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Date: Mon, 6 Mar 2017 17:34:32 +0000 (UTC)
From: "Kahlil Oppenheimer (JIRA)" <jira@apache.org>
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Subject: [jira] [Commented] (HBASE-17707) New More Accurate Table Skew cost
 function/generator
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archived-at: Mon, 06 Mar 2017 17:34:38 -0000


    [ https://issues.apache.org/jira/browse/HBASE-17707?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15897708#comment-15897708 ] 

Kahlil Oppenheimer commented on HBASE-17707:
--------------------------------------------

Just fixed and re-uploaded v7. I originally uploaded the wrong file.

> New More Accurate Table Skew cost function/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
>            Assignee: Kahlil Oppenheimer
>            Priority: Minor
>             Fix For: 2.0
>
>         Attachments: HBASE-17707-00.patch, HBASE-17707-01.patch, HBASE-17707-02.patch, HBASE-17707-03.patch, HBASE-17707-04.patch, HBASE-17707-05.patch, HBASE-17707-06.patch, HBASE-17707-07.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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