摘要：Hyperion reading book
index driven types
Label Only and Shared Member are index based, Members whith these storage types,When
incorporate dimension defined as sparse. Are actually index pointers to other members stored
in the Analytic services Page file in the form of data blocks
Label Only Member have an index to the first child with an Add(+) consolidation operator
,or the first child if all children have an Ignore(~) consolidation operator,There may be some v-
ariability in this defined behavior in actual situations
Share member members have an index to main member whose name it bears,Shared
Members generally follow the main member in the outline they point to through the index
Share Member
the share member assumers attributes of the main member(its value,aliases,time balance
flags and so forth)except the member’s consolidation operator.
share member have their consolidation operation independent from the main member’s
value they share,This facilitates building complex models with computation dependencies
between members
Formulas in Outlines Versus in calc scripts
Use formulats in outlines where :
The member calculations are straightforward without complex order of calculation dependencies
The member requires a Two Pass Calc operation and is flagged as such,and not other
back caculation of other members is required to be performed in a calc script after the main
calc All of Calc Dim statement
The member requires a Two Pass Calc operation and is flagged as such ,and the conditions
are otherwise met for accomplishing a two For The Price of One Calculation
The member’s data storage type is Dynamic Calc or Dynamic Calc And Store
note: Formlas For Dynamic Calc members cannot be executed within a calc scripts
User Defined Attributes(UDAs)
Use UDAs is a way to avoid setting up additional dimensions where member identification
is not hierarchical
Attribute Dimensions
Attribute dimensions is help further assign characteristics to give members in an outline
Attribute dimensions add no overhead in terms of database size. They are dynamic
dimensions with no storage requirements
Calculation of the Attribute dimensions is deferred until they are requested in a report
Attribute Dimensions are drillable so that a report can show the specified attribute dimension
across all the other dimensions in the model.
Attribute dimensions can be of different types ,-- text ,numeric,boolean and date
A given member within a dimension may be assigned one or more attributes ,or no attributes
at all.
attribute dimensions may be created and loaded to specificmembers using load rules
Ground Rules
Follow these general when creating attribute attribute dimensions
1. Base dimensions must be sparse. Base dimensions are the dimensions associated with
the attribute dimension.
2. Attribute dimensions don’t have consolidation symbols of formulas attached to them.All
calculations are done across the base dimensions
3. Although Attribute dimensions can have multi-tiered hierarchy,you must associate the level 0
members(bottom level members)of attribute dimensions with base dimensions members.
4. Base dimension members associated with attribute dimensions must be at the same level.
this can be any level but it must be the same across the base dimension.
5. Do not tag shared members in the base dimension with attribute dimension members,
Shared members automatically inherit their respective stored member attributes
