class PlanExecutorNative extends PlanExecutor[Jena, RDD[Triple], Node, Triple, RDFGraphNative] with Logging
An executor that works on the the native Scala data structures and uses Spark joins, filters etc.
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- new PlanExecutorNative(sc: SparkContext)
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- implicit class EnrichedWithToTuple[A] extends AnyRef
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- def applyFilter[T <: Product](condition: Expression, childExpressions: List[Expression], rdd: RDD[T]): RDD[T]
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- def asKeyValue(tuple: Product, keyPositions: Seq[Int]): (Product, Product)
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def
execute(plan: Plan, graph: RDFGraphNative): RDFGraphNative
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- PlanExecutorNative → PlanExecutor
- def executePlan[T >: Product, U <: Product](logicalPlan: LogicalPlan, triples: RDD[Product]): RDD[Product]
- def expressionsFor(expr: Expression, isJoin: Boolean = false): List[Expression]
- def expressionsFor(logicalPlan: LogicalPlan): List[Expression]
- def extract[T <: Product](tuple: T, positions: Seq[Int], aliases: Seq[(Int, Expression)]): Product
- def genMapper[A, B](f: (A) ⇒ B): (A) ⇒ B
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logger: Logger
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- def mergeKeyValue(pair: (Product, (Product, Product)), joinPositions: Seq[Int]): Product
- def mergedRDD(tuples: RDD[(Product, (Product, Product))], joinPositions: Seq[Int]): RDD[Product]
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- def performJoin(leftRDD: RDD[Product], rightRDD: RDD[Product], leftExpressions: List[Expression], rightExpressions: List[Expression], joinCondition: Expression): RDD[Product]
- def performProjection(rdd: RDD[Product], projectList: Seq[NamedExpression], child: LogicalPlan): RDD[Product]
- def performProjection(rdd: RDD[Product], projectList: Seq[Expression], childExpressions: Seq[Expression], joinConditions: Seq[EqualTo]): RDD[Product]
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- def toPairRDD[T >: Product](tuples: RDD[Product], joinPositions: Seq[Int]): RDD[(Product, Product)]
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