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org.apache.spark.sql.execution.python

FlatMapCoGroupsInPandasExec

case class FlatMapCoGroupsInPandasExec(leftGroup: Seq[Attribute], rightGroup: Seq[Attribute], func: Expression, output: Seq[Attribute], left: SparkPlan, right: SparkPlan) extends SparkPlan with BinaryExecNode with Product with Serializable

Physical node for org.apache.spark.sql.catalyst.plans.logical.FlatMapCoGroupsInPandas

The input dataframes are first Cogrouped. Rows from each side of the cogroup are passed to the Python worker via Arrow. As each side of the cogroup may have a different schema we send every group in its own Arrow stream. The Python worker turns the resulting record batches to pandas.DataFrames, invokes the user-defined function, and passes the resulting pandas.DataFrame as an Arrow record batch. Finally, each record batch is turned to Iterator[InternalRow] using ColumnarBatch.

Note on memory usage: Both the Python worker and the Java executor need to have enough memory to hold the largest cogroup. The memory on the Java side is used to construct the record batches (off heap memory). The memory on the Python side is used for holding the pandas.DataFrame. It's possible to further split one group into multiple record batches to reduce the memory footprint on the Java side, this is left as future work.

Linear Supertypes
BinaryExecNode, SparkPlan, Serializable, Serializable, Logging, QueryPlan[SparkPlan], TreeNode[SparkPlan], Product, Equals, AnyRef, Any
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Inherited
  1. FlatMapCoGroupsInPandasExec
  2. BinaryExecNode
  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 FlatMapCoGroupsInPandasExec(leftGroup: Seq[Attribute], rightGroup: Seq[Attribute], func: Expression, output: Seq[Attribute], left: SparkPlan, right: 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. final def children: Seq[SparkPlan]
    Definition Classes
    BinaryExecNode → TreeNode
  7. def clone(): SparkPlan
    Definition Classes
    TreeNode → AnyRef
  8. def collect[B](pf: PartialFunction[SparkPlan, B]): Seq[B]
    Definition Classes
    TreeNode
  9. def collectFirst[B](pf: PartialFunction[SparkPlan, B]): Option[B]
    Definition Classes
    TreeNode
  10. def collectLeaves(): Seq[SparkPlan]
    Definition Classes
    TreeNode
  11. def collectWithSubqueries[B](f: PartialFunction[SparkPlan, B]): Seq[B]
    Definition Classes
    QueryPlan
  12. def conf: SQLConf
    Definition Classes
    QueryPlan
  13. lazy val containsChild: Set[TreeNode[_]]
    Definition Classes
    TreeNode
  14. 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
  15. 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
  16. 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
  17. 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
  18. 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
  19. 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
  20. 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
  21. 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).

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

    returns

    The logical plan this plan is linked to.

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

    returns

    SQLMetric for the name.

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

    returns

    All metrics containing metrics of this SparkPlan.

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

    Specifies how data is ordered in each partition.

    Specifies how data is ordered in each partition.

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

    Prepares this SparkPlan for execution.

    Prepares this SparkPlan for execution. It's idempotent.

    Definition Classes
    SparkPlan
  54. def prettyJson: String
    Definition Classes
    TreeNode
  55. def printSchema(): Unit
    Definition Classes
    QueryPlan
  56. def producedAttributes: AttributeSet
    Definition Classes
    FlatMapCoGroupsInPandasExec → QueryPlan
  57. lazy val references: AttributeSet
    Definition Classes
    QueryPlan
    Annotations
    @transient()
  58. 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
    FlatMapCoGroupsInPandasExecSparkPlan
  59. 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
    FlatMapCoGroupsInPandasExecSparkPlan
  60. def resetMetrics(): Unit

    Resets all the metrics.

    Resets all the metrics.

    Definition Classes
    SparkPlan
  61. val right: SparkPlan
  62. val rightGroup: Seq[Attribute]
  63. final def sameResult(other: SparkPlan): Boolean
    Definition Classes
    QueryPlan
  64. lazy val schema: StructType
    Definition Classes
    QueryPlan
  65. def schemaString: String
    Definition Classes
    QueryPlan
  66. final def semanticHash(): Int
    Definition Classes
    QueryPlan
  67. def setLogicalLink(logicalPlan: LogicalPlan): Unit

    Set logical plan link recursively if unset.

    Set logical plan link recursively if unset.

    Definition Classes
    SparkPlan
  68. def setTagValue[T](tag: TreeNodeTag[T], value: T): Unit
    Definition Classes
    TreeNode
  69. def simpleString(maxFields: Int): String
    Definition Classes
    QueryPlan → TreeNode
  70. def simpleStringWithNodeId(): String
    Definition Classes
    QueryPlan → TreeNode
  71. 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
  72. def subqueries: Seq[SparkPlan]
    Definition Classes
    QueryPlan
  73. def subqueriesAll: Seq[SparkPlan]
    Definition Classes
    QueryPlan
  74. 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
  75. def toJSON: String
    Definition Classes
    TreeNode
  76. def toString(): String
    Definition Classes
    TreeNode → AnyRef → Any
  77. def transform(rule: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
    Definition Classes
    TreeNode
  78. def transformAllExpressions(rule: PartialFunction[Expression, Expression]): FlatMapCoGroupsInPandasExec.this.type
    Definition Classes
    QueryPlan
  79. def transformDown(rule: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
    Definition Classes
    TreeNode
  80. def transformExpressions(rule: PartialFunction[Expression, Expression]): FlatMapCoGroupsInPandasExec.this.type
    Definition Classes
    QueryPlan
  81. def transformExpressionsDown(rule: PartialFunction[Expression, Expression]): FlatMapCoGroupsInPandasExec.this.type
    Definition Classes
    QueryPlan
  82. def transformExpressionsUp(rule: PartialFunction[Expression, Expression]): FlatMapCoGroupsInPandasExec.this.type
    Definition Classes
    QueryPlan
  83. def transformUp(rule: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
    Definition Classes
    TreeNode
  84. def treeString(append: (String) ⇒ Unit, verbose: Boolean, addSuffix: Boolean, maxFields: Int, printOperatorId: Boolean): Unit
    Definition Classes
    TreeNode
  85. final def treeString(verbose: Boolean, addSuffix: Boolean, maxFields: Int, printOperatorId: Boolean): String
    Definition Classes
    TreeNode
  86. final def treeString: String
    Definition Classes
    TreeNode
  87. def unsetTagValue[T](tag: TreeNodeTag[T]): Unit
    Definition Classes
    TreeNode
  88. 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
  89. def verboseString(maxFields: Int): String
    Definition Classes
    QueryPlan → TreeNode
  90. def verboseStringWithOperatorId(): String
    Definition Classes
    BinaryExecNode → QueryPlan
  91. def verboseStringWithSuffix(maxFields: Int): String
    Definition Classes
    TreeNode
  92. def withNewChildren(newChildren: Seq[SparkPlan]): SparkPlan
    Definition Classes
    TreeNode