Packages

class QueryExecution extends AnyRef

The primary workflow for executing relational queries using Spark. Designed to allow easy access to the intermediate phases of query execution for developers.

While this is not a public class, we should avoid changing the function names for the sake of changing them, because a lot of developers use the feature for debugging.

Linear Supertypes
AnyRef, Any
Known Subclasses
IncrementalExecution
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Instance Constructors

  1. new QueryExecution(sparkSession: SparkSession, logical: LogicalPlan, tracker: QueryPlanningTracker = new QueryPlanningTracker)

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. lazy val analyzed: LogicalPlan
  5. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  6. def assertAnalyzed(): Unit
  7. def assertSupported(): Unit
  8. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
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    Annotations
    @throws( ... ) @native()
  9. final def eq(arg0: AnyRef): Boolean
    Definition Classes
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  10. def equals(arg0: Any): Boolean
    Definition Classes
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  11. lazy val executedPlan: SparkPlan
  12. def explainString(mode: ExplainMode): String
  13. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
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    Annotations
    @throws( classOf[java.lang.Throwable] )
  14. final def getClass(): Class[_]
    Definition Classes
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    Annotations
    @native()
  15. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  16. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  17. val logical: LogicalPlan
  18. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  19. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  20. final def notifyAll(): Unit
    Definition Classes
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    Annotations
    @native()
  21. def observedMetrics: Map[String, Row]

    Get the metrics observed during the execution of the query plan.

  22. lazy val optimizedPlan: LogicalPlan
  23. def planner: SparkPlanner
    Attributes
    protected
  24. def preparations: Seq[Rule[SparkPlan]]
    Attributes
    protected
  25. def simpleString(formatted: Boolean): String
  26. def simpleString: String
  27. lazy val sparkPlan: SparkPlan
  28. val sparkSession: SparkSession
  29. def stringWithStats: String
  30. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  31. lazy val toRdd: RDD[InternalRow]

    Internal version of the RDD.

    Internal version of the RDD. Avoids copies and has no schema. Note for callers: Spark may apply various optimization including reusing object: this means the row is valid only for the iteration it is retrieved. You should avoid storing row and accessing after iteration. (Calling collect() is one of known bad usage.) If you want to store these rows into collection, please apply some converter or copy row which produces new object per iteration. Given QueryExecution is not a public class, end users are discouraged to use this: please use Dataset.rdd instead where conversion will be applied.

  32. def toString(): String
    Definition Classes
    QueryExecution → AnyRef → Any
  33. val tracker: QueryPlanningTracker
  34. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  35. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
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    Annotations
    @throws( ... )
  36. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  37. lazy val withCachedData: LogicalPlan
  38. object debug

    A special namespace for commands that can be used to debug query execution.

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