Packages

case class RDDScanExec(output: Seq[Attribute], rdd: RDD[InternalRow], name: String, outputPartitioning: Partitioning = UnknownPartitioning(0), outputOrdering: Seq[SortOrder] = Nil) extends SparkPlan with LeafExecNode with InputRDDCodegen with Product with Serializable

Physical plan node for scanning data from an RDD of InternalRow.

Linear Supertypes
InputRDDCodegen, CodegenSupport, LeafExecNode, SparkPlan, Serializable, Serializable, Logging, QueryPlan[SparkPlan], TreeNode[SparkPlan], Product, Equals, AnyRef, Any
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Inherited
  1. RDDScanExec
  2. InputRDDCodegen
  3. CodegenSupport
  4. LeafExecNode
  5. SparkPlan
  6. Serializable
  7. Serializable
  8. Logging
  9. QueryPlan
  10. TreeNode
  11. Product
  12. Equals
  13. AnyRef
  14. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new RDDScanExec(output: Seq[Attribute], rdd: RDD[InternalRow], name: String, outputPartitioning: Partitioning = UnknownPartitioning(0), outputOrdering: Seq[SortOrder] = Nil)

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. def canCheckLimitNotReached: Boolean

    Check if the node is supposed to produce limit not reached checks.

    Check if the node is supposed to produce limit not reached checks.

    Attributes
    protected
    Definition Classes
    CodegenSupport
  10. final lazy val canonicalized: SparkPlan
    Definition Classes
    QueryPlan
    Annotations
    @transient()
  11. final def children: Seq[SparkPlan]
    Definition Classes
    LeafExecNode → 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. final def consume(ctx: CodegenContext, outputVars: Seq[ExprCode], row: String = null): String

    Consume the generated columns or row from current SparkPlan, call its parent's doConsume().

    Consume the generated columns or row from current SparkPlan, call its parent's doConsume().

    Note that outputVars and row can't both be null.

    Definition Classes
    CodegenSupport
  20. lazy val containsChild: Set[TreeNode[_]]
    Definition Classes
    TreeNode
  21. def copyTagsFrom(other: SparkPlan): Unit
    Attributes
    protected
    Definition Classes
    TreeNode
  22. val createUnsafeProjection: Boolean
    Attributes
    protected
    Definition Classes
    RDDScanExecInputRDDCodegen
  23. def doCanonicalize(): SparkPlan
    Attributes
    protected
    Definition Classes
    QueryPlan
  24. def doConsume(ctx: CodegenContext, input: Seq[ExprCode], row: ExprCode): String

    Generate the Java source code to process the rows from child SparkPlan.

    Generate the Java source code to process the rows from child SparkPlan. This should only be called from consume.

    This should be override by subclass to support codegen.

    Note: The operator should not assume the existence of an outer processing loop, which it can jump from with "continue;"!

    For example, filter could generate this: # code to evaluate the predicate expression, result is isNull1 and value2 if (!isNull1 && value2) { # call consume(), which will call parent.doConsume() }

    Note: A plan can either consume the rows as UnsafeRow (row), or a list of variables (input). When consuming as a listing of variables, the code to produce the input is already generated and CodegenContext.currentVars is already set. When consuming as UnsafeRow, implementations need to put row.code in the generated code and set CodegenContext.INPUT_ROW manually. Some plans may need more tweaks as they have different inputs(join build side, aggregate buffer, etc.), or other special cases.

    Definition Classes
    CodegenSupport
  25. 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
    RDDScanExecSparkPlan
  26. 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
  27. 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
  28. 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.

  29. def doProduce(ctx: CodegenContext): String

    Generate the Java source code to process, should be overridden by subclass to support codegen.

    Generate the Java source code to process, should be overridden by subclass to support codegen.

    doProduce() usually generate the framework, for example, aggregation could generate this:

    if (!initialized) { # create a hash map, then build the aggregation hash map # call child.produce() initialized = true; } while (hashmap.hasNext()) { row = hashmap.next(); # build the aggregation results # create variables for results # call consume(), which will call parent.doConsume() if (shouldStop()) return; }

    Definition Classes
    InputRDDCodegenCodegenSupport
  30. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  31. def evaluateNondeterministicVariables(attributes: Seq[Attribute], variables: Seq[ExprCode], expressions: Seq[NamedExpression]): String

    Returns source code to evaluate the variables for non-deterministic expressions, and clear the code of evaluated variables, to prevent them to be evaluated twice.

    Returns source code to evaluate the variables for non-deterministic expressions, and clear the code of evaluated variables, to prevent them to be evaluated twice.

    Attributes
    protected
    Definition Classes
    CodegenSupport
  32. def evaluateRequiredVariables(attributes: Seq[Attribute], variables: Seq[ExprCode], required: AttributeSet): String

    Returns source code to evaluate the variables for required attributes, and clear the code of evaluated variables, to prevent them to be evaluated twice.

    Returns source code to evaluate the variables for required attributes, and clear the code of evaluated variables, to prevent them to be evaluated twice.

    Attributes
    protected
    Definition Classes
    CodegenSupport
  33. def evaluateVariables(variables: Seq[ExprCode]): String

    Returns source code to evaluate all the variables, and clear the code of them, to prevent them to be evaluated twice.

    Returns source code to evaluate all the variables, and clear the code of them, to prevent them to be evaluated twice.

    Attributes
    protected
    Definition Classes
    CodegenSupport
  34. 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
  35. 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
  36. 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
  37. 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
  38. 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
  39. 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
  40. 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
  41. 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
  42. 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).

  43. final def expressions: Seq[Expression]
    Definition Classes
    QueryPlan
  44. def fastEquals(other: TreeNode[_]): Boolean
    Definition Classes
    TreeNode
  45. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  46. def find(f: (SparkPlan) ⇒ Boolean): Option[SparkPlan]
    Definition Classes
    TreeNode
  47. def flatMap[A](f: (SparkPlan) ⇒ TraversableOnce[A]): Seq[A]
    Definition Classes
    TreeNode
  48. def foreach(f: (SparkPlan) ⇒ Unit): Unit
    Definition Classes
    TreeNode
  49. def foreachUp(f: (SparkPlan) ⇒ Unit): Unit
    Definition Classes
    TreeNode
  50. def formattedNodeName: String
    Attributes
    protected
    Definition Classes
    QueryPlan
  51. def generateTreeString(depth: Int, lastChildren: Seq[Boolean], append: (String) ⇒ Unit, verbose: Boolean, prefix: String, addSuffix: Boolean, maxFields: Int, printNodeId: Boolean): Unit
    Definition Classes
    TreeNode
  52. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  53. def getTagValue[T](tag: TreeNodeTag[T]): Option[T]
    Definition Classes
    TreeNode
  54. def hashCode(): Int
    Definition Classes
    TreeNode → AnyRef → Any
  55. val id: Int
    Definition Classes
    SparkPlan
  56. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  57. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  58. def innerChildren: Seq[QueryPlan[_]]
    Definition Classes
    QueryPlan → TreeNode
  59. def inputRDD: RDD[InternalRow]
    Definition Classes
    RDDScanExecInputRDDCodegen
  60. def inputRDDs(): Seq[RDD[InternalRow]]

    Returns all the RDDs of InternalRow which generates the input rows.

    Returns all the RDDs of InternalRow which generates the input rows.

    Definition Classes
    InputRDDCodegenCodegenSupport
    Note

    Right now we support up to two RDDs

  61. def inputSet: AttributeSet
    Definition Classes
    QueryPlan
  62. def isCanonicalizedPlan: Boolean
    Attributes
    protected
    Definition Classes
    QueryPlan
  63. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  64. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  65. def jsonFields: List[JField]
    Attributes
    protected
    Definition Classes
    TreeNode
  66. def limitNotReachedChecks: Seq[String]

    A sequence of checks which evaluate to true if the downstream Limit operators have not received enough records and reached the limit.

    A sequence of checks which evaluate to true if the downstream Limit operators have not received enough records and reached the limit. If current node is a data producing node, it can leverage this information to stop producing data and complete the data flow earlier. Common data producing nodes are leaf nodes like Range and Scan, and blocking nodes like Sort and Aggregate. These checks should be put into the loop condition of the data producing loop.

    Definition Classes
    CodegenSupport
  67. final def limitNotReachedCond: String

    A helper method to generate the data producing loop condition according to the limit-not-reached checks.

    A helper method to generate the data producing loop condition according to the limit-not-reached checks.

    Definition Classes
    CodegenSupport
  68. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  69. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  70. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  71. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  72. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  73. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  74. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  75. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  76. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  77. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  78. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  79. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  80. def logicalLink: Option[LogicalPlan]

    returns

    The logical plan this plan is linked to.

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

    returns

    SQLMetric for the name.

    Definition Classes
    SparkPlan
  82. 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
  83. def map[A](f: (SparkPlan) ⇒ A): Seq[A]
    Definition Classes
    TreeNode
  84. def mapChildren(f: (SparkPlan) ⇒ SparkPlan): SparkPlan
    Definition Classes
    TreeNode
  85. def mapExpressions(f: (Expression) ⇒ Expression): RDDScanExec.this.type
    Definition Classes
    QueryPlan
  86. def mapProductIterator[B](f: (Any) ⇒ B)(implicit arg0: ClassTag[B]): Array[B]
    Attributes
    protected
    Definition Classes
    TreeNode
  87. def metricTerm(ctx: CodegenContext, name: String): String

    Creates a metric using the specified name.

    Creates a metric using the specified name.

    returns

    name of the variable representing the metric

    Definition Classes
    CodegenSupport
  88. lazy val metrics: Map[String, SQLMetric]

    returns

    All metrics containing metrics of this SparkPlan.

    Definition Classes
    RDDScanExecSparkPlan
  89. final def missingInput: AttributeSet
    Definition Classes
    QueryPlan
  90. val name: String
  91. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  92. def needCopyResult: Boolean

    Whether or not the result rows of this operator should be copied before putting into a buffer.

    Whether or not the result rows of this operator should be copied before putting into a buffer.

    If any operator inside WholeStageCodegen generate multiple rows from a single row (for example, Join), this should be true.

    If an operator starts a new pipeline, this should be false.

    Definition Classes
    CodegenSupport
  93. def needStopCheck: Boolean

    Whether or not the children of this operator should generate a stop check when consuming input rows.

    Whether or not the children of this operator should generate a stop check when consuming input rows. This is used to suppress shouldStop() in a loop of WholeStageCodegen.

    This should be false if an operator starts a new pipeline, which means it consumes all rows produced by children but doesn't output row to buffer by calling append(), so the children don't require shouldStop() in the loop of producing rows.

    Definition Classes
    CodegenSupport
  94. val nodeName: String
    Definition Classes
    RDDScanExec → TreeNode
  95. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  96. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  97. def numberedTreeString: String
    Definition Classes
    TreeNode
  98. val origin: Origin
    Definition Classes
    TreeNode
  99. def otherCopyArgs: Seq[AnyRef]
    Attributes
    protected
    Definition Classes
    TreeNode
  100. val output: Seq[Attribute]
    Definition Classes
    RDDScanExec → QueryPlan
  101. val outputOrdering: Seq[SortOrder]

    Specifies how data is ordered in each partition.

    Specifies how data is ordered in each partition.

    Definition Classes
    RDDScanExecSparkPlan
  102. val 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
    RDDScanExecSparkPlan
  103. lazy val outputSet: AttributeSet
    Definition Classes
    QueryPlan
    Annotations
    @transient()
  104. def p(number: Int): SparkPlan
    Definition Classes
    TreeNode
  105. val parent: CodegenSupport

    Which SparkPlan is calling produce() of this one.

    Which SparkPlan is calling produce() of this one. It's itself for the first SparkPlan.

    Attributes
    protected
    Definition Classes
    CodegenSupport
  106. final def prepare(): Unit

    Prepares this SparkPlan for execution.

    Prepares this SparkPlan for execution. It's idempotent.

    Definition Classes
    SparkPlan
  107. 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
  108. def prettyJson: String
    Definition Classes
    TreeNode
  109. def printSchema(): Unit
    Definition Classes
    QueryPlan
  110. final def produce(ctx: CodegenContext, parent: CodegenSupport): String

    Returns Java source code to process the rows from input RDD.

    Returns Java source code to process the rows from input RDD.

    Definition Classes
    CodegenSupport
  111. def producedAttributes: AttributeSet
    Definition Classes
    LeafExecNode → QueryPlan
  112. val rdd: RDD[InternalRow]
  113. lazy val references: AttributeSet
    Definition Classes
    QueryPlan
    Annotations
    @transient()
  114. 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
  115. 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
  116. def resetMetrics(): Unit

    Resets all the metrics.

    Resets all the metrics.

    Definition Classes
    SparkPlan
  117. final def sameResult(other: SparkPlan): Boolean
    Definition Classes
    QueryPlan
  118. lazy val schema: StructType
    Definition Classes
    QueryPlan
  119. def schemaString: String
    Definition Classes
    QueryPlan
  120. final def semanticHash(): Int
    Definition Classes
    QueryPlan
  121. def setLogicalLink(logicalPlan: LogicalPlan): Unit

    Set logical plan link recursively if unset.

    Set logical plan link recursively if unset.

    Definition Classes
    SparkPlan
  122. def setTagValue[T](tag: TreeNodeTag[T], value: T): Unit
    Definition Classes
    TreeNode
  123. def shouldStopCheckCode: String

    Helper default should stop check code.

    Helper default should stop check code.

    Definition Classes
    CodegenSupport
  124. def simpleString(maxFields: Int): String
    Definition Classes
    RDDScanExec → QueryPlan → TreeNode
  125. def simpleStringWithNodeId(): String
    Definition Classes
    QueryPlan → TreeNode
  126. def sparkContext: SparkContext
    Attributes
    protected
    Definition Classes
    SparkPlan
  127. 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
  128. def statePrefix: String
    Attributes
    protected
    Definition Classes
    QueryPlan
  129. def stringArgs: Iterator[Any]
    Attributes
    protected
    Definition Classes
    TreeNode
  130. def subqueries: Seq[SparkPlan]
    Definition Classes
    QueryPlan
  131. def subqueriesAll: Seq[SparkPlan]
    Definition Classes
    QueryPlan
  132. def supportCodegen: Boolean

    Whether this SparkPlan supports whole stage codegen or not.

    Whether this SparkPlan supports whole stage codegen or not.

    Definition Classes
    CodegenSupport
  133. 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
  134. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  135. def toJSON: String
    Definition Classes
    TreeNode
  136. def toString(): String
    Definition Classes
    TreeNode → AnyRef → Any
  137. def transform(rule: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
    Definition Classes
    TreeNode
  138. def transformAllExpressions(rule: PartialFunction[Expression, Expression]): RDDScanExec.this.type
    Definition Classes
    QueryPlan
  139. def transformDown(rule: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
    Definition Classes
    TreeNode
  140. def transformExpressions(rule: PartialFunction[Expression, Expression]): RDDScanExec.this.type
    Definition Classes
    QueryPlan
  141. def transformExpressionsDown(rule: PartialFunction[Expression, Expression]): RDDScanExec.this.type
    Definition Classes
    QueryPlan
  142. def transformExpressionsUp(rule: PartialFunction[Expression, Expression]): RDDScanExec.this.type
    Definition Classes
    QueryPlan
  143. def transformUp(rule: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
    Definition Classes
    TreeNode
  144. def treeString(append: (String) ⇒ Unit, verbose: Boolean, addSuffix: Boolean, maxFields: Int, printOperatorId: Boolean): Unit
    Definition Classes
    TreeNode
  145. final def treeString(verbose: Boolean, addSuffix: Boolean, maxFields: Int, printOperatorId: Boolean): String
    Definition Classes
    TreeNode
  146. final def treeString: String
    Definition Classes
    TreeNode
  147. def unsetTagValue[T](tag: TreeNodeTag[T]): Unit
    Definition Classes
    TreeNode
  148. def usedInputs: AttributeSet

    The subset of inputSet those should be evaluated before this plan.

    The subset of inputSet those should be evaluated before this plan.

    We will use this to insert some code to access those columns that are actually used by current plan before calling doConsume().

    Definition Classes
    CodegenSupport
  149. 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
  150. def verboseString(maxFields: Int): String
    Definition Classes
    QueryPlan → TreeNode
  151. def verboseStringWithOperatorId(): String
    Definition Classes
    LeafExecNode → QueryPlan
  152. def verboseStringWithSuffix(maxFields: Int): String
    Definition Classes
    TreeNode
  153. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  154. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  155. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  156. 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
  157. def withNewChildren(newChildren: Seq[SparkPlan]): SparkPlan
    Definition Classes
    TreeNode

Inherited from InputRDDCodegen

Inherited from CodegenSupport

Inherited from LeafExecNode

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