org.apache.hadoop.hbase.master.balancer
Class StochasticLoadBalancer

java.lang.Object
  org.apache.hadoop.hbase.master.balancer.BaseLoadBalancer
      org.apache.hadoop.hbase.master.balancer.StochasticLoadBalancer

All Implemented Interfaces:

org.apache.hadoop.conf.Configurable, LoadBalancer

@InterfaceAudience.Private
public class StochasticLoadBalancer
extends BaseLoadBalancer

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.

Field Summary

Fields inherited from class org.apache.hadoop.hbase.master.balancer.BaseLoadBalancer

services

Constructor Summary

StochasticLoadBalancer()

Method Summary

List<RegionPlan>	balanceCluster(Map<ServerName,List<HRegionInfo>> clusterState) Given the cluster state this will try and approach an optimal balance.
protected double	computeCost(Map<HRegionInfo,ServerName> initialRegionMapping, Map<ServerName,List<HRegionInfo>> clusterState) This is the main cost function.
void	setClusterStatus(ClusterStatus st) Set the current cluster status.
void	setConf(org.apache.hadoop.conf.Configuration conf)
void	setMasterServices(MasterServices masterServices) Set the master service.

Methods inherited from class org.apache.hadoop.hbase.master.balancer.BaseLoadBalancer

getConf, immediateAssignment, needsBalance, randomAssignment, retainAssignment, roundRobinAssignment

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

StochasticLoadBalancer

public StochasticLoadBalancer()

Method Detail

setConf

public void setConf(org.apache.hadoop.conf.Configuration conf)

Specified by:

setConf in interface org.apache.hadoop.conf.Configurable

Overrides:

setConf in class BaseLoadBalancer

setClusterStatus

public void setClusterStatus(ClusterStatus st)

Description copied from interface: LoadBalancer

Set the current cluster status. This allows a LoadBalancer to map host name to a server

Specified by:

setClusterStatus in interface LoadBalancer

Overrides:

setClusterStatus in class BaseLoadBalancer

setMasterServices

public void setMasterServices(MasterServices masterServices)

Description copied from interface: LoadBalancer

Set the master service.

Specified by:

setMasterServices in interface LoadBalancer

Overrides:

setMasterServices in class BaseLoadBalancer

balanceCluster

public List<RegionPlan> balanceCluster(Map<ServerName,List<HRegionInfo>> clusterState)

Given the cluster state this will try and approach an optimal balance. This should always approach the optimal state given enough steps.

Returns:

List of plans

computeCost

protected double computeCost(Map<HRegionInfo,ServerName> initialRegionMapping,
                             Map<ServerName,List<HRegionInfo>> clusterState)

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.

Parameters:

initialRegionMapping - Map of where the regions started.

clusterState - Map of ServerName to list of regions.

Returns:

a double of a cost associated with the proposed