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org.apache.spark.sql.execution.python

FlatMapGroupsInPandasExec

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

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

Rows in each group are passed to the Python worker as an Arrow record batch. The Python worker turns the record batch to a pandas.DataFrame, invoke 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 group. The memory on the Java side is used to construct the record batch (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
UnaryExecNode, SparkPlan, Serializable, Serializable, Logging, QueryPlan[SparkPlan], TreeNode[SparkPlan], Product, Equals, AnyRef, Any
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Inherited
  1. FlatMapGroupsInPandasExec
  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 FlatMapGroupsInPandasExec(groupingAttributes: Seq[Attribute], func: Expression, output: Seq[Attribute], child: SparkPlan)

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 allAttributes: AttributeSeq
    Definition Classes
    QueryPlan
  5. def apply(number: Int): TreeNode[_]
    Definition Classes
    TreeNode
  6. def argString(maxFields: Int): String
    Definition Classes
    TreeNode
  7. def asCode: String
    Definition Classes
    TreeNode
  8. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  9. final lazy val canonicalized: SparkPlan
    Definition Classes
    QueryPlan
    Annotations
    @transient()
  10. val child: SparkPlan
    Definition Classes
    FlatMapGroupsInPandasExec → UnaryExecNode
  11. final def children: Seq[SparkPlan]
    Definition Classes
    UnaryExecNode → TreeNode
  12. def cleanupResources(): Unit

    Cleans up the resources used by the physical operator (if any).

    Cleans up the resources used by the physical operator (if any). In general, all the resources should be cleaned up when the task finishes but operators like SortMergeJoinExec and LimitExec may want eager cleanup to free up tight resources (e.g., memory).

    Attributes
    protected[sql]
    Definition Classes
    SparkPlan
  13. def clone(): SparkPlan
    Definition Classes
    TreeNode → AnyRef
  14. def collect[B](pf: PartialFunction[SparkPlan, B]): Seq[B]
    Definition Classes
    TreeNode
  15. def collectFirst[B](pf: PartialFunction[SparkPlan, B]): Option[B]
    Definition Classes
    TreeNode
  16. def collectLeaves(): Seq[SparkPlan]
    Definition Classes
    TreeNode
  17. def collectWithSubqueries[B](f: PartialFunction[SparkPlan, B]): Seq[B]
    Definition Classes
    QueryPlan
  18. def conf: SQLConf
    Definition Classes
    QueryPlan
  19. lazy val containsChild: Set[TreeNode[_]]
    Definition Classes
    TreeNode
  20. def copyTagsFrom(other: SparkPlan): Unit
    Attributes
    protected
    Definition Classes
    TreeNode
  21. def doCanonicalize(): SparkPlan
    Attributes
    protected
    Definition Classes
    QueryPlan
  22. def doExecute(): RDD[InternalRow]

    Produces the result of the query as an RDD[InternalRow]

    Produces the result of the query as an RDD[InternalRow]

    Overridden by concrete implementations of SparkPlan.

    Attributes
    protected
    Definition Classes
    FlatMapGroupsInPandasExec → SparkPlan
  23. def doExecuteBroadcast[T](): Broadcast[T]

    Produces the result of the query as a broadcast variable.

    Produces the result of the query as a broadcast variable.

    Overridden by concrete implementations of SparkPlan.

    Attributes
    protected[sql]
    Definition Classes
    SparkPlan
  24. def doExecuteColumnar(): RDD[ColumnarBatch]

    Produces the result of the query as an RDD[ColumnarBatch] if supportsColumnar returns true.

    Produces the result of the query as an RDD[ColumnarBatch] if supportsColumnar returns true. By convention the executor that creates a ColumnarBatch is responsible for closing it when it is no longer needed. This allows input formats to be able to reuse batches if needed.

    Attributes
    protected
    Definition Classes
    SparkPlan
  25. def doPrepare(): Unit

    Overridden by concrete implementations of SparkPlan.

    Overridden by concrete implementations of SparkPlan. It is guaranteed to run before any execute of SparkPlan. This is helpful if we want to set up some state before executing the query, e.g., BroadcastHashJoin uses it to broadcast asynchronously.

    Attributes
    protected
    Definition Classes
    SparkPlan
    Note

    prepare method has already walked down the tree, so the implementation doesn't have to call children's prepare methods. This will only be called once, protected by this.

  26. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  27. 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
  28. 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
  29. 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
  30. 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
  31. 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
  32. final def executeQuery[T](query: ⇒ T): T

    Executes a query after preparing the query and adding query plan information to created RDDs for visualization.

    Executes a query after preparing the query and adding query plan information to created RDDs for visualization.

    Attributes
    protected
    Definition Classes
    SparkPlan
  33. 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
  34. 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
  35. 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).

  36. final def expressions: Seq[Expression]
    Definition Classes
    QueryPlan
  37. def fastEquals(other: TreeNode[_]): Boolean
    Definition Classes
    TreeNode
  38. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  39. def find(f: (SparkPlan) ⇒ Boolean): Option[SparkPlan]
    Definition Classes
    TreeNode
  40. def flatMap[A](f: (SparkPlan) ⇒ TraversableOnce[A]): Seq[A]
    Definition Classes
    TreeNode
  41. def foreach(f: (SparkPlan) ⇒ Unit): Unit
    Definition Classes
    TreeNode
  42. def foreachUp(f: (SparkPlan) ⇒ Unit): Unit
    Definition Classes
    TreeNode
  43. def formattedNodeName: String
    Attributes
    protected
    Definition Classes
    QueryPlan
  44. val func: Expression
  45. def generateTreeString(depth: Int, lastChildren: Seq[Boolean], append: (String) ⇒ Unit, verbose: Boolean, prefix: String, addSuffix: Boolean, maxFields: Int, printNodeId: Boolean): Unit
    Definition Classes
    TreeNode
  46. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  47. def getTagValue[T](tag: TreeNodeTag[T]): Option[T]
    Definition Classes
    TreeNode
  48. val groupingAttributes: Seq[Attribute]
  49. def hashCode(): Int
    Definition Classes
    TreeNode → AnyRef → Any
  50. val id: Int
    Definition Classes
    SparkPlan
  51. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  52. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  53. def innerChildren: Seq[QueryPlan[_]]
    Definition Classes
    QueryPlan → TreeNode
  54. def inputSet: AttributeSet
    Definition Classes
    QueryPlan
  55. def isCanonicalizedPlan: Boolean
    Attributes
    protected
    Definition Classes
    QueryPlan
  56. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  57. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  58. def jsonFields: List[JField]
    Attributes
    protected
    Definition Classes
    TreeNode
  59. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  60. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  61. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  62. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  63. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  64. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  65. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  66. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  67. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  68. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  69. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  70. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  71. def logicalLink: Option[LogicalPlan]

    returns

    The logical plan this plan is linked to.

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

    returns

    SQLMetric for the name.

    Definition Classes
    SparkPlan
  73. 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
  74. def map[A](f: (SparkPlan) ⇒ A): Seq[A]
    Definition Classes
    TreeNode
  75. def mapChildren(f: (SparkPlan) ⇒ SparkPlan): SparkPlan
    Definition Classes
    TreeNode
  76. def mapExpressions(f: (Expression) ⇒ Expression): FlatMapGroupsInPandasExec.this.type
    Definition Classes
    QueryPlan
  77. def mapProductIterator[B](f: (Any) ⇒ B)(implicit arg0: ClassTag[B]): Array[B]
    Attributes
    protected
    Definition Classes
    TreeNode
  78. def metrics: Map[String, SQLMetric]

    returns

    All metrics containing metrics of this SparkPlan.

    Definition Classes
    SparkPlan
  79. final def missingInput: AttributeSet
    Definition Classes
    QueryPlan
  80. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  81. def nodeName: String
    Definition Classes
    TreeNode
  82. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  83. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  84. def numberedTreeString: String
    Definition Classes
    TreeNode
  85. val origin: Origin
    Definition Classes
    TreeNode
  86. def otherCopyArgs: Seq[AnyRef]
    Attributes
    protected
    Definition Classes
    TreeNode
  87. val output: Seq[Attribute]
    Definition Classes
    FlatMapGroupsInPandasExec → QueryPlan
  88. def outputOrdering: Seq[SortOrder]

    Specifies how data is ordered in each partition.

    Specifies how data is ordered in each partition.

    Definition Classes
    SparkPlan
  89. 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
    FlatMapGroupsInPandasExec → SparkPlan
  90. lazy val outputSet: AttributeSet
    Definition Classes
    QueryPlan
    Annotations
    @transient()
  91. def p(number: Int): SparkPlan
    Definition Classes
    TreeNode
  92. final def prepare(): Unit

    Prepares this SparkPlan for execution.

    Prepares this SparkPlan for execution. It's idempotent.

    Definition Classes
    SparkPlan
  93. def prepareSubqueries(): Unit

    Finds scalar subquery expressions in this plan node and starts evaluating them.

    Finds scalar subquery expressions in this plan node and starts evaluating them.

    Attributes
    protected
    Definition Classes
    SparkPlan
  94. def prettyJson: String
    Definition Classes
    TreeNode
  95. def printSchema(): Unit
    Definition Classes
    QueryPlan
  96. def producedAttributes: AttributeSet
    Definition Classes
    FlatMapGroupsInPandasExec → QueryPlan
  97. lazy val references: AttributeSet
    Definition Classes
    QueryPlan
    Annotations
    @transient()
  98. 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
    FlatMapGroupsInPandasExec → SparkPlan
  99. 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
    FlatMapGroupsInPandasExec → SparkPlan
  100. def resetMetrics(): Unit

    Resets all the metrics.

    Resets all the metrics.

    Definition Classes
    SparkPlan
  101. final def sameResult(other: SparkPlan): Boolean
    Definition Classes
    QueryPlan
  102. lazy val schema: StructType
    Definition Classes
    QueryPlan
  103. def schemaString: String
    Definition Classes
    QueryPlan
  104. final def semanticHash(): Int
    Definition Classes
    QueryPlan
  105. def setLogicalLink(logicalPlan: LogicalPlan): Unit

    Set logical plan link recursively if unset.

    Set logical plan link recursively if unset.

    Definition Classes
    SparkPlan
  106. def setTagValue[T](tag: TreeNodeTag[T], value: T): Unit
    Definition Classes
    TreeNode
  107. def simpleString(maxFields: Int): String
    Definition Classes
    QueryPlan → TreeNode
  108. def simpleStringWithNodeId(): String
    Definition Classes
    QueryPlan → TreeNode
  109. def sparkContext: SparkContext
    Attributes
    protected
    Definition Classes
    SparkPlan
  110. 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
  111. def statePrefix: String
    Attributes
    protected
    Definition Classes
    QueryPlan
  112. def stringArgs: Iterator[Any]
    Attributes
    protected
    Definition Classes
    TreeNode
  113. def subqueries: Seq[SparkPlan]
    Definition Classes
    QueryPlan
  114. def subqueriesAll: Seq[SparkPlan]
    Definition Classes
    QueryPlan
  115. 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
  116. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  117. def toJSON: String
    Definition Classes
    TreeNode
  118. def toString(): String
    Definition Classes
    TreeNode → AnyRef → Any
  119. def transform(rule: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
    Definition Classes
    TreeNode
  120. def transformAllExpressions(rule: PartialFunction[Expression, Expression]): FlatMapGroupsInPandasExec.this.type
    Definition Classes
    QueryPlan
  121. def transformDown(rule: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
    Definition Classes
    TreeNode
  122. def transformExpressions(rule: PartialFunction[Expression, Expression]): FlatMapGroupsInPandasExec.this.type
    Definition Classes
    QueryPlan
  123. def transformExpressionsDown(rule: PartialFunction[Expression, Expression]): FlatMapGroupsInPandasExec.this.type
    Definition Classes
    QueryPlan
  124. def transformExpressionsUp(rule: PartialFunction[Expression, Expression]): FlatMapGroupsInPandasExec.this.type
    Definition Classes
    QueryPlan
  125. def transformUp(rule: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
    Definition Classes
    TreeNode
  126. def treeString(append: (String) ⇒ Unit, verbose: Boolean, addSuffix: Boolean, maxFields: Int, printOperatorId: Boolean): Unit
    Definition Classes
    TreeNode
  127. final def treeString(verbose: Boolean, addSuffix: Boolean, maxFields: Int, printOperatorId: Boolean): String
    Definition Classes
    TreeNode
  128. final def treeString: String
    Definition Classes
    TreeNode
  129. def unsetTagValue[T](tag: TreeNodeTag[T]): Unit
    Definition Classes
    TreeNode
  130. 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
  131. def verboseString(maxFields: Int): String
    Definition Classes
    QueryPlan → TreeNode
  132. def verboseStringWithOperatorId(): String
    Definition Classes
    UnaryExecNode → QueryPlan
  133. def verboseStringWithSuffix(maxFields: Int): String
    Definition Classes
    TreeNode
  134. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  135. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  136. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  137. def waitForSubqueries(): Unit

    Blocks the thread until all subqueries finish evaluation and update the results.

    Blocks the thread until all subqueries finish evaluation and update the results.

    Attributes
    protected
    Definition Classes
    SparkPlan
  138. def withNewChildren(newChildren: Seq[SparkPlan]): SparkPlan
    Definition Classes
    TreeNode

Inherited from UnaryExecNode

Inherited from SparkPlan

Inherited from Serializable

Inherited from Serializable

Inherited from Logging

Inherited from QueryPlan[SparkPlan]

Inherited from TreeNode[SparkPlan]

Inherited from Product

Inherited from Equals

Inherited from AnyRef

Inherited from Any

Ungrouped