val spark: SparkSession = ...
scala> :type spark.sessionState.planner
org.apache.spark.sql.execution.SparkPlanner
SparkPlanner — Spark Query Planner
SparkPlanner is a concrete Catalyst Query Planner that converts a logical plan to one or more physical plans using execution planning strategies with support for extra strategies (by means of ExperimentalMethods) and extraPlanningStrategies.
| 
 Note 
 | 
SparkPlanner is expected to plan (aka generate) at least one physical plan per logical plan.
 | 
SparkPlanner is available as planner of a SessionState.
| SparkStrategy | Description | 
|---|---|
   | 
|
Extension point for extra planning strategies  | 
|
| 
 Note 
 | 
SparkPlanner extends SparkStrategies abstract class.
 | 
Creating SparkPlanner Instance
SparkPlanner takes the following when created:
| 
 Note 
 | 
 
 
  | 
 Extension Point for Extra Planning Strategies — extraPlanningStrategies Method
extraPlanningStrategies: Seq[Strategy] = Nil
extraPlanningStrategies is an extension point to register extra planning strategies with the query planner.
| 
 Note 
 | 
extraPlanningStrategies are executed after extraStrategies.
 | 
| 
 Note 
 | 
 
 
  | 
 Collecting PlanLater Physical Operators — collectPlaceholders Method
collectPlaceholders(plan: SparkPlan): Seq[(SparkPlan, LogicalPlan)]
collectPlaceholders collects all PlanLater physical operators in the plan physical plan.
| 
 Note 
 | 
collectPlaceholders is part of QueryPlanner Contract.
 | 
 Pruning "Bad" Physical Plans — prunePlans Method
prunePlans(plans: Iterator[SparkPlan]): Iterator[SparkPlan]
prunePlans gives the input plans physical plans back (i.e. with no changes).
| 
 Note 
 | 
prunePlans is part of QueryPlanner Contract to remove somehow "bad" plans.
 | 
 Creating Physical Operator (Possibly Under FilterExec and ProjectExec Operators) — pruneFilterProject Method
pruneFilterProject(
  projectList: Seq[NamedExpression],
  filterPredicates: Seq[Expression],
  prunePushedDownFilters: Seq[Expression] => Seq[Expression],
  scanBuilder: Seq[Attribute] => SparkPlan): SparkPlan
| 
 Note 
 | 
pruneFilterProject is almost like DataSourceStrategy.pruneFilterProjectRaw.
 | 
pruneFilterProject branches off per whether it is possible to use a column pruning only (to get the right projection) and the input projectList columns of this projection are enough to evaluate all input filterPredicates filter conditions.
If so, pruneFilterProject does the following:
- 
Applies the input
scanBuilderfunction to the inputprojectListcolumns that creates a new physical operator - 
If there are Catalyst predicate expressions in the input
prunePushedDownFiltersthat cannot be pushed down,pruneFilterProjectcreates a FilterExec unary physical operator (with the unhandled predicate expressions) - 
Otherwise,
pruneFilterProjectsimply returns the physical operator 
| 
 Note 
 | 
In this case no extra ProjectExec unary physical operator is created. | 
If not (i.e. it is neither possible to use a column pruning only nor evaluate filter conditions), pruneFilterProject does the following:
- 
Applies the input
scanBuilderfunction to the projection and filtering columns that creates a new physical operator - 
Creates a FilterExec unary physical operator (with the unhandled predicate expressions if available)
 - 
Creates a ProjectExec unary physical operator with the optional
FilterExecoperator (with the scan physical operator) or simply the scan physical operator alone 
| 
 Note 
 | 
pruneFilterProject is used when HiveTableScans and InMemoryScans execution planning strategies are executed.
 |