SparkOptimizer

Instance Constructors

new SparkOptimizer(catalog: SessionCatalog, conf: SQLConf, experimentalMethods: ExperimentalMethods)

Type Members

case class Batch extends Product with Serializable

Attributes
protected
Definition Classes
RuleExecutor
case class FixedPoint extends Strategy with Product with Serializable

Definition Classes
RuleExecutor
abstract class Strategy extends AnyRef

Definition Classes
RuleExecutor

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
object Once extends Strategy with Product with Serializable

Definition Classes
RuleExecutor
final def asInstanceOf[T0]: T0

Definition Classes
Any
def batches: Seq[Batch]

Definition Classes
SparkOptimizer → Optimizer → RuleExecutor
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def execute(plan: LogicalPlan): LogicalPlan

Definition Classes
RuleExecutor
def extendedOperatorOptimizationRules: Seq[Rule[LogicalPlan]]

Definition Classes
Optimizer
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
val fixedPoint: FixedPoint

Attributes
protected
Definition Classes
Optimizer
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
def hashCode(): Int

Definition Classes
AnyRef → Any
def initializeLogIfNecessary(isInterpreter: Boolean): Unit

Attributes
protected
Definition Classes
Logging
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
def isTraceEnabled(): Boolean

Attributes
protected
Definition Classes
Logging
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
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
def postHocOptimizationBatches: Seq[Batch]

Optimization batches that are executed after the regular optimization batches, but before the batch executing the ExperimentalMethods optimizer rules.
Optimization batches that are executed after the regular optimization batches, but before the batch executing the ExperimentalMethods optimizer rules. This hook can be used to add custom optimizer batches to the Spark optimizer.
def preOptimizationBatches: Seq[Batch]

Optimization batches that are executed before the regular optimization batches (also before the finish analysis batch).
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

Definition Classes
AnyRef → Any
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( ... )

Related Doc: package execution

class SparkOptimizer extends Optimizer

Instance Constructors

new SparkOptimizer(catalog: SessionCatalog, conf: SQLConf, experimentalMethods: ExperimentalMethods)

Type Members

case class Batch extends Product with Serializable

case class FixedPoint extends Strategy with Product with Serializable

abstract class Strategy extends AnyRef

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

object Once extends Strategy with Product with Serializable

final def asInstanceOf[T0]: T0

def batches: Seq[Batch]

def clone(): AnyRef

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def execute(plan: LogicalPlan): LogicalPlan

def extendedOperatorOptimizationRules: Seq[Rule[LogicalPlan]]

def finalize(): Unit

val fixedPoint: FixedPoint

final def getClass(): Class[_]

def hashCode(): Int

def initializeLogIfNecessary(isInterpreter: Boolean): Unit

final def isInstanceOf[T0]: Boolean

def isTraceEnabled(): Boolean

def log: Logger

def logDebug(msg: ⇒ String, throwable: Throwable): Unit

def logDebug(msg: ⇒ String): Unit

def logError(msg: ⇒ String, throwable: Throwable): Unit

def logError(msg: ⇒ String): Unit

def logInfo(msg: ⇒ String, throwable: Throwable): Unit

def logInfo(msg: ⇒ String): Unit

def logName: String

def logTrace(msg: ⇒ String, throwable: Throwable): Unit

def logTrace(msg: ⇒ String): Unit

def logWarning(msg: ⇒ String, throwable: Throwable): Unit

def logWarning(msg: ⇒ String): Unit

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def postHocOptimizationBatches: Seq[Batch]

def preOptimizationBatches: Seq[Batch]

final def synchronized[T0](arg0: ⇒ T0): T0

def toString(): String

final def wait(): Unit

final def wait(arg0: Long, arg1: Int): Unit

final def wait(arg0: Long): Unit

Inherited from Optimizer

Inherited from RuleExecutor[LogicalPlan]

Inherited from Logging

Inherited from AnyRef

Inherited from Any

Ungrouped