Packages

case class MapInPandasExec(func: Expression, output: Seq[Attribute], child: SparkPlan) extends SparkPlan with UnaryExecNode with Product with Serializable

A relation produced by applying a function that takes an iterator of pandas DataFrames and outputs an iterator of pandas DataFrames.

This is somewhat similar with FlatMapGroupsInPandasExec and org.apache.spark.sql.catalyst.plans.logical.MapPartitionsInRWithArrow

Linear Supertypes
UnaryExecNode, SparkPlan, Serializable, Serializable, Logging, QueryPlan[SparkPlan], TreeNode[SparkPlan], Product, Equals, AnyRef, Any
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Inherited
  1. MapInPandasExec
  2. UnaryExecNode
  3. SparkPlan
  4. Serializable
  5. Serializable
  6. Logging
  7. QueryPlan
  8. TreeNode
  9. Product
  10. Equals
  11. AnyRef
  12. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new MapInPandasExec(func: Expression, output: Seq[Attribute], child: SparkPlan)

Value Members

  1. lazy val allAttributes: AttributeSeq
    Definition Classes
    QueryPlan
  2. def apply(number: Int): TreeNode[_]
    Definition Classes
    TreeNode
  3. def argString(maxFields: Int): String
    Definition Classes
    TreeNode
  4. def asCode: String
    Definition Classes
    TreeNode
  5. final lazy val canonicalized: SparkPlan
    Definition Classes
    QueryPlan
    Annotations
    @transient()
  6. val child: SparkPlan
    Definition Classes
    MapInPandasExec → UnaryExecNode
  7. final def children: Seq[SparkPlan]
    Definition Classes
    UnaryExecNode → TreeNode
  8. def clone(): SparkPlan
    Definition Classes
    TreeNode → AnyRef
  9. def collect[B](pf: PartialFunction[SparkPlan, B]): Seq[B]
    Definition Classes
    TreeNode
  10. def collectFirst[B](pf: PartialFunction[SparkPlan, B]): Option[B]
    Definition Classes
    TreeNode
  11. def collectLeaves(): Seq[SparkPlan]
    Definition Classes
    TreeNode
  12. def collectWithSubqueries[B](f: PartialFunction[SparkPlan, B]): Seq[B]
    Definition Classes
    QueryPlan
  13. def conf: SQLConf
    Definition Classes
    QueryPlan
  14. lazy val containsChild: Set[TreeNode[_]]
    Definition Classes
    TreeNode
  15. final def execute(): RDD[InternalRow]

    Returns the result of this query as an RDD[InternalRow] by delegating to doExecute after preparations.

    Returns the result of this query as an RDD[InternalRow] by delegating to doExecute after preparations.

    Concrete implementations of SparkPlan should override doExecute.

    Definition Classes
    SparkPlan
  16. final def executeBroadcast[T](): Broadcast[T]

    Returns the result of this query as a broadcast variable by delegating to doExecuteBroadcast after preparations.

    Returns the result of this query as a broadcast variable by delegating to doExecuteBroadcast after preparations.

    Concrete implementations of SparkPlan should override doExecuteBroadcast.

    Definition Classes
    SparkPlan
  17. def executeCollect(): Array[InternalRow]

    Runs this query returning the result as an array.

    Runs this query returning the result as an array.

    Definition Classes
    SparkPlan
  18. def executeCollectPublic(): Array[Row]

    Runs this query returning the result as an array, using external Row format.

    Runs this query returning the result as an array, using external Row format.

    Definition Classes
    SparkPlan
  19. final def executeColumnar(): RDD[ColumnarBatch]

    Returns the result of this query as an RDD[ColumnarBatch] by delegating to doColumnarExecute after preparations.

    Returns the result of this query as an RDD[ColumnarBatch] by delegating to doColumnarExecute after preparations.

    Concrete implementations of SparkPlan should override doColumnarExecute if supportsColumnar returns true.

    Definition Classes
    SparkPlan
  20. def executeTail(n: Int): Array[InternalRow]

    Runs this query returning the last n rows as an array.

    Runs this query returning the last n rows as an array.

    This is modeled after RDD.take but never runs any job locally on the driver.

    Definition Classes
    SparkPlan
  21. def executeTake(n: Int): Array[InternalRow]

    Runs this query returning the first n rows as an array.

    Runs this query returning the first n rows as an array.

    This is modeled after RDD.take but never runs any job locally on the driver.

    Definition Classes
    SparkPlan
  22. def executeToIterator(): Iterator[InternalRow]

    Runs this query returning the result as an iterator of InternalRow.

    Runs this query returning the result as an iterator of InternalRow.

    Definition Classes
    SparkPlan
    Note

    Triggers multiple jobs (one for each partition).

  23. final def expressions: Seq[Expression]
    Definition Classes
    QueryPlan
  24. def fastEquals(other: TreeNode[_]): Boolean
    Definition Classes
    TreeNode
  25. def find(f: (SparkPlan) ⇒ Boolean): Option[SparkPlan]
    Definition Classes
    TreeNode
  26. def flatMap[A](f: (SparkPlan) ⇒ TraversableOnce[A]): Seq[A]
    Definition Classes
    TreeNode
  27. def foreach(f: (SparkPlan) ⇒ Unit): Unit
    Definition Classes
    TreeNode
  28. def foreachUp(f: (SparkPlan) ⇒ Unit): Unit
    Definition Classes
    TreeNode
  29. val func: Expression
  30. def generateTreeString(depth: Int, lastChildren: Seq[Boolean], append: (String) ⇒ Unit, verbose: Boolean, prefix: String, addSuffix: Boolean, maxFields: Int, printNodeId: Boolean): Unit
    Definition Classes
    TreeNode
  31. def getTagValue[T](tag: TreeNodeTag[T]): Option[T]
    Definition Classes
    TreeNode
  32. def hashCode(): Int
    Definition Classes
    TreeNode → AnyRef → Any
  33. val id: Int
    Definition Classes
    SparkPlan
  34. def innerChildren: Seq[QueryPlan[_]]
    Definition Classes
    QueryPlan → TreeNode
  35. def inputSet: AttributeSet
    Definition Classes
    QueryPlan
  36. def logicalLink: Option[LogicalPlan]

    returns

    The logical plan this plan is linked to.

    Definition Classes
    SparkPlan
  37. def longMetric(name: String): SQLMetric

    returns

    SQLMetric for the name.

    Definition Classes
    SparkPlan
  38. def makeCopy(newArgs: Array[AnyRef]): SparkPlan

    Overridden make copy also propagates sqlContext to copied plan.

    Overridden make copy also propagates sqlContext to copied plan.

    Definition Classes
    SparkPlan → TreeNode
  39. def map[A](f: (SparkPlan) ⇒ A): Seq[A]
    Definition Classes
    TreeNode
  40. def mapChildren(f: (SparkPlan) ⇒ SparkPlan): SparkPlan
    Definition Classes
    TreeNode
  41. def mapExpressions(f: (Expression) ⇒ Expression): MapInPandasExec.this.type
    Definition Classes
    QueryPlan
  42. def metrics: Map[String, SQLMetric]

    returns

    All metrics containing metrics of this SparkPlan.

    Definition Classes
    SparkPlan
  43. final def missingInput: AttributeSet
    Definition Classes
    QueryPlan
  44. def nodeName: String
    Definition Classes
    TreeNode
  45. def numberedTreeString: String
    Definition Classes
    TreeNode
  46. val origin: Origin
    Definition Classes
    TreeNode
  47. val output: Seq[Attribute]
    Definition Classes
    MapInPandasExec → QueryPlan
  48. def outputOrdering: Seq[SortOrder]

    Specifies how data is ordered in each partition.

    Specifies how data is ordered in each partition.

    Definition Classes
    SparkPlan
  49. def outputPartitioning: Partitioning

    Specifies how data is partitioned across different nodes in the cluster.

    Specifies how data is partitioned across different nodes in the cluster.

    Definition Classes
    MapInPandasExec → SparkPlan
  50. lazy val outputSet: AttributeSet
    Definition Classes
    QueryPlan
    Annotations
    @transient()
  51. def p(number: Int): SparkPlan
    Definition Classes
    TreeNode
  52. final def prepare(): Unit

    Prepares this SparkPlan for execution.

    Prepares this SparkPlan for execution. It's idempotent.

    Definition Classes
    SparkPlan
  53. def prettyJson: String
    Definition Classes
    TreeNode
  54. def printSchema(): Unit
    Definition Classes
    QueryPlan
  55. def producedAttributes: AttributeSet
    Definition Classes
    MapInPandasExec → QueryPlan
  56. lazy val references: AttributeSet
    Definition Classes
    QueryPlan
    Annotations
    @transient()
  57. def requiredChildDistribution: Seq[Distribution]

    Specifies the data distribution requirements of all the children for this operator.

    Specifies the data distribution requirements of all the children for this operator. By default it's UnspecifiedDistribution for each child, which means each child can have any distribution.

    If an operator overwrites this method, and specifies distribution requirements(excluding UnspecifiedDistribution and BroadcastDistribution) for more than one child, Spark guarantees that the outputs of these children will have same number of partitions, so that the operator can safely zip partitions of these children's result RDDs. Some operators can leverage this guarantee to satisfy some interesting requirement, e.g., non-broadcast joins can specify HashClusteredDistribution(a,b) for its left child, and specify HashClusteredDistribution(c,d) for its right child, then it's guaranteed that left and right child are co-partitioned by a,b/c,d, which means tuples of same value are in the partitions of same index, e.g., (a=1,b=2) and (c=1,d=2) are both in the second partition of left and right child.

    Definition Classes
    SparkPlan
  58. def requiredChildOrdering: Seq[Seq[SortOrder]]

    Specifies sort order for each partition requirements on the input data for this operator.

    Specifies sort order for each partition requirements on the input data for this operator.

    Definition Classes
    SparkPlan
  59. def resetMetrics(): Unit

    Resets all the metrics.

    Resets all the metrics.

    Definition Classes
    SparkPlan
  60. final def sameResult(other: SparkPlan): Boolean
    Definition Classes
    QueryPlan
  61. lazy val schema: StructType
    Definition Classes
    QueryPlan
  62. def schemaString: String
    Definition Classes
    QueryPlan
  63. final def semanticHash(): Int
    Definition Classes
    QueryPlan
  64. def setLogicalLink(logicalPlan: LogicalPlan): Unit

    Set logical plan link recursively if unset.

    Set logical plan link recursively if unset.

    Definition Classes
    SparkPlan
  65. def setTagValue[T](tag: TreeNodeTag[T], value: T): Unit
    Definition Classes
    TreeNode
  66. def simpleString(maxFields: Int): String
    Definition Classes
    QueryPlan → TreeNode
  67. def simpleStringWithNodeId(): String
    Definition Classes
    QueryPlan → TreeNode
  68. final val sqlContext: SQLContext

    A handle to the SQL Context that was used to create this plan.

    A handle to the SQL Context that was used to create this plan. Since many operators need access to the sqlContext for RDD operations or configuration this field is automatically populated by the query planning infrastructure.

    Definition Classes
    SparkPlan
  69. def subqueries: Seq[SparkPlan]
    Definition Classes
    QueryPlan
  70. def subqueriesAll: Seq[SparkPlan]
    Definition Classes
    QueryPlan
  71. def supportsColumnar: Boolean

    Return true if this stage of the plan supports columnar execution.

    Return true if this stage of the plan supports columnar execution.

    Definition Classes
    SparkPlan
  72. def toJSON: String
    Definition Classes
    TreeNode
  73. def toString(): String
    Definition Classes
    TreeNode → AnyRef → Any
  74. def transform(rule: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
    Definition Classes
    TreeNode
  75. def transformAllExpressions(rule: PartialFunction[Expression, Expression]): MapInPandasExec.this.type
    Definition Classes
    QueryPlan
  76. def transformDown(rule: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
    Definition Classes
    TreeNode
  77. def transformExpressions(rule: PartialFunction[Expression, Expression]): MapInPandasExec.this.type
    Definition Classes
    QueryPlan
  78. def transformExpressionsDown(rule: PartialFunction[Expression, Expression]): MapInPandasExec.this.type
    Definition Classes
    QueryPlan
  79. def transformExpressionsUp(rule: PartialFunction[Expression, Expression]): MapInPandasExec.this.type
    Definition Classes
    QueryPlan
  80. def transformUp(rule: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
    Definition Classes
    TreeNode
  81. def treeString(append: (String) ⇒ Unit, verbose: Boolean, addSuffix: Boolean, maxFields: Int, printOperatorId: Boolean): Unit
    Definition Classes
    TreeNode
  82. final def treeString(verbose: Boolean, addSuffix: Boolean, maxFields: Int, printOperatorId: Boolean): String
    Definition Classes
    TreeNode
  83. final def treeString: String
    Definition Classes
    TreeNode
  84. def unsetTagValue[T](tag: TreeNodeTag[T]): Unit
    Definition Classes
    TreeNode
  85. def vectorTypes: Option[Seq[String]]

    The exact java types of the columns that are output in columnar processing mode.

    The exact java types of the columns that are output in columnar processing mode. This is a performance optimization for code generation and is optional.

    Definition Classes
    SparkPlan
  86. def verboseString(maxFields: Int): String
    Definition Classes
    QueryPlan → TreeNode
  87. def verboseStringWithOperatorId(): String
    Definition Classes
    UnaryExecNode → QueryPlan
  88. def verboseStringWithSuffix(maxFields: Int): String
    Definition Classes
    TreeNode
  89. def withNewChildren(newChildren: Seq[SparkPlan]): SparkPlan
    Definition Classes
    TreeNode