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From "Kahlil Oppenheimer (JIRA)" <j...@apache.org>
Subject [jira] [Created] (HBASE-17707) New More Accurate TableSkew Balancer/Generator
Date Tue, 28 Feb 2017 04:54:45 GMT
Kahlil Oppenheimer created HBASE-17707:

             Summary: New More Accurate TableSkew Balancer/Generator
                 Key: HBASE-17707
                 URL: https://issues.apache.org/jira/browse/HBASE-17707
             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
            Priority: Minor
         Attachments: HBASE-17707.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 round-robin-ed across the cluster). This number of
moves is computer for each table, then normalized to a score between 0-1 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
0-1, 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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