Packages

o

com.nvidia.spark.rapids

ExplainPlan

object ExplainPlan

Linear Supertypes
AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. ExplainPlan
  2. AnyRef
  3. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

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. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  5. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native() @HotSpotIntrinsicCandidate()
  6. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  7. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  8. def explainPotentialGpuPlan(df: DataFrame, explain: String = "ALL"): String

    Looks at the CPU plan associated with the dataframe and outputs information about which parts of the query the RAPIDS Accelerator for Apache Spark could place on the GPU.

    Looks at the CPU plan associated with the dataframe and outputs information about which parts of the query the RAPIDS Accelerator for Apache Spark could place on the GPU. This only applies to the initial plan, so if running with adaptive query execution enable, it will not be able to show any changes in the plan due to that.

    This is very similar output you would get by running the query with the Rapids Accelerator enabled and with the config spark.rapids.sql.enabled enabled.

    Requires the RAPIDS Accelerator for Apache Spark jar and RAPIDS cudf jar be included in the classpath but the RAPIDS Accelerator for Apache Spark should be disabled.

    val output = com.nvidia.spark.rapids.ExplainPlan.explainPotentialGpuPlan(df)

    Calling from PySpark:

    output = sc._jvm.com.nvidia.spark.rapids.ExplainPlan.explainPotentialGpuPlan(df._jdf, "ALL")
    df

    The Spark DataFrame to get the query plan from

    explain

    If ALL returns all the explain data, otherwise just returns what does not work on the GPU. Default is ALL.

    returns

    String containing the explained plan.

    Annotations
    @throws( ... ) @throws( ... )
    Exceptions thrown

    java.lang.IllegalArgumentException if an argument is invalid or it is unable to determine the Spark version

    java.lang.IllegalStateException if the plugin gets into an invalid state while trying to process the plan or there is an unexepected exception.

  9. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  10. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  11. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  12. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  13. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  14. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  15. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  16. def toString(): String
    Definition Classes
    AnyRef → Any
  17. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  18. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  19. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Deprecated Value Members

  1. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] ) @Deprecated
    Deprecated

Inherited from AnyRef

Inherited from Any

Ungrouped