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https://issues.apache.org/jira/browse/HBASE-6800?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13457945#comment-13457945
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Andrew Purtell commented on HBASE-6800:
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bq. If moving your code into Apache is a goal, you could also start the
co-processor project in the apache incubator. You could do that while being
consistent with andrew's suggested methodology (not forking HBase, mavenized
integration...).
This is a good suggestion. Panthera isn't so much an enhancement to HBase but
rather a full application on top, and with wider scope than just HBase -- also
Hive, and additional new components. In the scope of the HBase project alone,
API changes, core changes, and (incorporating my earlier comment) utility
coprocessors of sufficient generality make a lot of sense, as well as
addressing the meta issues raised (I.e. should HBase have Eclipse plugin like
tooling for getting and installing CPs). HBase should be a good platform for
your work, let us know what you need.
> Build a Document Store on HBase for Better Query Processing
> -----------------------------------------------------------
>
> Key: HBASE-6800
> URL: https://issues.apache.org/jira/browse/HBASE-6800
> Project: HBase
> Issue Type: New Feature
> Components: coprocessors, performance
> Affects Versions: 0.96.0
> Reporter: Jason Dai
> Attachments: dot-deisgn.pdf
>
>
> In the last couple of years, increasingly more people begin to stream data
> into HBase in near time, and
> use high level queries (e.g., Hive) to analyze the data in HBase directly.
> While HBase already has very effective MapReduce integration with its good
> scanning performance, query processing using MapReduce on HBase still has
> significant gaps compared to HDFS: ~3x space overheads and 3~5x performance
> overheads according to our measurement.
> We propose to implement a document store on HBase, which can greatly improve
> query processing on HBase (by leveraging the relational model and read-mostly
> access patterns). According to our prototype, it can reduce space usage by
> up-to ~3x and speedup query processing by up-to ~1.8x.
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