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From davies <...@git.apache.org>
Subject [GitHub] spark pull request: [SPARK-13671] [SQL] Use different physical pla...
Date Sat, 05 Mar 2016 08:13:47 GMT
Github user davies commented on a diff in the pull request:

    https://github.com/apache/spark/pull/11514#discussion_r55117715
  
    --- Diff: sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala ---
    @@ -101,15 +101,69 @@ private[sql] case class LogicalRDD(
     private[sql] case class PhysicalRDD(
         output: Seq[Attribute],
         rdd: RDD[InternalRow],
    -    override val nodeName: String,
    -    override val metadata: Map[String, String] = Map.empty,
    -    isUnsafeRow: Boolean = false,
    -    override val outputPartitioning: Partitioning = UnknownPartitioning(0))
    +    override val nodeName: String) extends LeafNode {
    +
    +  private[sql] override lazy val metrics = Map(
    +    "numOutputRows" -> SQLMetrics.createLongMetric(sparkContext, "number of output
rows"))
    +
    +  protected override def doExecute(): RDD[InternalRow] = {
    +    val numOutputRows = longMetric("numOutputRows")
    +    rdd.mapPartitionsInternal { iter =>
    +      val proj = UnsafeProjection.create(schema)
    +      iter.map { r =>
    +        numOutputRows += 1
    +        proj(r)
    +      }
    +    }
    +  }
    +
    +  override def simpleString: String = {
    +    s"RDD $nodeName${output.mkString("[", ",", "]")}"
    +  }
    +}
    --- End diff --
    
    If a partitioning is UnknownPartitioning, the number is meaningless, I think.


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