prateeka

        val idx                 = idxMinus + 1
        val fd                  = hier.dimension
        val uniqueName          = MdxSelectorString(fd.name, hier.name)
        val allMemberExpression = s"$uniqueName.[All]"
        val (defaultMember, allMember) = hier.defaultMember match {
          case AllMember =>
            if (hier.isCalculationGroup) {
              (s"${hier.uniqueName}.&[${fd.calculationGroup.get.defaultMember.name}]", None)
            } else {
              (allMemberExpression, Some(allMemberExpression))

prateeka

      case mpv: MemberPropertyValue[_] =>
        calculationContext match {
          case FilterCalculationContext(FilterFlatLevel(flatLevel)) =>
            (mpv.property, mpv.typed) match {
              case (_: MemberNameProperty | _: MemberCaption, _) =>
                val v = resolveMDX(mpv.member)
                v.physicalType match {
                  case _: VariableStringType | NullType => v
                  case _                                => TypeConvertedValue(v, MaxStringType)
                }

prateeka

def handleExcelUnionForTopCountAndBottomCount(cube: Cube, queryAxes: Map[Int, Axis], targetLevel: FlatLevel) = {
    logger.warn("ExcelUnionBothTopBottomCount applied")

    // As we go down levels we have to build out the names and keys
    case class RowLevel(fl: FlatLevel, nameIndices: Seq[Int], keyIndices: Seq[Seq[Int]])

    def getRowLevels(levels: IndexedSeq[FlatLevel], idx: Int, rowIdx: Int, prevRowLevel: Option[RowLevel]): Seq[RowLevel] = {
      if (idx < levels.size) {
        val (prevNameIndices, prevKeyIndices) = prevRowLevel.map { p => (p.nameIndices, p.keyIndices) }.getOrElse((Seq.empty, Seq.empty))
        val level = levels(idx)

prateeka

   def makeSelectColumn(gb: GroupByType): Option[SelectColumn] = {
            gb match {
              case GroupByIgnore => None
              case _: GroupByColumnNumber => None
              case gbv@GroupByValue(_: ConstantValue, _) if findGroupByTypeColumn(gbv).isEmpty => None
              case _ =>
                val (exposed, expr) =
                  gb match {
                    case GroupByColumnName(name, _, Some(expression)) => (Some(name), expression)
                    case GroupByValue(_, expression) => (None, expression)

prateeka

 def makeSelectColumn(gb: GroupByType): Option[SelectColumn] = {
    gb match {
      case GroupByIgnore => None
      case _: GroupByColumnNumber => None
      case gbv@GroupByValue(_: ConstantValue, _) if findGroupByTypeColumn(gbv).isEmpty => None
      case _ =>
        val (exposed, expr) =
          gb match {
            case GroupByColumnName(name, _, Some(expression)) => (Some(name), expression)
            case GroupByValue(_, expression) => (None, expression)

prateeka

AggregateLogical(
  SelectedData(
    ColumnData(SelectColumn(Some(c0),DimensionallyModifiedValue(AggregatedValue(AttributeValue(FlatAttribute(ef1dd654-da9a-42bc-77ef-ea4431bdeb4e: "salesamount1")),Sum),List(Child(Child(CurrentMember(FlatHierarchy(d525ca44-1aa7-4c19-bfa7-ed6e69040b00+1298889108: "Order Date Month Hierarchy")),false),false))),NoAggregation), NoAggregation, Some(c0))
  ),
  AuxiliaryData(),
  AggregateLogical(
    SelectedData(
      DimensionallyModifiedData(ValueData(AggregatedValue(AttributeValue(FlatAttribute(ef1dd654-da9a-42bc-77ef-ea4431bdeb4e: "salesamount1")),Sum),NoAggregation,Set(RawAttribute(FlatAttribute(ef1dd654-da9a-42bc-77ef-ea4431bdeb4e: "salesamount1"),Sum,Some(c_36))),Some(c_37)),List(Child(Child(CurrentMember(FlatHierarchy(d525ca44-1aa7-4c19-bfa7-ed6e69040b00+1298889108: "Order Date Month Hierarchy")),false),false)),Min,Some(c_37))
    ),
    AuxiliaryData(),

prateeka

   case MdxFunctions.DistinctCount.Applied(valueSet :: HNil) =>
        val resolvedVal = ConstantValue(5, IntType)
        ComplexAggregatedValue(resolvedVal, resolveSetExpression(valueSet), core.DistinctCountExact)

prateeka

SELECT
    MIN(t_129.c0) AS c0,
    MIN(t_129.c_39) AS c1,
    t_129.c2 AS c2,
    t_129.c3s0 AS c3s0
FROM
    (
        SELECT
            MIN(t_128.c0) AS c0,
            MIN(t_128.c_39) AS c_39,

prateeka

SELECT
    MIN(t_101.c_44) AS c0,
    t_101.c1 AS c1,
    t_101.c2s0 AS c2s0
FROM
    (
        SELECT
            MIN(t_98.c_44) AS c_44,
            COALESCE(t_100.c_45, t_98.c1) AS c1,
            COALESCE(t_100.c_55, t_98.c2s0) AS c2s0

prateeka

OrderCube(
  AggregateLogical(
    SelectedData(
      ColumnData(SelectColumn(Some(c0),AttributeValue(FlatAttribute(62874bbe-7ead-48ac-4496-8c7758b5aaa8: "orderquantity1")),Sum), Sum, Some(c0)),
      ColumnData(SelectColumn(Some(c1),DimensionallyModifiedValue(AggregatedValue(AttributeValue(FlatAttribute(62874bbe-7ead-48ac-4496-8c7758b5aaa8: "orderquantity1")),Sum),List(Child(CurrentMember(FlatHierarchy(9bf44374-c106-4ab3-9c6a-d68474e9b25f+3938: "Product Dimension")),true))),NoAggregation), NoAggregation, Some(c1)),
      ColumnData(SelectColumn(Some(c2),AttributeValue(FlatAttribute(2ff18d3a-894a-4be1-6d5c-39d97245160a: "Product Line")),AggregateGrouped(true)), AggregateGrouped(true), Some(c2)),
      ColumnData(SelectColumn(Some(c3s0),KeyValue(FlatKey(3b0e5176-ca31-4706-a508-092e3c17daa2)),AggregateGrouped(true)), AggregateGrouped(true), Some(c3s0))
    ),
    AuxiliaryData(),
    UnionCubes(