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From "Zhihong Yu (Updated) (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (HBASE-5139) Compute (weighted) median using AggregateProtocol
Date Tue, 10 Jan 2012 18:32:39 GMT

     [ https://issues.apache.org/jira/browse/HBASE-5139?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Zhihong Yu updated HBASE-5139:
------------------------------

    Attachment:     (was: 5139.txt)
    
> Compute (weighted) median using AggregateProtocol
> -------------------------------------------------
>
>                 Key: HBASE-5139
>                 URL: https://issues.apache.org/jira/browse/HBASE-5139
>             Project: HBase
>          Issue Type: Sub-task
>            Reporter: Zhihong Yu
>            Assignee: Zhihong Yu
>
> Suppose cf:cq1 stores numeric values and optionally cf:cq2 stores weights. This task
finds out the median value among the values of cf:cq1 (See http://www.stat.ucl.ac.be/ISdidactique/Rhelp/library/R.basic/html/weighted.median.html)
> This can be done in two passes.
> The first pass utilizes AggregateProtocol where the following tuple is returned from
each region:
> (partial-sum-of-values, partial-sum-of-weights)
> The start rowkey (supplied by coprocessor framework) would be used to sort the tuples.
This way we can determine which region (called R) contains the (weighted) median. partial-sum-of-weights
can be 0 if unweighted median is sought
> The second pass involves scanning the table, beginning with startrow of region R and
computing partial (weighted) sum until the threshold of S/2 is crossed. The (weighted) median
is returned.
> However, this approach wouldn't work if there is mutation in the underlying table between
pass one and pass two.
> In that case, sequential scanning seems to be the solution which is slower than the above
approach.

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