Type Members

1.  type DataFrame = Dataset[Row]
2.  case class DoubleFieldStatAccumulator(nulls: LongAccumulator, nonNulls: LongAccumulator, sum: DoubleAccumulator, mins: CollectionAccumulator[Double], maxs: CollectionAccumulator[Double], m2: DoubleAccumulator) extends FieldStatAccumulator with Product with Serializable
3.  sealed trait FieldStatAccumulator extends Serializable
4.  case class Interim(outputFunction: InterimOutput, subgraph: String, component: String, port: String, subPath: String, numRows: Int, child: LogicalPlan, detailedStats: Boolean = false) extends LogicalPlan with UnaryLike[LogicalPlan] with IgnoreCachedData with Product with Serializable

   IgnoreCachedData:- To ignore caching in planning phase.

   IgnoreCachedData:- To ignore caching in planning phase. In planning phase we re-compute each and every node/step in tree repeatdly. and try to replace it with computed version of the node. this helps to not re-compute things of the tree which are already computed.

   Add this trait if you want to force the re-computation of the plan.

5.  case class InterimExec(outputFunction: InterimOutput, subgraph: String, component: String, port: String, subPath: String, child: SparkPlan, numRows: Int, detailedStats: Boolean, sparkSession: SparkSession) extends SparkPlan with InterimExec2 with Product with Serializable
6.  trait InterimExec2 extends SparkPlan
7.  trait InterimOutput extends Serializable
8.  case class InterimOutputHive2(session: String, workflowID: String, workflowVersion: String, jobid: String) extends Serializable with InterimOutput with Product
9.  case class InterimStat(dataFrameSchema: StructType, basicStats: Boolean, statsAccs: Array[FieldStatAccumulator], rowAccumulator: CollectionAccumulator[InterimRow], counterAccumulator: LongAccumulator, partitionCounter: LongAccumulator, rowAccSchema: StructType, schema: StructType, numPartitions: Int, numRows: Int, schemaJson: Seq[InternalRow], schemaSchema: StructType) extends Serializable with Product
10.  case class InterimStore(sparkSession: SparkSession, interims: LinkedHashMap[RDDInterimKey, InterimStat] = ...) extends LazyLogging with Product with Serializable
11.  case class InterimStrategy(spark: SparkSession) extends SparkStrategy with Product with Serializable

    Spark strategy converts logical plan to sequence of spark plan.

    Spark strategy converts logical plan to sequence of spark plan. This class represents custom interim strategy. Logical operators other than Interim are converted using the regular SparkStrategy which is applied because of planLater method

    * GenericStrategy.planLater scala doc: Returns a placeholder for a physical plan that executes plan. This placeholder will be filled in automatically by the QueryPlanner using the other execution strategies that are available.

12.  case class LongFieldStatAccumulator(nulls: LongAccumulator, nonNulls: LongAccumulator, sum: LongAccumulator, mins: CollectionAccumulator[Long], maxs: CollectionAccumulator[Long], m2: LongAccumulator) extends FieldStatAccumulator with Product with Serializable
13.  case class OtherFieldStatAccumulator(nulls: LongAccumulator, nonNulls: LongAccumulator) extends FieldStatAccumulator with Product with Serializable
14.  class ProphecyDataFrame extends AnyRef
15.  class ProphecyListener extends SparkListener with LazyLogging
16.  type Strategy = SparkStrategy

    Annotations

    @DeveloperApi() @Unstable()

17.  case class StreamQueryListener(query: io.prophecy.libs.StreamingTarget, maxEmptyTicks: Int = 3) extends StreamingQueryListener with Product with Serializable
18.  case class StringFieldStatAccumulator(nulls: LongAccumulator, nonNulls: LongAccumulator, mins: CollectionAccumulator[String], maxs: CollectionAccumulator[String]) extends FieldStatAccumulator with Product with Serializable