[jira] [Updated] (SPARK-7160) Support converting DataFrames to typed RDDs.

["Michael Armbrust (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-7160?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Michael Armbrust updated SPARK-7160:
------------------------------------
            Priority: Critical  (was: Major)
    Target Version/s: 1.5.0
            Shepherd: Michael Armbrust

> Support converting DataFrames to typed RDDs.
> --------------------------------------------
>
>                 Key: SPARK-7160
>                 URL: https://issues.apache.org/jira/browse/SPARK-7160
>             Project: Spark
>          Issue Type: Sub-task
>          Components: SQL
>    Affects Versions: 1.3.1
>            Reporter: Ray Ortigas
>            Assignee: Ray Ortigas
>            Priority: Critical
>
> As a Spark user still working with RDDs, I'd like the ability to convert a DataFrame to a typed RDD.
> For example, if I've converted RDDs to DataFrames so that I could save them as Parquet or CSV files, I would like to rebuild the RDD from those files automatically rather than writing the row-to-type conversion myself.
> {code}
> val rdd0 = sc.parallelize(Seq(Food("apple", 1), Food("banana", 2), Food("cherry", 3)))
> val df0 = rdd0.toDF()
> df0.save("foods.parquet")
> val df1 = sqlContext.load("foods.parquet")
> val rdd1 = df1.toTypedRDD[Food]()
> // rdd0 and rdd1 should have the same elements
> {code}
> I originally submitted a smaller PR for spark-csv <https://github.com/databricks/spark-csv/pull/52>, but Reynold Xin suggested that converting a DataFrame to a typed RDD wasn't something specific to spark-csv.



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