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From marmbrus <...@git.apache.org>
Subject [GitHub] spark pull request: [SPARK-4133] [SQL] [PySpark] type conversionfo...
Date Tue, 28 Oct 2014 19:51:34 GMT
Github user marmbrus commented on a diff in the pull request:

    https://github.com/apache/spark/pull/2973#discussion_r19498469
  
    --- Diff: sql/core/src/main/scala/org/apache/spark/sql/SchemaRDD.scala ---
    @@ -428,9 +397,10 @@ class SchemaRDD(
        */
       private[sql] def collectToPython: JList[Array[Byte]] = {
         val rowSchema = StructType.fromAttributes(this.queryExecution.analyzed.output)
    +    val fields = rowSchema.fields.map(_.dataType)
    --- End diff --
    
    Nit/existing: I'd avoid creating attributes which is actually pretty expensive due to
an `AtomicLong` and use the public API for `schema`.  I think instead of these two lines you
can just do the following here and above.
    
    ```scala
    val fieldTypes = schema.fields.map(_.dataType)
    ```


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