Packages

c

com.nvidia.spark.rapids

GpuReplicateRows

case class GpuReplicateRows(children: Seq[Expression]) extends Expression with GpuGenerator with ShimExpression with Product with Serializable

Linear Supertypes
Serializable, Serializable, ShimExpression, GpuGenerator, GpuUnevaluable, GpuExpression, Expression, TreeNode[Expression], Product, Equals, AnyRef, Any
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Inherited
  1. GpuReplicateRows
  2. Serializable
  3. Serializable
  4. ShimExpression
  5. GpuGenerator
  6. GpuUnevaluable
  7. GpuExpression
  8. Expression
  9. TreeNode
  10. Product
  11. Equals
  12. AnyRef
  13. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new GpuReplicateRows(children: Seq[Expression])

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. def apply(number: Int): TreeNode[_]
    Definition Classes
    TreeNode
  5. def argString(maxFields: Int): String
    Definition Classes
    TreeNode
  6. def asCode: String
    Definition Classes
    TreeNode
  7. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  8. lazy val canonicalized: Expression
    Definition Classes
    GpuExpression → Expression
  9. def checkInputDataTypes(): TypeCheckResult
    Definition Classes
    Expression
  10. val children: Seq[Expression]
    Definition Classes
    GpuReplicateRows → TreeNode
  11. def childrenResolved: Boolean
    Definition Classes
    Expression
  12. def clone(): Expression
    Definition Classes
    TreeNode → AnyRef
  13. def collect[B](pf: PartialFunction[Expression, B]): Seq[B]
    Definition Classes
    TreeNode
  14. def collectFirst[B](pf: PartialFunction[Expression, B]): Option[B]
    Definition Classes
    TreeNode
  15. def collectLeaves(): Seq[Expression]
    Definition Classes
    TreeNode
  16. final def columnarEval(batch: ColumnarBatch): GpuColumnVector

    Returns the result of evaluating this expression on the entire ColumnarBatch.

    Returns the result of evaluating this expression on the entire ColumnarBatch. The result of calling this is a GpuColumnVector.

    By convention any GpuColumnVector returned by columnarEval is owned by the caller and will need to be closed by them. This can happen by putting it into a ColumnarBatch and closing the batch or by closing the vector directly if it is a temporary value.

    Definition Classes
    GpuUnevaluable → GpuExpression
  17. final def columnarEvalAny(batch: ColumnarBatch): Any

    Returns the result of evaluating this expression on the entire ColumnarBatch.

    Returns the result of evaluating this expression on the entire ColumnarBatch. The result of calling this may be a single GpuColumnVector or a scalar value. Scalar values typically happen if they are a part of the expression i.e. col("a") + 100. In this case the 100 is a literal that Add would have to be able to handle.

    By convention any AutoCloseable returned by columnarEvalAny is owned by the caller and will need to be closed by them.

    Definition Classes
    GpuUnevaluable → GpuExpression
  18. lazy val containsChild: Set[TreeNode[_]]
    Definition Classes
    TreeNode
  19. def convertToAst(numFirstTableColumns: Int): AstExpression

    Build an equivalent representation of this expression in a cudf AST.

    Build an equivalent representation of this expression in a cudf AST.

    numFirstTableColumns

    number of columns in the leftmost input table. Spark places the columns of all inputs in a single sequence, while cudf AST uses an explicit table reference to make column indices unique. This parameter helps translate input column references from Spark's single sequence into cudf's separate sequences.

    returns

    top node of the equivalent AST

    Definition Classes
    GpuExpression
  20. def copyTagsFrom(other: Expression): Unit
    Definition Classes
    TreeNode
  21. def dataType: DataType
    Definition Classes
    GpuGenerator → Expression
  22. lazy val deterministic: Boolean
    Definition Classes
    Expression
  23. def disableCoalesceUntilInput(): Boolean

    Override this if your expression cannot allow combining of data from multiple files into a single batch before it operates on them.

    Override this if your expression cannot allow combining of data from multiple files into a single batch before it operates on them. These are for things like getting the input file name. Which for spark is stored in a thread local variable which means we have to jump through some hoops to make this work.

    Definition Classes
    GpuExpression
  24. def disableTieredProjectCombine: Boolean

    If this returns true then tiered project will stop looking to combine expressions when this is seen.

    If this returns true then tiered project will stop looking to combine expressions when this is seen.

    Definition Classes
    GpuExpression
  25. final def doGenCode(ctx: CodegenContext, ev: ExprCode): ExprCode
    Definition Classes
    GpuExpression → Expression
  26. def elementSchema: StructType

    The output element schema.

    The output element schema.

    Definition Classes
    GpuReplicateRows → GpuGenerator
  27. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  28. final def eval(input: InternalRow = null): Any
    Definition Classes
    GpuExpression → Expression
  29. def fastEquals(other: TreeNode[_]): Boolean
    Definition Classes
    TreeNode
  30. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  31. def find(f: (Expression) ⇒ Boolean): Option[Expression]
    Definition Classes
    TreeNode
  32. def fixedLenLazyArrayGenerate(inputIterator: Iterator[ColumnarBatch], boundLazyProjectList: Seq[Expression], boundOthersProjectList: Seq[Expression], outputSchema: Array[DataType], outer: Boolean, numOutputRows: GpuMetric, numOutputBatches: GpuMetric, opTime: GpuMetric): Iterator[ColumnarBatch]

    Optimized lazy generation interface which is specialized for fixed length array input.

    Optimized lazy generation interface which is specialized for fixed length array input.

    For some generators (like explode), it is possible to improve performance through lazy evaluation when input schema is fixed length array.

    inputIterator

    input iterator from child plan

    boundLazyProjectList

    lazy expressions bounded with child outputs

    boundOthersProjectList

    other required expressions bounded with child outputs

    outputSchema

    result schema of GpuGenerateExec

    outer

    when true, each input row will be output at least once, even if the output of the given generator is empty.

    numOutputRows

    Gpu spark metric of output rows

    numOutputBatches

    Gpu spark metric of output batches

    opTime

    Gpu spark metric of time on GPU by GpuGenerateExec

    returns

    result iterator

    Definition Classes
    GpuGenerator
  33. def fixedLenLazyExpressions: Seq[Expression]

    Extract lazy expressions from generator if exists.

    Extract lazy expressions from generator if exists.

    This is a specialized method for GPU runtime, which is called by GpuGenerateExec to determine whether current generation plan can be executed with optimized lazy array generation or not.

    returns

    fixed length lazy expressions for generation. Nil value means no lazy expressions to extract, which indicates fixed length lazy array generation is unavailable.

    Definition Classes
    GpuGenerator
  34. def flatArguments: Iterator[Any]
    Attributes
    protected
    Definition Classes
    Expression
  35. def flatMap[A](f: (Expression) ⇒ TraversableOnce[A]): Seq[A]
    Definition Classes
    TreeNode
  36. def foldable: Boolean
    Definition Classes
    GpuGenerator → Expression
  37. def foreach(f: (Expression) ⇒ Unit): Unit
    Definition Classes
    TreeNode
  38. def foreachUp(f: (Expression) ⇒ Unit): Unit
    Definition Classes
    TreeNode
  39. def genCode(ctx: CodegenContext): ExprCode
    Definition Classes
    Expression
  40. def generate(inputBatch: ColumnarBatch, generatorOffset: Int, outer: Boolean): ColumnarBatch

    Apply generator to produce result ColumnarBatch from input batch.

    Apply generator to produce result ColumnarBatch from input batch.

    This is a specialized method for GPU runtime, which is called by GpuGenerateExec who owns the generator. The reason of creating a new method rather than implementing columnarEval is that generator is an integrated Table transformer instead of column transformer in terms of cuDF.

    inputBatch

    projected input data, which ensures appending columns are ahead of generators' inputs. So, generators can distinguish them with an offset.

    generatorOffset

    column offset of generator's input columns in inputBatch

    outer

    when true, each input row will be output at least once, even if the output of the given generator is empty.

    returns

    result ColumnarBatch

    Definition Classes
    GpuReplicateRows → GpuGenerator
  41. def generateTreeString(depth: Int, lastChildren: Seq[Boolean], append: (String) ⇒ Unit, verbose: Boolean, prefix: String, addSuffix: Boolean, maxFields: Int, printNodeId: Boolean, indent: Int): Unit
    Definition Classes
    TreeNode
  42. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  43. def getTagValue[T](tag: TreeNodeTag[T]): Option[T]
    Definition Classes
    TreeNode
  44. def hasSideEffects: Boolean

    Could evaluating this expression cause side-effects, such as throwing an exception?

    Could evaluating this expression cause side-effects, such as throwing an exception?

    Definition Classes
    GpuExpression
  45. def hashCode(): Int
    Definition Classes
    TreeNode → AnyRef → Any
  46. def innerChildren: Seq[TreeNode[_]]
    Definition Classes
    TreeNode
  47. def inputSplitIndices(inputBatch: ColumnarBatch, generatorOffset: Int, outer: Boolean, targetSizeBytes: Long, maxRows: Int = Int.MaxValue): Array[Int]

    Compute split indices for generator's input batches.

    Compute split indices for generator's input batches.

    This is a specialized method for GPU runtime, which is called by GpuGenerateExec to split up input batches to reduce total memory cost during generating. It is necessary because most of generators may produce multiple records for each input record, which make output batch size much larger than input size.

    inputBatch

    projected input data, which ensures appending columns are ahead of generators' inputs. So, generators can distinguish them with an offset.

    generatorOffset

    column offset of generator's input columns in inputBatch

    outer

    when true, each input row will be output at least once, even if the output of the given generator is empty.

    targetSizeBytes

    the target number of bytes for a GPU batch, one of RapidsConf

    maxRows

    the target number of rows for a GPU batch, exposed for testing purposes.

    returns

    split indices of input batch

    Definition Classes
    GpuReplicateRows → GpuGenerator
  48. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  49. def jsonFields: List[JField]
    Attributes
    protected
    Definition Classes
    TreeNode
  50. def makeCopy(newArgs: Array[AnyRef]): Expression
    Definition Classes
    TreeNode
  51. def map[A](f: (Expression) ⇒ A): Seq[A]
    Definition Classes
    TreeNode
  52. def mapChildren(f: (Expression) ⇒ Expression): Expression
    Definition Classes
    TreeNode
  53. def mapProductIterator[B](f: (Any) ⇒ B)(implicit arg0: ClassTag[B]): Array[B]
    Attributes
    protected
    Definition Classes
    TreeNode
  54. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  55. def nodeName: String
    Definition Classes
    TreeNode
  56. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  57. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  58. def nullable: Boolean
    Definition Classes
    GpuGenerator → Expression
  59. def numberedTreeString: String
    Definition Classes
    TreeNode
  60. val origin: Origin
    Definition Classes
    TreeNode
  61. def otherCopyArgs: Seq[AnyRef]
    Attributes
    protected
    Definition Classes
    TreeNode
  62. def p(number: Int): Expression
    Definition Classes
    TreeNode
  63. def prettyJson: String
    Definition Classes
    TreeNode
  64. def prettyName: String
    Definition Classes
    Expression
  65. def references: AttributeSet
    Definition Classes
    Expression
  66. lazy val resolved: Boolean
    Definition Classes
    Expression
  67. lazy val retryable: Boolean

    true means this expression can be used inside a retry block, otherwise false.

    true means this expression can be used inside a retry block, otherwise false. An expression is retryable when

    • it is deterministic, or
    • when being non-deterministic, it is a Retryable and its children are all retryable.
    Definition Classes
    GpuExpression
  68. val selfNonDeterministic: Boolean

    Whether an expression itself is non-deterministic when its "deterministic" is false, no matter whether it has any non-deterministic children.

    Whether an expression itself is non-deterministic when its "deterministic" is false, no matter whether it has any non-deterministic children. An expression is actually a tree, and deterministic being false means there is at least one tree node is non-deterministic, but we need to know the exact nodes which are non-deterministic to check if it implements the Retryable.

    Default to false because Spark checks only children by default in Expression. So it is non-deterministic iff it has non-deterministic children.

    NOTE When overriding "deterministic", this should be taken care of.

    Definition Classes
    GpuExpression
  69. def semanticEquals(other: Expression): Boolean
    Definition Classes
    Expression
  70. def semanticHash(): Int
    Definition Classes
    Expression
  71. def setTagValue[T](tag: TreeNodeTag[T], value: T): Unit
    Definition Classes
    TreeNode
  72. def simpleString(maxFields: Int): String
    Definition Classes
    Expression → TreeNode
  73. def simpleStringWithNodeId(): String
    Definition Classes
    Expression → TreeNode
  74. def sql: String
    Definition Classes
    Expression
  75. def stringArgs: Iterator[Any]
    Attributes
    protected
    Definition Classes
    TreeNode
  76. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  77. def toJSON: String
    Definition Classes
    TreeNode
  78. def toString(): String
    Definition Classes
    Expression → TreeNode → AnyRef → Any
  79. def transform(rule: PartialFunction[Expression, Expression]): Expression
    Definition Classes
    TreeNode
  80. def transformDown(rule: PartialFunction[Expression, Expression]): Expression
    Definition Classes
    TreeNode
  81. def transformUp(rule: PartialFunction[Expression, Expression]): Expression
    Definition Classes
    TreeNode
  82. def treeString(append: (String) ⇒ Unit, verbose: Boolean, addSuffix: Boolean, maxFields: Int, printOperatorId: Boolean): Unit
    Definition Classes
    TreeNode
  83. final def treeString(verbose: Boolean, addSuffix: Boolean, maxFields: Int, printOperatorId: Boolean): String
    Definition Classes
    TreeNode
  84. final def treeString: String
    Definition Classes
    TreeNode
  85. def unsetTagValue[T](tag: TreeNodeTag[T]): Unit
    Definition Classes
    TreeNode
  86. final def verboseString(maxFields: Int): String
    Definition Classes
    Expression → TreeNode
  87. def verboseStringWithSuffix(maxFields: Int): String
    Definition Classes
    TreeNode
  88. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  89. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  90. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  91. def withNewChildren(newChildren: Seq[Expression]): Expression
    Definition Classes
    TreeNode

Inherited from Serializable

Inherited from Serializable

Inherited from ShimExpression

Inherited from GpuGenerator

Inherited from GpuUnevaluable

Inherited from GpuExpression

Inherited from Expression

Inherited from TreeNode[Expression]

Inherited from Product

Inherited from Equals

Inherited from AnyRef

Inherited from Any

Ungrouped