case class CommandResultExec(output: Seq[Attribute], commandPhysicalPlan: SparkPlan, rows: Seq[InternalRow]) extends SparkPlan with LeafExecNode with InputRDDCodegen with Product with Serializable
Physical plan node for holding data from a command.
commandPhysicalPlan
is just used to display the plan tree for EXPLAIN.
rows
may not be serializable and ideally we should not send rows
to the executors.
Thus marking them as transient.
- Alphabetic
- By Inheritance
- CommandResultExec
- InputRDDCodegen
- CodegenSupport
- LeafExecNode
- LeafLike
- SparkPlan
- Serializable
- Logging
- QueryPlan
- SQLConfHelper
- TreeNode
- TreePatternBits
- Product
- Equals
- AnyRef
- Any
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- Public
- Protected
Instance Constructors
Value Members
- lazy val allAttributes: AttributeSeq
- Definition Classes
- QueryPlan
- def apply(number: Int): TreeNode[_]
- Definition Classes
- TreeNode
- def argString(maxFields: Int): String
- Definition Classes
- TreeNode
- def asCode: String
- Definition Classes
- TreeNode
- final lazy val canonicalized: SparkPlan
- Definition Classes
- QueryPlan
- Annotations
- @transient()
- final def children: Seq[SparkPlan]
- Definition Classes
- LeafLike
- def clone(): SparkPlan
- Definition Classes
- TreeNode → AnyRef
- def collect[B](pf: PartialFunction[SparkPlan, B]): Seq[B]
- Definition Classes
- TreeNode
- def collectFirst[B](pf: PartialFunction[SparkPlan, B]): Option[B]
- Definition Classes
- TreeNode
- def collectLeaves(): Seq[SparkPlan]
- Definition Classes
- TreeNode
- def collectWithSubqueries[B](f: PartialFunction[SparkPlan, B]): Seq[B]
- Definition Classes
- QueryPlan
- val commandPhysicalPlan: SparkPlan
- def conf: SQLConf
- Definition Classes
- SparkPlan → SQLConfHelper
- 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
androw
can't both be null.- Definition Classes
- CodegenSupport
- final def containsAllPatterns(patterns: TreePattern*): Boolean
- Definition Classes
- TreePatternBits
- final def containsAnyPattern(patterns: TreePattern*): Boolean
- Definition Classes
- TreePatternBits
- lazy val containsChild: Set[TreeNode[_]]
- Definition Classes
- TreeNode
- final def containsPattern(t: TreePattern): Boolean
- Definition Classes
- TreePatternBits
- Annotations
- @inline()
- def copyTagsFrom(other: SparkPlan): Unit
- Definition Classes
- TreeNode
- lazy val deterministic: Boolean
- Definition Classes
- QueryPlan
- 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 putrow.code
in the generated code and setCodegenContext.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
- 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.
- Definition Classes
- CommandResultExec → SparkPlan
- 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
- InputRDDCodegen → CodegenSupport
- 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
- 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
- def executeCollect(): Array[InternalRow]
Runs this query returning the result as an array.
Runs this query returning the result as an array.
- Definition Classes
- CommandResultExec → SparkPlan
- 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
- 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
ifsupportsColumnar
returns true.- Definition Classes
- SparkPlan
- def executeTail(limit: 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
- CommandResultExec → SparkPlan
- def executeTake(limit: 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
- CommandResultExec → SparkPlan
- 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).
- def exists(f: (SparkPlan) => Boolean): Boolean
- Definition Classes
- TreeNode
- final def expressions: Seq[Expression]
- Definition Classes
- QueryPlan
- def fastEquals(other: TreeNode[_]): Boolean
- Definition Classes
- TreeNode
- def find(f: (SparkPlan) => Boolean): Option[SparkPlan]
- Definition Classes
- TreeNode
- def flatMap[A](f: (SparkPlan) => TraversableOnce[A]): Seq[A]
- Definition Classes
- TreeNode
- def foreach(f: (SparkPlan) => Unit): Unit
- Definition Classes
- TreeNode
- def foreachUp(f: (SparkPlan) => Unit): Unit
- Definition Classes
- TreeNode
- def generateTreeString(depth: Int, lastChildren: Seq[Boolean], append: (String) => Unit, verbose: Boolean, prefix: String, addSuffix: Boolean, maxFields: Int, printNodeId: Boolean, indent: Int): Unit
- Definition Classes
- TreeNode
- def getTagValue[T](tag: TreeNodeTag[T]): Option[T]
- Definition Classes
- TreeNode
- def hashCode(): Int
- Definition Classes
- TreeNode → AnyRef → Any
- val id: Int
- Definition Classes
- SparkPlan
- def innerChildren: Seq[QueryPlan[_]]
- Definition Classes
- CommandResultExec → QueryPlan → TreeNode
- def inputRDD: RDD[InternalRow]
- Definition Classes
- CommandResultExec → InputRDDCodegen
- 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
- InputRDDCodegen → CodegenSupport
- Note
Right now we support up to two RDDs
- def inputSet: AttributeSet
- Definition Classes
- QueryPlan
- 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
- 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
- def logicalLink: Option[LogicalPlan]
- returns
The logical plan this plan is linked to.
- Definition Classes
- SparkPlan
- def longMetric(name: String): SQLMetric
- returns
SQLMetric for the
name
.
- Definition Classes
- SparkPlan
- 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
- def map[A](f: (SparkPlan) => A): Seq[A]
- Definition Classes
- TreeNode
- final def mapChildren(f: (SparkPlan) => SparkPlan): SparkPlan
- Definition Classes
- LeafLike
- def mapExpressions(f: (Expression) => Expression): CommandResultExec.this.type
- Definition Classes
- QueryPlan
- 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
- lazy val metrics: Map[String, SQLMetric]
- returns
All metrics containing metrics of this SparkPlan.
- Definition Classes
- CommandResultExec → SparkPlan
- final def missingInput: AttributeSet
- Definition Classes
- QueryPlan
- 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
- 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
- def nodeName: String
- Definition Classes
- TreeNode
- def numberedTreeString: String
- Definition Classes
- TreeNode
- val origin: Origin
- Definition Classes
- TreeNode
- val output: Seq[Attribute]
- Definition Classes
- CommandResultExec → QueryPlan
- def outputOrdering: Seq[SortOrder]
Specifies how data is ordered in each partition.
Specifies how data is ordered in each partition.
- Definition Classes
- SparkPlan
- 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. Note this method may fail if it is invoked before
EnsureRequirements
is applied sincePartitioningCollection
requires all its partitionings to have the same number of partitions.- Definition Classes
- SparkPlan
- lazy val outputSet: AttributeSet
- Definition Classes
- QueryPlan
- Annotations
- @transient()
- def p(number: Int): SparkPlan
- Definition Classes
- TreeNode
- final def prepare(): Unit
Prepares this SparkPlan for execution.
Prepares this SparkPlan for execution. It's idempotent.
- Definition Classes
- SparkPlan
- def prettyJson: String
- Definition Classes
- TreeNode
- def printSchema(): Unit
- Definition Classes
- QueryPlan
- 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
- def producedAttributes: AttributeSet
- Definition Classes
- LeafExecNode → QueryPlan
- def productElementNames: Iterator[String]
- Definition Classes
- Product
- lazy val references: AttributeSet
- Definition Classes
- QueryPlan
- Annotations
- @transient()
- 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
- 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
- def resetMetrics(): Unit
Resets all the metrics.
Resets all the metrics.
- Definition Classes
- SparkPlan
- def rewriteAttrs(attrMap: AttributeMap[Attribute]): SparkPlan
- Definition Classes
- QueryPlan
- val rows: Seq[InternalRow]
- final def sameResult(other: SparkPlan): Boolean
- Definition Classes
- QueryPlan
- lazy val schema: StructType
- Definition Classes
- QueryPlan
- def schemaString: String
- Definition Classes
- QueryPlan
- final def semanticHash(): Int
- Definition Classes
- QueryPlan
- final val session: SparkSession
- Definition Classes
- SparkPlan
- 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 shouldStopCheckCode: String
Helper default should stop check code.
Helper default should stop check code.
- Definition Classes
- CodegenSupport
- def simpleString(maxFields: Int): String
- Definition Classes
- QueryPlan → TreeNode
- def simpleStringWithNodeId(): String
- Definition Classes
- QueryPlan → TreeNode
- lazy val subqueries: Seq[SparkPlan]
- Definition Classes
- QueryPlan
- Annotations
- @transient()
- def subqueriesAll: Seq[SparkPlan]
- Definition Classes
- QueryPlan
- def supportCodegen: Boolean
Whether this SparkPlan supports whole stage codegen or not.
Whether this SparkPlan supports whole stage codegen or not.
- Definition Classes
- CodegenSupport
- 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. A plan can also support row-based execution (see
supportsRowBased
). Spark will decide which execution to be called during query planning.- Definition Classes
- SparkPlan
- def supportsRowBased: Boolean
Return true if this stage of the plan supports row-based execution.
Return true if this stage of the plan supports row-based execution. A plan can also support columnar execution (see
supportsColumnar
). Spark will decide which execution to be called during query planning.- Definition Classes
- SparkPlan
- def toJSON: String
- Definition Classes
- TreeNode
- def toRowBased: SparkPlan
Converts the output of this plan to row-based if it is columnar plan.
Converts the output of this plan to row-based if it is columnar plan.
- Definition Classes
- SparkPlan
- def toString(): String
- Definition Classes
- TreeNode → AnyRef → Any
- def transform(rule: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
- Definition Classes
- TreeNode
- def transformAllExpressions(rule: PartialFunction[Expression, Expression]): CommandResultExec.this.type
- Definition Classes
- QueryPlan
- def transformAllExpressionsWithPruning(cond: (TreePatternBits) => Boolean, ruleId: RuleId)(rule: PartialFunction[Expression, Expression]): CommandResultExec.this.type
- Definition Classes
- QueryPlan
- def transformDown(rule: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
- Definition Classes
- TreeNode
- def transformDownWithPruning(cond: (TreePatternBits) => Boolean, ruleId: RuleId)(rule: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
- Definition Classes
- TreeNode
- def transformDownWithSubqueries(f: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
- Definition Classes
- QueryPlan
- def transformDownWithSubqueriesAndPruning(cond: (TreePatternBits) => Boolean, ruleId: RuleId)(f: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
- Definition Classes
- QueryPlan
- def transformExpressions(rule: PartialFunction[Expression, Expression]): CommandResultExec.this.type
- Definition Classes
- QueryPlan
- def transformExpressionsDown(rule: PartialFunction[Expression, Expression]): CommandResultExec.this.type
- Definition Classes
- QueryPlan
- def transformExpressionsDownWithPruning(cond: (TreePatternBits) => Boolean, ruleId: RuleId)(rule: PartialFunction[Expression, Expression]): CommandResultExec.this.type
- Definition Classes
- QueryPlan
- def transformExpressionsUp(rule: PartialFunction[Expression, Expression]): CommandResultExec.this.type
- Definition Classes
- QueryPlan
- def transformExpressionsUpWithPruning(cond: (TreePatternBits) => Boolean, ruleId: RuleId)(rule: PartialFunction[Expression, Expression]): CommandResultExec.this.type
- Definition Classes
- QueryPlan
- def transformExpressionsWithPruning(cond: (TreePatternBits) => Boolean, ruleId: RuleId)(rule: PartialFunction[Expression, Expression]): CommandResultExec.this.type
- Definition Classes
- QueryPlan
- def transformUp(rule: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
- Definition Classes
- TreeNode
- def transformUpWithBeforeAndAfterRuleOnChildren(cond: (SparkPlan) => Boolean, ruleId: RuleId)(rule: PartialFunction[(SparkPlan, SparkPlan), SparkPlan]): SparkPlan
- Definition Classes
- TreeNode
- def transformUpWithNewOutput(rule: PartialFunction[SparkPlan, (SparkPlan, Seq[(Attribute, Attribute)])], skipCond: (SparkPlan) => Boolean, canGetOutput: (SparkPlan) => Boolean): SparkPlan
- Definition Classes
- QueryPlan
- def transformUpWithPruning(cond: (TreePatternBits) => Boolean, ruleId: RuleId)(rule: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
- Definition Classes
- TreeNode
- def transformUpWithSubqueries(f: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
- Definition Classes
- QueryPlan
- def transformWithPruning(cond: (TreePatternBits) => Boolean, ruleId: RuleId)(rule: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
- Definition Classes
- TreeNode
- def transformWithSubqueries(f: PartialFunction[SparkPlan, SparkPlan]): SparkPlan
- Definition Classes
- QueryPlan
- lazy val treePatternBits: BitSet
- Definition Classes
- QueryPlan → TreeNode → TreePatternBits
- 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 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
- 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
- LeafExecNode → QueryPlan
- def verboseStringWithSuffix(maxFields: Int): String
- Definition Classes
- TreeNode
- final def withNewChildren(newChildren: Seq[SparkPlan]): SparkPlan
- Definition Classes
- TreeNode
- final def withNewChildrenInternal(newChildren: IndexedSeq[SparkPlan]): SparkPlan
- Definition Classes
- LeafLike