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From "Charlie Qiangeng Xu (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (HBASE-17110) Add an "Overall Strategy" option(balanced both on table level and server level) to SimpleLoadBalancer
Date Mon, 28 Nov 2016 07:23:59 GMT

     [ https://issues.apache.org/jira/browse/HBASE-17110?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Charlie Qiangeng Xu updated HBASE-17110:
----------------------------------------
    Attachment: HBASE-17110-V6.patch

Finally, I think adding a function setClusterLoad  to the LoadBalancer interface would be
the best choice. Uploaded a new patch, the code looks much cleaner

> Add an "Overall Strategy" option(balanced both on table level and server level) to SimpleLoadBalancer
> -----------------------------------------------------------------------------------------------------
>
>                 Key: HBASE-17110
>                 URL: https://issues.apache.org/jira/browse/HBASE-17110
>             Project: HBase
>          Issue Type: Improvement
>          Components: Balancer
>    Affects Versions: 2.0.0, 1.2.4
>            Reporter: Charlie Qiangeng Xu
>            Assignee: Charlie Qiangeng Xu
>         Attachments: HBASE-17110-V2.patch, HBASE-17110-V3.patch, HBASE-17110-V4.patch,
HBASE-17110-V5.patch, HBASE-17110-V6.patch, HBASE-17110.patch
>
>
> This jira is about an enhancement of simpleLoadBalancer. Here we introduce a new strategy:
"bytableOverall" which could be controlled by adding:
> {noformat}
> <property>
>   <name>hbase.master.loadbalance.bytableOverall</name>
>   <value>true</value>
> </property>
> {noformat}
> We have been using the strategy on our largest cluster for several months. it's proven
to be very helpful and stable, especially, the result is quite visible to the users.
> Here is the reason why it's helpful:
> When operating large scale clusters(our case), some companies still prefer to use {{SimpleLoadBalancer}}
due to its simplicity, quick balance plan generation, etc. Current SimpleLoadBalancer has
two modes: 
> 1. byTable, which only guarantees that the regions of one table could be uniformly distributed.

> 2. byCluster, which ignores the distribution within tables and balance the regions all
together.
> If the pressures on different tables are different, the first byTable option is the preferable
one in most case. Yet, this choice sacrifice the cluster level balance and would cause some
servers to have significantly higher load, e.g. 242 regions on server A but 417 regions on
server B.(real world stats)
> Consider this case,  a cluster has 3 tables and 4 servers:
> {noformat}
>   server A has 3 regions: table1:1, table2:1, table3:1
>   server B has 3 regions: table1:2, table2:2, table3:2
>   server C has 3 regions: table1:3, table2:3, table3:3
>   server D has 0 regions.
> {noformat}
> From the byTable strategy's perspective, the cluster has already been perfectly balanced
on table level. But a perfect status should be like:
> {noformat}
>   server A has 2 regions: table2:1, table3:1
>   server B has 2 regions: table1:2, table3:2
>   server C has 3 regions: table1:3, table2:3, table3:3
>   server D has 2 regions: table1:1, table2:2
> {noformat}
> We can see the server loads change from 3,3,3,0 to 2,2,3,2, while the table1, table2
and table3 still keep balanced.   
> And this is what the new mode "byTableOverall" can achieve.
> Two UTs have been added as well and the last one demonstrates the advantage of the new
strategy.
> Also, a onConfigurationChange method has been implemented to hot control the "slop" variable.
>  



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