);
double currentCost = computeCost(cluster, Double.MAX_VALUE);
double initCost = currentCost;
double newCost = currentCost;
long computedMaxSteps = Math.min(this.maxSteps,
((long)cluster.numRegions * (long)this.stepsPerRegion * (long)cluster.numServers));
// Perform a stochastic walk to see if we can get a good fit.
long step;
for (step = 0; step < computedMaxSteps; step++) {
int pickerIdx = RANDOM.nextInt(pickers.length);
RegionPicker p = pickers[pickerIdx];
Pair, Pair> picks = p.pick(cluster);
int leftServer = picks.getFirst().getFirst();
int leftRegion = picks.getFirst().getSecond();
int rightServer = picks.getSecond().getFirst();
int rightRegion = picks.getSecond().getSecond();
// We couldn't find a server
if (rightServer < 0 || leftServer < 0) {
continue;
}
// We randomly picked to do nothing.
if (leftRegion < 0 && rightRegion < 0) {
continue;
}
cluster.moveOrSwapRegion(leftServer,
rightServer,
leftRegion,
rightRegion);
newCost = computeCost(cluster, currentCost);
// Should this be kept?
if (newCost < currentCost) {
currentCost = newCost;
} else {
// Put things back the way they were before.
// TODO: undo by remembering old values, using an UndoAction class
cluster.moveOrSwapRegion(leftServer,
rightServer,
rightRegion,
leftRegion);
}
if (EnvironmentEdgeManager.currentTimeMillis() - startTime >
maxRunningTime) {
break;
}
}
long endTime = EnvironmentEdgeManager.currentTimeMillis();
metricsBalancer.balanceCluster(endTime - startTime);
if (initCost > currentCost) {
List plans = createRegionPlans(cluster);
if (LOG.isDebugEnabled()) {
LOG.debug("Finished computing new load balance plan. Computation took "
+ (endTime - startTime) + "ms to try " + step
+ " different iterations. Found a solution that moves "
+ plans.size() + " regions; Going from a computed cost of "
+ initCost + " to a new cost of " + currentCost);
}
return plans;
}
if (LOG.isDebugEnabled()) {
LOG.debug("Could not find a better load balance plan. Tried "
+ step + " different configurations in " + (endTime - startTime)
+ "ms, and did not find anything with a computed cost less than " + initCost);
}
return null;
}
/**
* Create all of the RegionPlan's needed to move from the initial cluster state to the desired
* state.
*
* @param cluster The state of the cluster
* @return List of RegionPlan's that represent the moves needed to get to desired final state.
*/
private List createRegionPlans(Cluster cluster) {
List plans = new LinkedList();
for (int regionIndex = 0;
regionIndex < cluster.regionIndexToServerIndex.length; regionIndex++) {
int initialServerIndex = cluster.initialRegionIndexToServerIndex[regionIndex];
int newServerIndex = cluster.regionIndexToServerIndex[regionIndex];
if (initialServerIndex != newServerIndex) {
HRegionInfo region = cluster.regions[regionIndex];
ServerName initialServer = cluster.servers[initialServerIndex];
ServerName newServer = cluster.servers[newServerIndex];
if (LOG.isTraceEnabled()) {
LOG.trace("Moving Region " + region.getEncodedName() + " from server "
+ initialServer.getHostname() + " to " + newServer.getHostname());
}
RegionPlan rp = new RegionPlan(region, initialServer, newServer);
plans.add(rp);
}
}
return plans;
}
/**
* Store the current region loads.
*/
private synchronized void updateRegionLoad() {
// We create a new hashmap so that regions that are no longer there are removed.
// However we temporarily need the old loads so we can use them to keep the rolling average.
Map> oldLoads = loads;
loads = new HashMap>();
for (ServerName sn : clusterStatus.getServers()) {
ServerLoad sl = clusterStatus.getLoad(sn);
if (sl == null) {
continue;
}
for (Entry entry : sl.getRegionsLoad().entrySet()) {
Deque rLoads = oldLoads.get(Bytes.toString(entry.getKey()));
if (rLoads == null) {
// There was nothing there
rLoads = new ArrayDeque();
} else if (rLoads.size() >= numRegionLoadsToRemember) {
rLoads.remove();
}
rLoads.add(entry.getValue());
loads.put(Bytes.toString(entry.getKey()), rLoads);
}
}
for(CostFromRegionLoadFunction cost : regionLoadFunctions) {
cost.setLoads(loads);
}
}
/**
* This is the main cost function. It will compute a cost associated with a proposed cluster
* state. All different costs will be combined with their multipliers to produce a double cost.
*
* @param cluster The state of the cluster
* @param previousCost the previous cost. This is used as an early out.
* @return a double of a cost associated with the proposed cluster state. This cost is an
* aggregate of all individual cost functions.
*/
protected double computeCost(Cluster cluster, double previousCost) {
double total = 0;
for (CostFunction c:costFunctions) {
if (c.getMultiplier() <= 0) {
continue;
}
total += c.getMultiplier() * c.cost(cluster);
if (total > previousCost) {
return total;
}
}
return total;
}
abstract static class RegionPicker {
abstract Pair, Pair> pick(Cluster cluster);
/**
* From a list of regions pick a random one. Null can be returned which
* {@link StochasticLoadBalancer#balanceCluster(Map)} recognize as signal to try a region move
* rather than swap.
*
* @param cluster The state of the cluster
* @param server index of the server
* @param chanceOfNoSwap Chance that this will decide to try a move rather
* than a swap.
* @return a random {@link HRegionInfo} or null if an asymmetrical move is
* suggested.
*/
protected int pickRandomRegion(Cluster cluster, int server, double chanceOfNoSwap) {
// Check to see if this is just a move.
if (cluster.regionsPerServer[server].length == 0 || RANDOM.nextFloat() < chanceOfNoSwap) {
// signal a move only.
return -1;
}
int rand = RANDOM.nextInt(cluster.regionsPerServer[server].length);
return cluster.regionsPerServer[server][rand];
}
protected int pickRandomServer(Cluster cluster) {
if (cluster.numServers < 1) {
return -1;
}
return RANDOM.nextInt(cluster.numServers);
}
protected int pickOtherRandomServer(Cluster cluster, int serverIndex) {
if (cluster.numServers < 2) {
return -1;
}
while (true) {
int otherServerIndex = pickRandomServer(cluster);
if (otherServerIndex != serverIndex) {
return otherServerIndex;
}
}
}
protected Pair pickRandomRegions(Cluster cluster,
int thisServer,
int otherServer) {
if (thisServer < 0 || otherServer < 0) {
return new Pair(-1, -1);
}
// Decide who is most likely to need another region
int thisRegionCount = cluster.getNumRegions(thisServer);
int otherRegionCount = cluster.getNumRegions(otherServer);
// Assign the chance based upon the above
double thisChance = (thisRegionCount > otherRegionCount) ? 0 : 0.5;
double otherChance = (thisRegionCount <= otherRegionCount) ? 0 : 0.5;
int thisRegion = pickRandomRegion(cluster, thisServer, thisChance);
int otherRegion = pickRandomRegion(cluster, otherServer, otherChance);
return new Pair(thisRegion, otherRegion);
}
}
static class RandomRegionPicker extends RegionPicker {
@Override
Pair, Pair> pick(Cluster cluster) {
int thisServer = pickRandomServer(cluster);
// Pick the other server
int otherServer = pickOtherRandomServer(cluster, thisServer);
Pair regions = pickRandomRegions(cluster, thisServer, otherServer);
return new Pair, Pair>(
new Pair(thisServer, regions.getFirst()),
new Pair(otherServer, regions.getSecond())
);
}
}
public static class LoadPicker extends RegionPicker {
@Override
Pair, Pair> pick(Cluster cluster) {
cluster.sortServersByRegionCount();
int thisServer = pickMostLoadedServer(cluster, -1);
int otherServer = pickLeastLoadedServer(cluster, thisServer);
Pair regions = pickRandomRegions(cluster, thisServer, otherServer);
return new Pair, Pair>(
new Pair(thisServer, regions.getFirst()),
new Pair(otherServer, regions.getSecond())
);
}
private int pickLeastLoadedServer(final Cluster cluster, int thisServer) {
Integer[] servers = cluster.serverIndicesSortedByRegionCount;
int index = 0;
while (servers[index] == null || servers[index] == thisServer) {
index++;
if (index == servers.length) {
return -1;
}
}
return servers[index];
}
private int pickMostLoadedServer(final Cluster cluster, int thisServer) {
Integer[] servers = cluster.serverIndicesSortedByRegionCount;
int index = servers.length - 1;
while (servers[index] == null || servers[index] == thisServer) {
index--;
if (index < 0) {
return -1;
}
}
return servers[index];
}
}
static class LocalityBasedPicker extends RegionPicker {
private MasterServices masterServices;
LocalityBasedPicker(MasterServices masterServices) {
this.masterServices = masterServices;
}
@Override
Pair, Pair> pick(Cluster cluster) {
if (this.masterServices == null) {
return new Pair, Pair>(
new Pair(-1,-1),
new Pair(-1,-1)
);
}
// Pick a random region server
int thisServer = pickRandomServer(cluster);
// Pick a random region on this server
int thisRegion = pickRandomRegion(cluster, thisServer, 0.0f);
if (thisRegion == -1) {
return new Pair, Pair>(
new Pair(-1,-1),
new Pair(-1,-1)
);
}
// Pick the server with the highest locality
int otherServer = pickHighestLocalityServer(cluster, thisServer, thisRegion);
// pick an region on the other server to potentially swap
int otherRegion = this.pickRandomRegion(cluster, otherServer, 0.5f);
return new Pair, Pair>(
new Pair(thisServer,thisRegion),
new Pair(otherServer,otherRegion)
);
}
private int pickHighestLocalityServer(Cluster cluster, int thisServer, int thisRegion) {
int[] regionLocations = cluster.regionLocations[thisRegion];
if (regionLocations == null || regionLocations.length <= 1) {
return pickOtherRandomServer(cluster, thisServer);
}
for (int loc : regionLocations) {
if (loc >= 0 && loc != thisServer) { // find the first suitable server
return loc;
}
}
// no location found
return pickOtherRandomServer(cluster, thisServer);
}
void setServices(MasterServices services) {
this.masterServices = services;
}
}
/**
* Base class of StochasticLoadBalancer's Cost Functions.
*/
public abstract static class CostFunction {
private float multiplier = 0;
private Configuration conf;
CostFunction(Configuration c) {
this.conf = c;
}
float getMultiplier() {
return multiplier;
}
void setMultiplier(float m) {
this.multiplier = m;
}
abstract double cost(Cluster cluster);
/**
* Function to compute a scaled cost using {@link DescriptiveStatistics}. It
* assumes that this is a zero sum set of costs. It assumes that the worst case
* possible is all of the elements in one region server and the rest having 0.
*
* @param stats the costs
* @return a scaled set of costs.
*/
protected double costFromArray(double[] stats) {
double totalCost = 0;
double total = getSum(stats);
double mean = total/((double)stats.length);
double count = stats.length;
// Compute max as if all region servers had 0 and one had the sum of all costs. This must be
// a zero sum cost for this to make sense.
double max = ((count - 1) * mean) + (total - mean);
// It's possible that there aren't enough regions to go around
double min;
if (count > total) {
min = ((count - total) * mean) + ((1 - mean) * total);
} else {
// Some will have 1 more than everything else.
int numHigh = (int) (total - (Math.floor(mean) * count));
int numLow = (int) (count - numHigh);
min = (numHigh * (Math.ceil(mean) - mean)) + (numLow * (mean - Math.floor(mean)));
}
min = Math.max(0, min);
for (int i=0; i maxMoves) {
return 1000000; // return a number much greater than any of the other cost
}
// hbase:meta region is special
if (cluster.numMovedMetaRegions > 0) {
// assume each hbase:meta region move costs 10 times
moveCost += META_MOVE_COST_MULT * cluster.numMovedMetaRegions;
}
return scale(0, Math.min(cluster.numRegions, maxMoves) + META_MOVE_COST_MULT, moveCost);
}
}
/**
* Compute the cost of a potential cluster state from skew in number of
* regions on a cluster.
*/
public static class RegionCountSkewCostFunction extends CostFunction {
private static final String REGION_COUNT_SKEW_COST_KEY =
"hbase.master.balancer.stochastic.regionCountCost";
private static final float DEFAULT_REGION_COUNT_SKEW_COST = 500;
private double[] stats = null;
RegionCountSkewCostFunction(Configuration conf) {
super(conf);
// Load multiplier should be the greatest as it is the most general way to balance data.
this.setMultiplier(conf.getFloat(REGION_COUNT_SKEW_COST_KEY, DEFAULT_REGION_COUNT_SKEW_COST));
}
@Override
double cost(Cluster cluster) {
if (stats == null || stats.length != cluster.numServers) {
stats = new double[cluster.numServers];
}
for (int i =0; i < cluster.numServers; i++) {
stats[i] = cluster.regionsPerServer[i].length;
}
return costFromArray(stats);
}
}
/**
* Compute the cost of a potential cluster configuration based upon how evenly
* distributed tables are.
*/
public static class TableSkewCostFunction extends CostFunction {
private static final String TABLE_SKEW_COST_KEY =
"hbase.master.balancer.stochastic.tableSkewCost";
private static final float DEFAULT_TABLE_SKEW_COST = 35;
TableSkewCostFunction(Configuration conf) {
super(conf);
this.setMultiplier(conf.getFloat(TABLE_SKEW_COST_KEY, DEFAULT_TABLE_SKEW_COST));
}
@Override
double cost(Cluster cluster) {
double max = cluster.numRegions;
double min = ((double) cluster.numRegions) / cluster.numServers;
double value = 0;
for (int i = 0; i < cluster.numMaxRegionsPerTable.length; i++) {
value += cluster.numMaxRegionsPerTable[i];
}
return scale(min, max, value);
}
}
/**
* Compute a cost of a potential cluster configuration based upon where
* {@link org.apache.hadoop.hbase.regionserver.StoreFile}s are located.
*/
public static class LocalityCostFunction extends CostFunction {
private static final String LOCALITY_COST_KEY = "hbase.master.balancer.stochastic.localityCost";
private static final float DEFAULT_LOCALITY_COST = 25;
private MasterServices services;
LocalityCostFunction(Configuration conf, MasterServices srv) {
super(conf);
this.setMultiplier(conf.getFloat(LOCALITY_COST_KEY, DEFAULT_LOCALITY_COST));
this.services = srv;
}
void setServices(MasterServices srvc) {
this.services = srvc;
}
@Override
double cost(Cluster cluster) {
double max = 0;
double cost = 0;
// If there's no master so there's no way anything else works.
if (this.services == null) {
return cost;
}
for (int i = 0; i < cluster.regionLocations.length; i++) {
max += 1;
int serverIndex = cluster.regionIndexToServerIndex[i];
int[] regionLocations = cluster.regionLocations[i];
// If we can't find where the data is getTopBlock returns null.
// so count that as being the best possible.
if (regionLocations == null) {
continue;
}
int index = -1;
for (int j = 0; j < regionLocations.length; j++) {
if (regionLocations[j] >= 0 && regionLocations[j] == serverIndex) {
index = j;
break;
}
}
if (index < 0) {
if (regionLocations.length > 0) {
cost += 1;
}
} else {
cost += (double) index / (double) regionLocations.length;
}
}
return scale(0, max, cost);
}
}
/**
* Base class the allows writing costs functions from rolling average of some
* number from RegionLoad.
*/
public abstract static class CostFromRegionLoadFunction extends CostFunction {
private ClusterStatus clusterStatus = null;
private Map> loads = null;
private double[] stats = null;
CostFromRegionLoadFunction(Configuration conf) {
super(conf);
}
void setClusterStatus(ClusterStatus status) {
this.clusterStatus = status;
}
void setLoads(Map> l) {
this.loads = l;
}
@Override
double cost(Cluster cluster) {
if (clusterStatus == null || loads == null) {
return 0;
}
if (stats == null || stats.length != cluster.numServers) {
stats = new double[cluster.numServers];
}
for (int i =0; i < stats.length; i++) {
//Cost this server has from RegionLoad
long cost = 0;
// for every region on this server get the rl
for(int regionIndex:cluster.regionsPerServer[i]) {
Collection regionLoadList = cluster.regionLoads[regionIndex];
// Now if we found a region load get the type of cost that was requested.
if (regionLoadList != null) {
cost += getRegionLoadCost(regionLoadList);
}
}
// Add the total cost to the stats.
stats[i] = cost;
}
// Now return the scaled cost from data held in the stats object.
return costFromArray(stats);
}
protected double getRegionLoadCost(Collection regionLoadList) {
double cost = 0;
for (RegionLoad rl : regionLoadList) {
double toAdd = getCostFromRl(rl);
if (cost == 0) {
cost = toAdd;
} else {
cost = (.5 * cost) + (.5 * toAdd);
}
}
return cost;
}
protected abstract double getCostFromRl(RegionLoad rl);
}
/**
* Compute the cost of total number of read requests The more unbalanced the higher the
* computed cost will be. This uses a rolling average of regionload.
*/
public static class ReadRequestCostFunction extends CostFromRegionLoadFunction {
private static final String READ_REQUEST_COST_KEY =
"hbase.master.balancer.stochastic.readRequestCost";
private static final float DEFAULT_READ_REQUEST_COST = 5;
ReadRequestCostFunction(Configuration conf) {
super(conf);
this.setMultiplier(conf.getFloat(READ_REQUEST_COST_KEY, DEFAULT_READ_REQUEST_COST));
}
@Override
protected double getCostFromRl(RegionLoad rl) {
return rl.getReadRequestsCount();
}
}
/**
* Compute the cost of total number of write requests. The more unbalanced the higher the
* computed cost will be. This uses a rolling average of regionload.
*/
public static class WriteRequestCostFunction extends CostFromRegionLoadFunction {
private static final String WRITE_REQUEST_COST_KEY =
"hbase.master.balancer.stochastic.writeRequestCost";
private static final float DEFAULT_WRITE_REQUEST_COST = 5;
WriteRequestCostFunction(Configuration conf) {
super(conf);
this.setMultiplier(conf.getFloat(WRITE_REQUEST_COST_KEY, DEFAULT_WRITE_REQUEST_COST));
}
@Override
protected double getCostFromRl(RegionLoad rl) {
return rl.getWriteRequestsCount();
}
}
/**
* Compute the cost of total memstore size. The more unbalanced the higher the
* computed cost will be. This uses a rolling average of regionload.
*/
public static class MemstoreSizeCostFunction extends CostFromRegionLoadFunction {
private static final String MEMSTORE_SIZE_COST_KEY =
"hbase.master.balancer.stochastic.memstoreSizeCost";
private static final float DEFAULT_MEMSTORE_SIZE_COST = 5;
MemstoreSizeCostFunction(Configuration conf) {
super(conf);
this.setMultiplier(conf.getFloat(MEMSTORE_SIZE_COST_KEY, DEFAULT_MEMSTORE_SIZE_COST));
}
@Override
protected double getCostFromRl(RegionLoad rl) {
return rl.getMemStoreSizeMB();
}
}
/**
* Compute the cost of total open storefiles size. The more unbalanced the higher the
* computed cost will be. This uses a rolling average of regionload.
*/
public static class StoreFileCostFunction extends CostFromRegionLoadFunction {
private static final String STOREFILE_SIZE_COST_KEY =
"hbase.master.balancer.stochastic.storefileSizeCost";
private static final float DEFAULT_STOREFILE_SIZE_COST = 5;
StoreFileCostFunction(Configuration conf) {
super(conf);
this.setMultiplier(conf.getFloat(STOREFILE_SIZE_COST_KEY, DEFAULT_STOREFILE_SIZE_COST));
}
@Override
protected double getCostFromRl(RegionLoad rl) {
return rl.getStorefileSizeMB();
}
}
}