case class WindowExec(windowExpression: Seq[NamedExpression], partitionSpec: Seq[Expression], orderSpec: Seq[SortOrder], child: SparkPlan) extends WindowExecBase with Product with Serializable
This class calculates and outputs (windowed) aggregates over the rows in a single (sorted) partition. The aggregates are calculated for each row in the group. Special processing instructions, frames, are used to calculate these aggregates. Frames are processed in the order specified in the window specification (the ORDER BY ... clause). There are four different frame types: - Entire partition: The frame is the entire partition, i.e. UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING. For this case, window function will take all rows as inputs and be evaluated once. - Growing frame: We only add new rows into the frame, i.e. UNBOUNDED PRECEDING AND .... Every time we move to a new row to process, we add some rows to the frame. We do not remove rows from this frame. - Shrinking frame: We only remove rows from the frame, i.e. ... AND UNBOUNDED FOLLOWING. Every time we move to a new row to process, we remove some rows from the frame. We do not add rows to this frame. - Moving frame: Every time we move to a new row to process, we remove some rows from the frame and we add some rows to the frame. Examples are: 1 PRECEDING AND CURRENT ROW and 1 FOLLOWING AND 2 FOLLOWING. - Offset frame: The frame consist of one row, which is an offset number of rows away from the current row. Only OffsetWindowFunctions can be processed in an offset frame.
Different frame boundaries can be used in Growing, Shrinking and Moving frames. A frame boundary can be either Row or Range based: - Row Based: A row based boundary is based on the position of the row within the partition. An offset indicates the number of rows above or below the current row, the frame for the current row starts or ends. For instance, given a row based sliding frame with a lower bound offset of -1 and a upper bound offset of +2. The frame for row with index 5 would range from index 4 to index 6. - Range based: A range based boundary is based on the actual value of the ORDER BY expression(s). An offset is used to alter the value of the ORDER BY expression, for instance if the current order by expression has a value of 10 and the lower bound offset is -3, the resulting lower bound for the current row will be 10 - 3 = 7. This however puts a number of constraints on the ORDER BY expressions: there can be only one expression and this expression must have a numerical data type. An exception can be made when the offset is 0, because no value modification is needed, in this case multiple and non-numeric ORDER BY expression are allowed.
This is quite an expensive operator because every row for a single group must be in the same partition and partitions must be sorted according to the grouping and sort order. The operator requires the planner to take care of the partitioning and sorting.
The operator is semi-blocking. The window functions and aggregates are calculated one group at a time, the result will only be made available after the processing for the entire group has finished. The operator is able to process different frame configurations at the same time. This is done by delegating the actual frame processing (i.e. calculation of the window functions) to specialized classes, see WindowFunctionFrame, which take care of their own frame type: Entire Partition, Sliding, Growing & Shrinking. Boundary evaluation is also delegated to a pair of specialized classes: RowBoundOrdering & RangeBoundOrdering.
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      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). 
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      Create the resulting projection. Create the resulting projection. This method uses Code Generation. It can only be used on the executor side. - expressions
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      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
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      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
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      Overridden by concrete implementations of SparkPlan. Overridden by concrete implementations of SparkPlan. It is guaranteed to run before any executeof SparkPlan. This is helpful if we want to set up some state before executing the query, e.g.,BroadcastHashJoinuses it to broadcast asynchronously.- Attributes
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      Returns the result of this query as an RDD[InternalRow] by delegating to doExecuteafter preparations.Returns the result of this query as an RDD[InternalRow] by delegating to doExecuteafter preparations.Concrete implementations of SparkPlan should override doExecute.- Definition Classes
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      Returns the result of this query as a broadcast variable by delegating to doExecuteBroadcastafter preparations.Returns the result of this query as a broadcast variable by delegating to doExecuteBroadcastafter preparations.Concrete implementations of SparkPlan should override doExecuteBroadcast.- Definition Classes
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      Runs this query returning the result as an array. Runs this query returning the result as an array. - Definition Classes
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      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
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      Returns the result of this query as an RDD[ColumnarBatch] by delegating to doColumnarExecuteafter preparations.Returns the result of this query as an RDD[ColumnarBatch] by delegating to doColumnarExecuteafter preparations.Concrete implementations of SparkPlan should override doColumnarExecuteifsupportsColumnarreturns true.- Definition Classes
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      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
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      Runs this query returning the first nrows as an array.Runs this query returning the first nrows as an array.This is modeled after RDD.takebut never runs any job locally on the driver.- Definition Classes
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      Runs this query returning the result as an iterator of InternalRow. Runs this query returning the result as an iterator of InternalRow. - Definition Classes
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        logicalLink: Option[LogicalPlan]
      
      
      - returns
- The logical plan this plan is linked to. 
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      - returns
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        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
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      - returns
- All metrics containing metrics of this SparkPlan. 
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      Specifies how data is ordered in each partition. Specifies how data is ordered in each partition. - Definition Classes
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      Specifies how data is partitioned across different nodes in the cluster. Specifies how data is partitioned across different nodes in the cluster. - Definition Classes
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      - Definition Classes
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      - Definition Classes
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-  val partitionSpec: Seq[Expression]
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      Prepares this SparkPlan for execution. Prepares this SparkPlan for execution. It's idempotent. - Definition Classes
- SparkPlan
 
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      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
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      - Definition Classes
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        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
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      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
- WindowExec → SparkPlan
 
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      Resets all the metrics. Resets all the metrics. - Definition Classes
- SparkPlan
 
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      - Definition Classes
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      - Definition Classes
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      - Definition Classes
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      - Definition Classes
- QueryPlan
 
- 
      
      
      
        
      
    
      
        
        def
      
      
        setLogicalLink(logicalPlan: LogicalPlan): Unit
      
      
      Set logical plan link recursively if unset. Set logical plan link recursively if unset. - Definition Classes
- SparkPlan
 
- 
      
      
      
        
      
    
      
        
        def
      
      
        setTagValue[T](tag: TreeNodeTag[T], value: T): Unit
      
      
      - Definition Classes
- TreeNode
 
- 
      
      
      
        
      
    
      
        
        def
      
      
        simpleString(maxFields: Int): String
      
      
      - Definition Classes
- QueryPlan → TreeNode
 
- 
      
      
      
        
      
    
      
        
        def
      
      
        simpleStringWithNodeId(): String
      
      
      - Definition Classes
- QueryPlan → TreeNode
 
- 
      
      
      
        
      
    
      
        
        def
      
      
        sparkContext: SparkContext
      
      
      - Attributes
- protected
- Definition Classes
- SparkPlan
 
- 
      
      
      
        
      
    
      
        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
 
- 
      
      
      
        
      
    
      
        
        def
      
      
        statePrefix: String
      
      
      - Attributes
- protected
- Definition Classes
- QueryPlan
 
- 
      
      
      
        
      
    
      
        
        def
      
      
        stringArgs: Iterator[Any]
      
      
      - Attributes
- protected
- Definition Classes
- TreeNode
 
- 
      
      
      
        
      
    
      
        
        def
      
      
        subqueries: Seq[SparkPlan]
      
      
      - Definition Classes
- QueryPlan
 
- 
      
      
      
        
      
    
      
        
        def
      
      
        subqueriesAll: Seq[SparkPlan]
      
      
      - Definition Classes
- QueryPlan
 
- 
      
      
      
        
      
    
      
        
        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
 
- 
      
      
      
        
      
    
      
        final 
        def
      
      
        synchronized[T0](arg0: ⇒ T0): T0
      
      
      - Definition Classes
- AnyRef
 
- 
      
      
      
        
      
    
      
        
        def
      
      
        toJSON: String
      
      
      - Definition Classes
- TreeNode
 
- 
      
      
      
        
      
    
      
        
        def
      
      
        toString(): String
      
      
      - Definition Classes
- TreeNode → AnyRef → Any
 
- 
      
      
      
        
      
    
      
        
        def
      
      
        transform(rule: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
      
      
      - Definition Classes
- TreeNode
 
- 
      
      
      
        
      
    
      
        
        def
      
      
        transformAllExpressions(rule: PartialFunction[Expression, Expression]): WindowExec.this.type
      
      
      - Definition Classes
- QueryPlan
 
- 
      
      
      
        
      
    
      
        
        def
      
      
        transformDown(rule: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
      
      
      - Definition Classes
- TreeNode
 
- 
      
      
      
        
      
    
      
        
        def
      
      
        transformExpressions(rule: PartialFunction[Expression, Expression]): WindowExec.this.type
      
      
      - Definition Classes
- QueryPlan
 
- 
      
      
      
        
      
    
      
        
        def
      
      
        transformExpressionsDown(rule: PartialFunction[Expression, Expression]): WindowExec.this.type
      
      
      - Definition Classes
- QueryPlan
 
- 
      
      
      
        
      
    
      
        
        def
      
      
        transformExpressionsUp(rule: PartialFunction[Expression, Expression]): WindowExec.this.type
      
      
      - Definition Classes
- QueryPlan
 
- 
      
      
      
        
      
    
      
        
        def
      
      
        transformUp(rule: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
      
      
      - Definition Classes
- TreeNode
 
- 
      
      
      
        
      
    
      
        
        def
      
      
        treeString(append: (String) ⇒ Unit, verbose: Boolean, addSuffix: Boolean, maxFields: Int, printOperatorId: Boolean): Unit
      
      
      - Definition Classes
- TreeNode
 
- 
      
      
      
        
      
    
      
        final 
        def
      
      
        treeString(verbose: Boolean, addSuffix: Boolean, maxFields: Int, printOperatorId: Boolean): String
      
      
      - Definition Classes
- TreeNode
 
- 
      
      
      
        
      
    
      
        final 
        def
      
      
        treeString: String
      
      
      - Definition Classes
- TreeNode
 
- 
      
      
      
        
      
    
      
        
        def
      
      
        unsetTagValue[T](tag: TreeNodeTag[T]): Unit
      
      
      - Definition Classes
- TreeNode
 
- 
      
      
      
        
      
    
      
        
        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
 
- 
      
      
      
        
      
    
      
        
        def
      
      
        verboseString(maxFields: Int): String
      
      
      - Definition Classes
- QueryPlan → TreeNode
 
- 
      
      
      
        
      
    
      
        
        def
      
      
        verboseStringWithOperatorId(): String
      
      
      - Definition Classes
- UnaryExecNode → QueryPlan
 
- 
      
      
      
        
      
    
      
        
        def
      
      
        verboseStringWithSuffix(maxFields: Int): String
      
      
      - Definition Classes
- TreeNode
 
- 
      
      
      
        
      
    
      
        final 
        def
      
      
        wait(): Unit
      
      
      - Definition Classes
- AnyRef
- Annotations
- @throws( ... )
 
- 
      
      
      
        
      
    
      
        final 
        def
      
      
        wait(arg0: Long, arg1: Int): Unit
      
      
      - Definition Classes
- AnyRef
- Annotations
- @throws( ... )
 
- 
      
      
      
        
      
    
      
        final 
        def
      
      
        wait(arg0: Long): Unit
      
      
      - Definition Classes
- AnyRef
- Annotations
- @throws( ... ) @native()
 
- 
      
      
      
        
      
    
      
        
        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
 
-  val windowExpression: Seq[NamedExpression]
- 
      
      
      
        
      
    
      
        
        lazy val
      
      
        windowFrameExpressionFactoryPairs: Seq[(ExpressionBuffer, (InternalRow) ⇒ WindowFunctionFrame)]
      
      
      Collection containing an entry for each window frame to process. Collection containing an entry for each window frame to process. Each entry contains a frame's WindowExpressions and factory function for the WindowFrameFunction. - Attributes
- protected
- Definition Classes
- WindowExecBase
 
- 
      
      
      
        
      
    
      
        
        def
      
      
        withNewChildren(newChildren: Seq[SparkPlan]): SparkPlan
      
      
      - Definition Classes
- TreeNode