[ https://issues.apache.org/jira/browse/HBASE17707?page=com.atlassian.jira.plugin.system.issuetabpanels:alltabpanel
]
Kahlil Oppenheimer updated HBASE17707:

Release Note: There are now new table skew cost functions and table skew candidate generators
in the stochastic load balancer to more evenly spread tables across the cluster. Table skew
cost is computed per table, and the final table skew cost number is a weighted average of
the maximum skew cost for a given table with the average skew cost across all tables. To configure
how much weight the maximum skew cost for a single table should get, you can change "hbase.master.balancer.stochastic.maxTableSkewWeight"
to a float between 0.0 and 1.0, where 0.0 means the max table skew gets 0% of the weight and
1.0 means max table skew gets 100% of the weight. This value is useful if you want to strongly
penalize any one table being skewed (even if all others are evenly balanced). We default this
value to 0.0 because this works best for most cases in practice.
> New More Accurate Table Skew cost function/generator
> 
>
> Key: HBASE17707
> URL: https://issues.apache.org/jira/browse/HBASE17707
> Project: HBase
> Issue Type: New Feature
> Components: Balancer
> Affects Versions: 1.2.0
> Environment: CentOS Derivative with a derivative of the 3.18.43 kernel. HBase
on CDH5.9.0 with some patches. HDFS CDH 5.9.0 with no patches.
> Reporter: Kahlil Oppenheimer
> Assignee: Kahlil Oppenheimer
> Priority: Minor
> Fix For: 2.0
>
> Attachments: HBASE1770700.patch, HBASE1770701.patch, HBASE1770702.patch,
HBASE1770703.patch, HBASE1770704.patch
>
>
> This patch includes new version of the TableSkewCostFunction and a new TableSkewCandidateGenerator.
> The new TableSkewCostFunction computes table skew by counting the minimal number of region
moves required for a given table to perfectly balance the table across the cluster (i.e. as
if the regions from that table had been roundrobined across the cluster). This number of
moves is computer for each table, then normalized to a score between 01 by dividing by the
number of moves required in the absolute worst case (i.e. the entire table is stored on one
server), and stored in an array. The cost function then takes a weighted average of the average
and maximum value across all tables. The weights in this average are configurable to allow
for certain users to more strongly penalize situations where one table is skewed versus where
every table is a little bit skewed. To better spread this value more evenly across the range
01, we take the square root of the weighted average to get the final value.
> The new TableSkewCandidateGenerator generates region moves/swaps to optimize the above
TableSkewCostFunction. It first simply tries to move regions until each server has the right
number of regions, then it swaps regions around such that each region swap improves table
skew across the cluster.
> We tested the cost function and generator in our production clusters with 100s of TBs
of data and 100s of tables across dozens of servers and found both to be very performant and
accurate.

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