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https://issues.apache.org/jira/browse/PHOENIX-1071?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14389673#comment-14389673
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ASF GitHub Bot commented on PHOENIX-1071:
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Github user jmahonin commented on the pull request:
https://github.com/apache/phoenix/pull/59#issuecomment-88285575
Can confirm the memory settings needed adjustment on 7u76 on Linux.
Special thanks to @robdaemon who had an excellent library to work with, and
a pre-emptive thanks to @dacort for the copyrights!
My preference would be to put the RelationProvider work under a new ticket.
It's separate functionality, and although I've made a bit of headway there,
testing against the current SparkSQLContext API is yielding some bizarre
results.
It's fairly likely I'm doing something wrong, but that's a brand new API
for Spark. Most of the methods have @DeveloperAPI annotations (read: unstable),
and a number of fixes are slated for Spark SQL in 1.3.1, so I expect a bit of
churn in that area for the time being.
> Provide integration for exposing Phoenix tables as Spark RDDs
> -------------------------------------------------------------
>
> Key: PHOENIX-1071
> URL: https://issues.apache.org/jira/browse/PHOENIX-1071
> Project: Phoenix
> 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 PhoenixInputFormat and
> PhoenixOutputFormat. There could be opportunities for additional interesting
> and deep integration.
> Add the ability to save RDDs back to Phoenix with a {{saveAsPhoenixTable}}
> action, implicitly creating necessary schema on demand.
> Add support for {{filter}} transformations that push predicates to the server.
> Add a new {{select}} transformation supporting a LINQ-like DSL, for example:
> {code}
> // Count the number of different coffee varieties offered by each
> // supplier from Guatemala
> phoenixTable("coffees")
> .select(c =>
> where(c.origin == "GT"))
> .countByKey()
> .foreach(r => println(r._1 + "=" + r._2))
> {code}
> Support conversions between Scala and Java types and Phoenix table data.
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