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https://issues.apache.org/jira/browse/HBASE-5139?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13191886#comment-13191886
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Hudson commented on HBASE-5139:
-------------------------------
Integrated in HBase-TRUNK #2645 (See
[https://builds.apache.org/job/HBase-TRUNK/2645/])
HBASE-5139 Addendum handles startRow being null for the case where median
is in the first region
tedyu :
Files :
*
/hbase/trunk/src/main/java/org/apache/hadoop/hbase/client/coprocessor/AggregationClient.java
> 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
> Attachments: 5139-v2.txt, 5139.addendum
>
>
> 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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