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org.apache.spark.sql.execution

BlockingOperatorWithCodegen

trait BlockingOperatorWithCodegen extends SparkPlan with CodegenSupport

A special kind of operators which support whole stage codegen. Blocking means these operators will consume all the inputs first, before producing output. Typical blocking operators are sort and aggregate.

Linear Supertypes
CodegenSupport, SparkPlan, Serializable, Serializable, Logging, QueryPlan[SparkPlan], TreeNode[SparkPlan], Product, Equals, AnyRef, Any
Known Subclasses
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Inherited
  1. BlockingOperatorWithCodegen
  2. CodegenSupport
  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

Abstract Value Members

  1. abstract def canEqual(that: Any): Boolean
    Definition Classes
    Equals
  2. abstract def children: Seq[SparkPlan]
    Definition Classes
    TreeNode
  3. abstract 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
    SparkPlan
  4. abstract 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; }

    Attributes
    protected
    Definition Classes
    CodegenSupport
  5. abstract 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
    CodegenSupport
    Note

    Right now we support up to two RDDs

  6. abstract def output: Seq[Attribute]
    Definition Classes
    QueryPlan
  7. abstract def productArity: Int
    Definition Classes
    Product
  8. abstract def productElement(n: Int): Any
    Definition Classes
    Product

Concrete 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
    BlockingOperatorWithCodegenCodegenSupport
  10. final lazy val canonicalized: SparkPlan
    Definition Classes
    QueryPlan
    Annotations
    @transient()
  11. 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
  12. def clone(): SparkPlan
    Definition Classes
    TreeNode → AnyRef
  13. def collect[B](pf: PartialFunction[SparkPlan, B]): Seq[B]
    Definition Classes
    TreeNode
  14. def collectFirst[B](pf: PartialFunction[SparkPlan, B]): Option[B]
    Definition Classes
    TreeNode
  15. def collectInPlanAndSubqueries[B](f: PartialFunction[SparkPlan, B]): Seq[B]
    Definition Classes
    QueryPlan
  16. def collectLeaves(): Seq[SparkPlan]
    Definition Classes
    TreeNode
  17. def conf: SQLConf
    Definition Classes
    QueryPlan
  18. 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
  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 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
  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. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  28. 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
  29. 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
  30. 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
  31. 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
  32. 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
  33. 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
  34. 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
  35. 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
  36. 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
  37. 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
  38. 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).

  39. final def expressions: Seq[Expression]
    Definition Classes
    QueryPlan
  40. def fastEquals(other: TreeNode[_]): Boolean
    Definition Classes
    TreeNode
  41. def find(f: (SparkPlan) ⇒ Boolean): Option[SparkPlan]
    Definition Classes
    TreeNode
  42. def flatMap[A](f: (SparkPlan) ⇒ TraversableOnce[A]): Seq[A]
    Definition Classes
    TreeNode
  43. def foreach(f: (SparkPlan) ⇒ Unit): Unit
    Definition Classes
    TreeNode
  44. def foreachUp(f: (SparkPlan) ⇒ Unit): Unit
    Definition Classes
    TreeNode
  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() @HotSpotIntrinsicCandidate()
  47. def getTagValue[T](tag: TreeNodeTag[T]): Option[T]
    Definition Classes
    TreeNode
  48. def hashCode(): Int
    Definition Classes
    TreeNode → AnyRef → Any
  49. val id: Int
    Definition Classes
    SparkPlan
  50. def initializeForcefully(isInterpreter: Boolean, silent: Boolean): Unit
    Definition Classes
    Logging
  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 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
    BlockingOperatorWithCodegenCodegenSupport
  60. 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
  61. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  62. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  63. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  64. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  65. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  66. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  67. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  68. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  69. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  70. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  71. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  72. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  73. def logicalLink: Option[LogicalPlan]

    returns

    The logical plan this plan is linked to.

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

    returns

    SQLMetric for the name.

    Definition Classes
    SparkPlan
  75. 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
  76. def map[A](f: (SparkPlan) ⇒ A): Seq[A]
    Definition Classes
    TreeNode
  77. def mapChildren(f: (SparkPlan) ⇒ SparkPlan): SparkPlan
    Definition Classes
    TreeNode
  78. def mapExpressions(f: (Expression) ⇒ Expression): BlockingOperatorWithCodegen.this.type
    Definition Classes
    QueryPlan
  79. def mapProductIterator[B](f: (Any) ⇒ B)(implicit arg0: ClassTag[B]): Array[B]
    Attributes
    protected
    Definition Classes
    TreeNode
  80. 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
  81. def metrics: Map[String, SQLMetric]

    returns

    All metrics containing metrics of this SparkPlan.

    Definition Classes
    SparkPlan
  82. final def missingInput: AttributeSet
    Definition Classes
    QueryPlan
  83. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  84. 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
    BlockingOperatorWithCodegenCodegenSupport
  85. 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
    BlockingOperatorWithCodegenCodegenSupport
  86. def nodeName: String
    Definition Classes
    TreeNode
  87. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  88. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  89. def numberedTreeString: String
    Definition Classes
    TreeNode
  90. val origin: Origin
    Definition Classes
    TreeNode
  91. def otherCopyArgs: Seq[AnyRef]
    Attributes
    protected
    Definition Classes
    TreeNode
  92. def outputOrdering: Seq[SortOrder]

    Specifies how data is ordered in each partition.

    Specifies how data is ordered in each partition.

    Definition Classes
    SparkPlan
  93. 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
    SparkPlan
  94. lazy val outputSet: AttributeSet
    Definition Classes
    QueryPlan
    Annotations
    @transient()
  95. def p(number: Int): SparkPlan
    Definition Classes
    TreeNode
  96. 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
  97. final def prepare(): Unit

    Prepares this SparkPlan for execution.

    Prepares this SparkPlan for execution. It's idempotent.

    Definition Classes
    SparkPlan
  98. 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
  99. def prettyJson: String
    Definition Classes
    TreeNode
  100. def printSchema(): Unit
    Definition Classes
    QueryPlan
  101. 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
  102. def producedAttributes: AttributeSet
    Definition Classes
    QueryPlan
  103. def productIterator: Iterator[Any]
    Definition Classes
    Product
  104. def productPrefix: String
    Definition Classes
    Product
  105. lazy val references: AttributeSet
    Definition Classes
    QueryPlan
    Annotations
    @transient()
  106. 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
  107. 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
  108. def resetMetrics(): Unit

    Resets all the metrics.

    Resets all the metrics.

    Definition Classes
    SparkPlan
  109. final def sameResult(other: SparkPlan): Boolean
    Definition Classes
    QueryPlan
  110. lazy val schema: StructType
    Definition Classes
    QueryPlan
  111. def schemaString: String
    Definition Classes
    QueryPlan
  112. final def semanticHash(): Int
    Definition Classes
    QueryPlan
  113. def setLogicalLink(logicalPlan: LogicalPlan): Unit

    Set logical plan link recursively if unset.

    Set logical plan link recursively if unset.

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

    Helper default should stop check code.

    Helper default should stop check code.

    Definition Classes
    CodegenSupport
  116. def simpleString(maxFields: Int): String
    Definition Classes
    QueryPlan → TreeNode
  117. def simpleStringWithNodeId(): String
    Definition Classes
    QueryPlan → TreeNode
  118. def sparkContext: SparkContext
    Attributes
    protected
    Definition Classes
    SparkPlan
  119. 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
  120. def statePrefix: String
    Attributes
    protected
    Definition Classes
    QueryPlan
  121. def stringArgs: Iterator[Any]
    Attributes
    protected
    Definition Classes
    TreeNode
  122. def subqueries: Seq[SparkPlan]
    Definition Classes
    QueryPlan
  123. def subqueriesAll: Seq[SparkPlan]
    Definition Classes
    QueryPlan
  124. def supportCodegen: Boolean

    Whether this SparkPlan supports whole stage codegen or not.

    Whether this SparkPlan supports whole stage codegen or not.

    Definition Classes
    CodegenSupport
  125. 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
  126. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  127. def toJSON: String
    Definition Classes
    TreeNode
  128. def toString(): String
    Definition Classes
    TreeNode → AnyRef → Any
  129. def transform(rule: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
    Definition Classes
    TreeNode
  130. def transformAllExpressions(rule: PartialFunction[Expression, Expression]): BlockingOperatorWithCodegen.this.type
    Definition Classes
    QueryPlan
  131. def transformDown(rule: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
    Definition Classes
    TreeNode
  132. def transformExpressions(rule: PartialFunction[Expression, Expression]): BlockingOperatorWithCodegen.this.type
    Definition Classes
    QueryPlan
  133. def transformExpressionsDown(rule: PartialFunction[Expression, Expression]): BlockingOperatorWithCodegen.this.type
    Definition Classes
    QueryPlan
  134. def transformExpressionsUp(rule: PartialFunction[Expression, Expression]): BlockingOperatorWithCodegen.this.type
    Definition Classes
    QueryPlan
  135. def transformUp(rule: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
    Definition Classes
    TreeNode
  136. def treeString(append: (String) ⇒ Unit, verbose: Boolean, addSuffix: Boolean, maxFields: Int, printOperatorId: Boolean): Unit
    Definition Classes
    TreeNode
  137. final def treeString(verbose: Boolean, addSuffix: Boolean, maxFields: Int, printOperatorId: Boolean): String
    Definition Classes
    TreeNode
  138. final def treeString: String
    Definition Classes
    TreeNode
  139. def unsetTagValue[T](tag: TreeNodeTag[T]): Unit
    Definition Classes
    TreeNode
  140. 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
  141. 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
  142. def verboseString(maxFields: Int): String
    Definition Classes
    QueryPlan → TreeNode
  143. def verboseStringWithOperatorId(): String
    Definition Classes
    QueryPlan
  144. def verboseStringWithSuffix(maxFields: Int): String
    Definition Classes
    TreeNode
  145. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  146. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  147. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  148. 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
  149. def withNewChildren(newChildren: Seq[SparkPlan]): SparkPlan
    Definition Classes
    TreeNode

Deprecated Value Members

  1. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] ) @Deprecated @deprecated
    Deprecated

    (Since version ) see corresponding Javadoc for more information.

Inherited from CodegenSupport

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