[GitHub] spark pull request #15945: [SPARK-12978][SQL] Merge unnecessary partial aggr...

[cloud-fan <gi...@git.apache.org>]

Github user cloud-fan commented on a diff in the pull request:

    https://github.com/apache/spark/pull/15945#discussion_r95782620
  
    --- Diff: sql/core/src/main/scala/org/apache/spark/sql/execution/QueryExecution.scala ---
    @@ -90,18 +92,27 @@ class QueryExecution(val sparkSession: SparkSession, val logical: LogicalPlan) {
        * Prepares a planned [[SparkPlan]] for execution by inserting shuffle operations and internal
        * row format conversions as needed.
        */
    -  protected def prepareForExecution(plan: SparkPlan): SparkPlan = {
    -    preparations.foldLeft(plan) { case (sp, rule) => rule.apply(sp) }
    -  }
    +  protected def prepareForExecution(plan: SparkPlan): SparkPlan = execute(plan)
    +
    +  private val fixedPoint = FixedPoint(sparkSession.sessionState.conf.optimizerMaxIterations)
     
       /** A sequence of rules that will be applied in order to the physical plan before execution. */
    -  protected def preparations: Seq[Rule[SparkPlan]] = Seq(
    -    python.ExtractPythonUDFs,
    -    PlanSubqueries(sparkSession),
    -    EnsureRequirements(sparkSession.sessionState.conf),
    -    CollapseCodegenStages(sparkSession.sessionState.conf),
    -    ReuseExchange(sparkSession.sessionState.conf),
    -    ReuseSubquery(sparkSession.sessionState.conf))
    +  override protected def batches: Seq[Batch] = Seq(
    --- End diff --
    
    How about we add a `PhysicalOptimizer` to do these things? then we can simply write `lazy val executedPlan: SparkPlan = physicalOptimizer.execute(sparkPlan))` instead of `lazy val executedPlan: SparkPlan = prepareForExecution(sparkPlan)`


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