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https://issues.apache.org/jira/browse/HBASE-11482?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Andrew Purtell updated HBASE-11482:
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Summary: Optimize HBase TableInput/OutputFormats for exposing tables and
snapshots as Spark RDDs (was: Optimize HBase TableInputFormat and
TableOutputFormat for tables and snapshots as Spark RDDs)
> Optimize HBase TableInput/OutputFormats for exposing tables and snapshots as
> Spark RDDs
> ---------------------------------------------------------------------------------------
>
> Key: HBASE-11482
> URL: https://issues.apache.org/jira/browse/HBASE-11482
> Project: HBase
> Issue Type: New Feature
> Reporter: Andrew Purtell
>
> A core concept of Apache Spark is the resilient distributed dataset (RDD), a
> "fault-tolerant collection of elements that can be operated on in parallel".
> One can create a RDDs referencing a dataset in any external storage system
> offering a Hadoop InputFormat, like HBase's TableInputFormat and
> TableSnapshotInputFormat.
> Insure the integration is reasonable and provides good performance.
> Add the ability to save RDDs back to HBase with a {{saveAsHBaseTable}}
> action, implicitly creating necessary schema on demand.
> Add support for {{filter}} transformations that push predicates down to the
> server as HBase filters.
> Consider supporting conversions between Scala and Java types and HBase data
> using the HBase types library.
> Consider an option to lazily and automatically produce a snapshot only when
> needed, in a coordinated way. (Concurrently executing workers may want to
> materialize a table snapshot RDD at the same time.)
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