case class FlatMapGroupsInPandasWithStateExec(functionExpr: Expression, groupingAttributes: Seq[Attribute], outAttributes: Seq[Attribute], stateType: StructType, stateInfo: Option[StatefulOperatorStateInfo], stateFormatVersion: Int, outputMode: OutputMode, timeoutConf: GroupStateTimeout, batchTimestampMs: Option[Long], eventTimeWatermarkForLateEvents: Option[Long], eventTimeWatermarkForEviction: Option[Long], child: SparkPlan) extends SparkPlan with UnaryExecNode with FlatMapGroupsWithStateExecBase with Product with Serializable
Physical operator for executing org.apache.spark.sql.catalyst.plans.logical.FlatMapGroupsInPandasWithState
- functionExpr
function called on each group
- groupingAttributes
used to group the data
- outAttributes
used to define the output rows
- stateType
used to serialize/deserialize state before calling
functionExpr- stateInfo
StatefulOperatorStateInfoto identify the state store for a given operator.- stateFormatVersion
the version of state format.
- outputMode
the output mode of
functionExpr- timeoutConf
used to timeout groups that have not received data in a while
- batchTimestampMs
processing timestamp of the current batch.
- eventTimeWatermarkForLateEvents
event time watermark for filtering late events
- eventTimeWatermarkForEviction
event time watermark for state eviction
- child
logical plan of the underlying data
- Alphabetic
- By Inheritance
- FlatMapGroupsInPandasWithStateExec
- FlatMapGroupsWithStateExecBase
- WatermarkSupport
- StateStoreWriter
- PythonSQLMetrics
- StatefulOperator
- UnaryExecNode
- UnaryLike
- SparkPlan
- Serializable
- Logging
- QueryPlan
- SQLConfHelper
- TreeNode
- TreePatternBits
- Product
- Equals
- AnyRef
- Any
- Hide All
- Show All
- Public
- Protected
Instance Constructors
- new FlatMapGroupsInPandasWithStateExec(functionExpr: Expression, groupingAttributes: Seq[Attribute], outAttributes: Seq[Attribute], stateType: StructType, stateInfo: Option[StatefulOperatorStateInfo], stateFormatVersion: Int, outputMode: OutputMode, timeoutConf: GroupStateTimeout, batchTimestampMs: Option[Long], eventTimeWatermarkForLateEvents: Option[Long], eventTimeWatermarkForEviction: Option[Long], child: SparkPlan)
- functionExpr
function called on each group
- groupingAttributes
used to group the data
- outAttributes
used to define the output rows
- stateType
used to serialize/deserialize state before calling
functionExpr- stateInfo
StatefulOperatorStateInfoto identify the state store for a given operator.- stateFormatVersion
the version of state format.
- outputMode
the output mode of
functionExpr- timeoutConf
used to timeout groups that have not received data in a while
- batchTimestampMs
processing timestamp of the current batch.
- eventTimeWatermarkForLateEvents
event time watermark for filtering late events
- eventTimeWatermarkForEviction
event time watermark for state eviction
- child
logical plan of the underlying data
Type Members
- abstract class InputProcessor extends AnyRef
- Definition Classes
- FlatMapGroupsWithStateExecBase
Value Members
- final def !=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def ##: Int
- Definition Classes
- AnyRef → Any
- final def ==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- lazy val allAttributes: AttributeSeq
- Definition Classes
- QueryPlan
- def apply(number: Int): TreeNode[_]
- Definition Classes
- TreeNode
- def applyRemovingRowsOlderThanWatermark(iter: Iterator[InternalRow], predicateDropRowByWatermark: BasePredicate): Iterator[InternalRow]
- Attributes
- protected
- Definition Classes
- StateStoreWriter
- def argString(maxFields: Int): String
- Definition Classes
- TreeNode
- def asCode: String
- Definition Classes
- TreeNode
- final def asInstanceOf[T0]: T0
- Definition Classes
- Any
- val batchTimestampMs: Option[Long]
- Definition Classes
- FlatMapGroupsInPandasWithStateExec → FlatMapGroupsWithStateExecBase
- final lazy val canonicalized: SparkPlan
- Definition Classes
- QueryPlan
- Annotations
- @transient()
- val child: SparkPlan
- Definition Classes
- FlatMapGroupsInPandasWithStateExec → WatermarkSupport → UnaryLike
- final lazy val children: Seq[SparkPlan]
- Definition Classes
- UnaryLike
- Annotations
- @transient()
- 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).
- 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
- def conf: SQLConf
- Definition Classes
- SparkPlan → SQLConfHelper
- 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
- def createInputProcessor(store: StateStore): InputProcessor
- Definition Classes
- FlatMapGroupsInPandasWithStateExec → FlatMapGroupsWithStateExecBase
- def customStatefulOperatorMetrics: Seq[StatefulOperatorCustomMetric]
Set of stateful operator custom metrics.
Set of stateful operator custom metrics. These are captured as part of the generic key-value map StateOperatorProgress.customMetrics. Stateful operators can extend this method to provide their own unique custom metrics.
- Attributes
- protected
- Definition Classes
- StateStoreWriter
- lazy val deterministic: Boolean
- Definition Classes
- QueryPlan
- def doCanonicalize(): SparkPlan
- Attributes
- protected
- Definition Classes
- QueryPlan
- 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
- FlatMapGroupsWithStateExecBase → SparkPlan
- def doExecuteBroadcast[T](): Broadcast[T]
Produces the result of the query as a broadcast variable.
- 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
- def doExecuteWrite(writeFilesSpec: WriteFilesSpec): RDD[WriterCommitMessage]
Produces the result of the writes as an
RDD[WriterCommitMessage]Produces the result of the writes as an
RDD[WriterCommitMessage]Overridden by concrete implementations of SparkPlan.
- Attributes
- protected
- Definition Classes
- SparkPlan
- def doPrepare(): Unit
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
- protected
- Definition Classes
- SparkPlan
- Note
preparemethod has already walked down the tree, so the implementation doesn't have to call children'spreparemethods. This will only be called once, protected bythis.
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- val eventTimeWatermarkForEviction: Option[Long]
The watermark value for closing aggregates and evicting state.
The watermark value for closing aggregates and evicting state. It is different from the late events filtering watermark (consider chained aggregators agg1 -> agg2: agg1 evicts state which will be effectively late against the eviction watermark but should not be late for agg2 input late record filtering watermark. Thus agg1 and agg2 use the current batch watermark for state eviction but the previous batch watermark for late record filtering.
- Definition Classes
- FlatMapGroupsInPandasWithStateExec → FlatMapGroupsWithStateExecBase → WatermarkSupport
- val eventTimeWatermarkForLateEvents: Option[Long]
The watermark value for filtering late events/records.
The watermark value for filtering late events/records. This should be the previous batch state eviction watermark.
- Definition Classes
- FlatMapGroupsInPandasWithStateExec → FlatMapGroupsWithStateExecBase → WatermarkSupport
- final def execute(): RDD[InternalRow]
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
- SparkPlan
- final def executeBroadcast[T](): Broadcast[T]
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
- 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
- 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
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
- SparkPlan
- 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
- def executeTail(n: Int): Array[InternalRow]
Runs this query returning the last
nrows as an array.Runs this query returning the last
nrows as an array.This is modeled after
RDD.takebut never runs any job locally on the driver.- Definition Classes
- SparkPlan
- def executeTake(n: Int): Array[InternalRow]
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
- 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 executeWrite(writeFilesSpec: WriteFilesSpec): RDD[WriterCommitMessage]
Returns the result of writes as an RDD[WriterCommitMessage] variable by delegating to
doExecuteWriteafter preparations.Returns the result of writes as an RDD[WriterCommitMessage] variable by delegating to
doExecuteWriteafter preparations.Concrete implementations of SparkPlan should override
doExecuteWrite.- Definition Classes
- SparkPlan
- 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 finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.Throwable])
- 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 formattedNodeName: String
- Attributes
- protected
- Definition Classes
- QueryPlan
- val functionExpr: Expression
- 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
- final def getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
- def getDefaultTreePatternBits: BitSet
- Attributes
- protected
- Definition Classes
- TreeNode
- def getProgress(): StateOperatorProgress
Get the progress made by this stateful operator after execution.
Get the progress made by this stateful operator after execution. This should be called in the driver after this SparkPlan has been executed and metrics have been updated.
- Definition Classes
- StateStoreWriter
- def getStateInfo: StatefulOperatorStateInfo
- Attributes
- protected
- Definition Classes
- StatefulOperator
- def getTagValue[T](tag: TreeNodeTag[T]): Option[T]
- Definition Classes
- TreeNode
- val groupingAttributes: Seq[Attribute]
- Definition Classes
- FlatMapGroupsInPandasWithStateExec → FlatMapGroupsWithStateExecBase
- val hasInitialState: Boolean
- Attributes
- protected
- Definition Classes
- FlatMapGroupsInPandasWithStateExec → FlatMapGroupsWithStateExecBase
- def hashCode(): Int
- Definition Classes
- TreeNode → AnyRef → Any
- val id: Int
- Definition Classes
- SparkPlan
- val initialState: SparkPlan
- Attributes
- protected
- Definition Classes
- FlatMapGroupsInPandasWithStateExec → FlatMapGroupsWithStateExecBase
- val initialStateDataAttrs: Seq[Attribute]
- Attributes
- protected
- Definition Classes
- FlatMapGroupsInPandasWithStateExec → FlatMapGroupsWithStateExecBase
- val initialStateDeserializer: Expression
- Attributes
- protected
- Definition Classes
- FlatMapGroupsInPandasWithStateExec → FlatMapGroupsWithStateExecBase
- val initialStateGroupAttrs: Seq[Attribute]
- Attributes
- protected
- Definition Classes
- FlatMapGroupsInPandasWithStateExec → FlatMapGroupsWithStateExecBase
- def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
- Attributes
- protected
- Definition Classes
- Logging
- def initializeLogIfNecessary(isInterpreter: Boolean): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def innerChildren: Seq[QueryPlan[_]]
- Definition Classes
- QueryPlan → TreeNode
- def inputSet: AttributeSet
- Definition Classes
- QueryPlan
- def isCanonicalizedPlan: Boolean
- Attributes
- protected
- Definition Classes
- QueryPlan
- final def isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- def isRuleIneffective(ruleId: RuleId): Boolean
- Attributes
- protected
- Definition Classes
- TreeNode
- val isTimeoutEnabled: Boolean
- Attributes
- protected
- Definition Classes
- FlatMapGroupsWithStateExecBase
- def isTraceEnabled(): Boolean
- Attributes
- protected
- Definition Classes
- Logging
- def jsonFields: List[JField]
- Attributes
- protected
- Definition Classes
- TreeNode
- def keyExpressions: Seq[Attribute]
The keys that may have a watermark attribute.
The keys that may have a watermark attribute.
- Definition Classes
- FlatMapGroupsWithStateExecBase → WatermarkSupport
- final def legacyWithNewChildren(newChildren: Seq[SparkPlan]): SparkPlan
- Attributes
- protected
- Definition Classes
- TreeNode
- def log: Logger
- Attributes
- protected
- Definition Classes
- Logging
- def logDebug(msg: => String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def logDebug(msg: => String): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def logError(msg: => String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def logError(msg: => String): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def logInfo(msg: => String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def logInfo(msg: => String): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def logName: String
- Attributes
- protected
- Definition Classes
- Logging
- def logTrace(msg: => String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def logTrace(msg: => String): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def logWarning(msg: => String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def logWarning(msg: => String): Unit
- Attributes
- protected
- Definition Classes
- Logging
- 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
- UnaryLike
- def mapExpressions(f: (Expression) => Expression): FlatMapGroupsInPandasWithStateExec.this.type
- Definition Classes
- QueryPlan
- def mapProductIterator[B](f: (Any) => B)(implicit arg0: ClassTag[B]): Array[B]
- Attributes
- protected
- Definition Classes
- TreeNode
- def markRuleAsIneffective(ruleId: RuleId): Unit
- Attributes
- protected
- Definition Classes
- TreeNode
- lazy val metrics: Map[String, SQLMetric]
- returns
All metrics containing metrics of this SparkPlan.
- Definition Classes
- StateStoreWriter → PythonSQLMetrics → SparkPlan
- final def missingInput: AttributeSet
- Definition Classes
- QueryPlan
- def multiTransformDown(rule: PartialFunction[SparkPlan, Seq[SparkPlan]]): Stream[SparkPlan]
- Definition Classes
- TreeNode
- def multiTransformDownWithPruning(cond: (TreePatternBits) => Boolean, ruleId: RuleId)(rule: PartialFunction[SparkPlan, Seq[SparkPlan]]): Stream[SparkPlan]
- Definition Classes
- TreeNode
- final def ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def nodeName: String
- Definition Classes
- TreeNode
- val nodePatterns: Seq[TreePattern]
- Attributes
- protected
- Definition Classes
- TreeNode
- final def notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
- final def notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
- def numberedTreeString: String
- Definition Classes
- TreeNode
- val origin: Origin
- Definition Classes
- TreeNode
- def otherCopyArgs: Seq[AnyRef]
- Attributes
- protected
- Definition Classes
- TreeNode
- val outAttributes: Seq[Attribute]
- def output: Seq[Attribute]
- Definition Classes
- FlatMapGroupsInPandasWithStateExec → QueryPlan
- val outputMode: OutputMode
- Definition Classes
- FlatMapGroupsInPandasWithStateExec → FlatMapGroupsWithStateExecBase
- def outputOrdering: Seq[SortOrder]
- Definition Classes
- QueryPlan
- 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
EnsureRequirementsis applied sincePartitioningCollectionrequires 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 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
- def prettyJson: String
- Definition Classes
- TreeNode
- def printSchema(): Unit
- Definition Classes
- QueryPlan
- def processDataWithPartition(iter: Iterator[InternalRow], store: StateStore, processor: InputProcessor, initialStateIterOption: Option[Iterator[InternalRow]] = None): CompletionIterator[InternalRow, Iterator[InternalRow]]
Process data by applying the user defined function on a per partition basis.
Process data by applying the user defined function on a per partition basis.
- iter
- Iterator of the data rows
- store
- associated state store for this partition
- processor
- handle to the input processor object.
- initialStateIterOption
- optional initial state iterator
- Definition Classes
- FlatMapGroupsWithStateExecBase
- def producedAttributes: AttributeSet
- Definition Classes
- QueryPlan
- def productElementNames: Iterator[String]
- Definition Classes
- Product
- val pythonMetrics: Map[String, SQLMetric]
- Definition Classes
- PythonSQLMetrics
- lazy val references: AttributeSet
- Definition Classes
- QueryPlan
- Annotations
- @transient()
- def removeKeysOlderThanWatermark(storeManager: StreamingAggregationStateManager, store: StateStore): Unit
- Attributes
- protected
- Definition Classes
- WatermarkSupport
- def removeKeysOlderThanWatermark(store: StateStore): Unit
- Attributes
- protected
- Definition Classes
- WatermarkSupport
- def requiredChildDistribution: Seq[Distribution]
Distribute by grouping attributes - We need the underlying data and the initial state data to have the same grouping so that the data are co-lacated on the same task.
Distribute by grouping attributes - We need the underlying data and the initial state data to have the same grouping so that the data are co-lacated on the same task.
- Definition Classes
- FlatMapGroupsInPandasWithStateExec → FlatMapGroupsWithStateExecBase → SparkPlan
- def requiredChildOrdering: Seq[Seq[SortOrder]]
Ordering needed for using GroupingIterator.
Ordering needed for using GroupingIterator. We need the initial state to also use the ordering as the data so that we can co-locate the keys from the underlying data and the initial state.
- Definition Classes
- FlatMapGroupsInPandasWithStateExec → FlatMapGroupsWithStateExecBase → SparkPlan
- def resetMetrics(): Unit
Resets all the metrics.
Resets all the metrics.
- Definition Classes
- SparkPlan
- def rewriteAttrs(attrMap: AttributeMap[Attribute]): SparkPlan
- Definition Classes
- QueryPlan
- 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 setOperatorMetrics(numStateStoreInstances: Int = 1): Unit
Set the operator level metrics
Set the operator level metrics
- Attributes
- protected
- Definition Classes
- StateStoreWriter
- def setStoreMetrics(store: StateStore): Unit
Set the SQL metrics related to the state store.
Set the SQL metrics related to the state store. This should be called in that task after the store has been updated.
- Attributes
- protected
- Definition Classes
- StateStoreWriter
- def setTagValue[T](tag: TreeNodeTag[T], value: T): Unit
- Definition Classes
- TreeNode
- def shortName: String
Name to output in StreamingOperatorProgress to identify operator type
Name to output in StreamingOperatorProgress to identify operator type
- Definition Classes
- FlatMapGroupsInPandasWithStateExec → FlatMapGroupsWithStateExecBase → StateStoreWriter
- def shouldRunAnotherBatch(newMetadata: OffsetSeqMetadata): Boolean
Should the MicroBatchExecution run another batch based on this stateful operator and the current updated metadata.
Should the MicroBatchExecution run another batch based on this stateful operator and the current updated metadata.
- Definition Classes
- FlatMapGroupsWithStateExecBase → StateStoreWriter
- def simpleString(maxFields: Int): String
- Definition Classes
- QueryPlan → TreeNode
- def simpleStringWithNodeId(): String
- Definition Classes
- QueryPlan → TreeNode
- def sparkContext: SparkContext
- Attributes
- protected
- Definition Classes
- SparkPlan
- val stateEncoder: ExpressionEncoder[Any]
- Attributes
- protected
- Definition Classes
- FlatMapGroupsInPandasWithStateExec → FlatMapGroupsWithStateExecBase
- val stateFormatVersion: Int
- Definition Classes
- FlatMapGroupsInPandasWithStateExec → FlatMapGroupsWithStateExecBase
- val stateInfo: Option[StatefulOperatorStateInfo]
- Definition Classes
- FlatMapGroupsInPandasWithStateExec → FlatMapGroupsWithStateExecBase → StatefulOperator
- lazy val stateManager: StateManager
- Definition Classes
- FlatMapGroupsWithStateExecBase
- def statePrefix: String
- Attributes
- protected
- Definition Classes
- QueryPlan
- val stateType: StructType
- def stringArgs: Iterator[Any]
- Attributes
- protected
- Definition Classes
- TreeNode
- lazy val subqueries: Seq[SparkPlan]
- Definition Classes
- QueryPlan
- Annotations
- @transient()
- 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. 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
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- def timeTakenMs(body: => Unit): Long
Records the duration of running
bodyfor the next query progress update.Records the duration of running
bodyfor the next query progress update.- Attributes
- protected
- Definition Classes
- StateStoreWriter
- val timeoutConf: GroupStateTimeout
- Definition Classes
- FlatMapGroupsInPandasWithStateExec → FlatMapGroupsWithStateExecBase
- 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]): FlatMapGroupsInPandasWithStateExec.this.type
- Definition Classes
- QueryPlan
- def transformAllExpressionsWithPruning(cond: (TreePatternBits) => Boolean, ruleId: RuleId)(rule: PartialFunction[Expression, Expression]): FlatMapGroupsInPandasWithStateExec.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]): FlatMapGroupsInPandasWithStateExec.this.type
- Definition Classes
- QueryPlan
- def transformExpressionsDown(rule: PartialFunction[Expression, Expression]): FlatMapGroupsInPandasWithStateExec.this.type
- Definition Classes
- QueryPlan
- def transformExpressionsDownWithPruning(cond: (TreePatternBits) => Boolean, ruleId: RuleId)(rule: PartialFunction[Expression, Expression]): FlatMapGroupsInPandasWithStateExec.this.type
- Definition Classes
- QueryPlan
- def transformExpressionsUp(rule: PartialFunction[Expression, Expression]): FlatMapGroupsInPandasWithStateExec.this.type
- Definition Classes
- QueryPlan
- def transformExpressionsUpWithPruning(cond: (TreePatternBits) => Boolean, ruleId: RuleId)(rule: PartialFunction[Expression, Expression]): FlatMapGroupsInPandasWithStateExec.this.type
- Definition Classes
- QueryPlan
- def transformExpressionsWithPruning(cond: (TreePatternBits) => Boolean, ruleId: RuleId)(rule: PartialFunction[Expression, Expression]): FlatMapGroupsInPandasWithStateExec.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 updateOuterReferencesInSubquery(plan: SparkPlan, attrMap: AttributeMap[Attribute]): SparkPlan
- Attributes
- protected
- Definition Classes
- QueryPlan
- 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(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException]) @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
- lazy val watermarkExpressionForEviction: Option[Expression]
Generate an expression that matches data older than the state eviction watermark
Generate an expression that matches data older than the state eviction watermark
- Definition Classes
- WatermarkSupport
- lazy val watermarkExpressionForLateEvents: Option[Expression]
Generate an expression that matches data older than late event filtering watermark
Generate an expression that matches data older than late event filtering watermark
- Definition Classes
- WatermarkSupport
- lazy val watermarkPredicateForDataForEviction: Option[BasePredicate]
- Definition Classes
- WatermarkSupport
- lazy val watermarkPredicateForDataForLateEvents: Option[BasePredicate]
Predicate based on the child output that matches data older than the watermark for late events filtering.
Predicate based on the child output that matches data older than the watermark for late events filtering.
- Definition Classes
- WatermarkSupport
- lazy val watermarkPredicateForKeysForEviction: Option[BasePredicate]
Generate an expression that matches data older than the state eviction watermark
Generate an expression that matches data older than the state eviction watermark
- Definition Classes
- WatermarkSupport
- lazy val watermarkPredicateForKeysForLateEvents: Option[BasePredicate]
Predicate based on keys that matches data older than the late event filtering watermark
Predicate based on keys that matches data older than the late event filtering watermark
- Definition Classes
- WatermarkSupport
- val watermarkPresent: Boolean
- Attributes
- protected
- Definition Classes
- FlatMapGroupsWithStateExecBase
- def withNewChildInternal(newChild: SparkPlan): FlatMapGroupsInPandasWithStateExec
- Attributes
- protected
- Definition Classes
- FlatMapGroupsInPandasWithStateExec → UnaryLike
- final def withNewChildren(newChildren: Seq[SparkPlan]): SparkPlan
- Definition Classes
- TreeNode
- final def withNewChildrenInternal(newChildren: IndexedSeq[SparkPlan]): SparkPlan
- Definition Classes
- UnaryLike