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https://issues.apache.org/jira/browse/PHOENIX-1071?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14388788#comment-14388788
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ASF GitHub Bot commented on PHOENIX-1071:
-----------------------------------------
Github user mravi commented on the pull request:
https://github.com/apache/phoenix/pull/59#issuecomment-88157968
Nice work @jmahonin . Couple of minor changes
1. JDK version in the pom.xml is 1.8. You would need to downgrade to 1.7
2. For the ProductRDDFunctions.scala file, I notice a mismatch in the
package declaration.
3. Would be ideal if we could have a scala file say PhoenixSparkContext
that merges the functionality you have written in ProductRDDFunctions and
SparkContextFunctions .
4. Renaming SparkSqlContextFunctions to just PhoenixSparkSqlContext to make
easier for end users.
5. The build goes through fine but when I try to run the PhoenixRDDTest
from a ScalaIDE , I keep getting errors. It could be more of a IDE thing which
i will fix and get back on tests results.
Good to haves
1. A Java friendly version of the PhoenixSparkContext and
PhoenixSparkSqlContext classes for a easier adoption for java folks ( like me
:) )
2. Extend the org.apache.spark.sql.sources.RelationProvider and have
PhoenixDatasource.
> 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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