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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