class SparkOptimizer extends Optimizer
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Instance Constructors
- new SparkOptimizer(catalogManager: CatalogManager, catalog: SessionCatalog, experimentalMethods: ExperimentalMethods)
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final
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!=(arg0: Any): Boolean
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final
def
asInstanceOf[T0]: T0
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final
def
batches: Seq[Batch]
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val
blacklistedOnceBatches: Set[String]
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def
clone(): AnyRef
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def
defaultBatches: Seq[Batch]
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def
earlyScanPushDownRules: Seq[Rule[LogicalPlan]]
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final
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eq(arg0: AnyRef): Boolean
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def
execute(plan: LogicalPlan): LogicalPlan
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def
executeAndTrack(plan: LogicalPlan, tracker: QueryPlanningTracker): LogicalPlan
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def
extendedOperatorOptimizationRules: Seq[Rule[LogicalPlan]]
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def
finalize(): Unit
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def
fixedPoint: FixedPoint
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final
def
getClass(): Class[_]
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hashCode(): Int
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def
initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
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def
initializeLogIfNecessary(isInterpreter: Boolean): Unit
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isInstanceOf[T0]: Boolean
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def
isPlanIntegral(plan: LogicalPlan): Boolean
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def
isTraceEnabled(): Boolean
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def
log: Logger
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logDebug(msg: ⇒ String, throwable: Throwable): Unit
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logInfo(msg: ⇒ String, throwable: Throwable): Unit
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def
logInfo(msg: ⇒ String): Unit
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def
logName: String
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logTrace(msg: ⇒ String, throwable: Throwable): Unit
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logTrace(msg: ⇒ String): Unit
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logWarning(msg: ⇒ String, throwable: Throwable): Unit
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logWarning(msg: ⇒ String): Unit
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def
ne(arg0: AnyRef): Boolean
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def
nonExcludableRules: Seq[String]
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final
def
notify(): Unit
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def
notifyAll(): Unit
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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.
Note that 'Extract Python UDFs' batch is an exception and ran after the batches defined here.
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def
preOptimizationBatches: Seq[Batch]
Optimization batches that are executed before the regular optimization batches (also before the finish analysis batch).
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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def
toString(): String
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wait(): Unit
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wait(arg0: Long): Unit
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object
Once extends Strategy with Product with Serializable
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- RuleExecutor
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object
OptimizeSubqueries extends Rule[LogicalPlan]
- Definition Classes
- Optimizer