bw olap aggregation

8/6/2019 BW OLAP Aggregation

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BW OLAPAggregat ion

Lothar Schubert, BW RIG

SAP Labs America, LLC

March 2003


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SAP AG 2002, Title of Presentation, Speaker Name 2

NoData

WithData

In t r oduct ion The Role of the OLAP Engine

Master Data

BasicInfoCube

MultiProvider

InfoSet

InfoPr

oviderInterface

ODS Object

OLAPEngine

Business

Explorer

VirtualInfoCube


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Overview

KF/CKF Properties and Exception Aggregation

OLAP Processor Under the Hood

Case Study Revenue Calculation

Calculation with Reference to Characteristic

Formula Collision

Percentage and Summary Functions


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Overview





Formula Collision



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Ex c ept ion Aggregat ion Set t ings on K F Level

Department Headcount Month Headcount

D1 100 1/3/03 160

D2 80 2/3/03 180

Result 180


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Ex cept ion Aggregat ion - Count ing

CNT: Counting of all values with respect to reference characteristic

Business Scenario: How many different materials does a customerhave "Open Orders" for?

Drilldown


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Ex cept ion Aggregat ion - Average

Calculation Steps

Aggregate values

using standardaggregation

Aggregate valuesusing exceptionaggregation

Drill-down by Materialexplains result

309 = ( 225 + 20 + 630+ 360) / 4

AVG: Average of all values with respect to reference characteristic

Business Scenario: Average "Open Order Qty" per Material

Drilldown


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Exc ept ion Aggregat ion Fi rs t & Last Va lue

FIR, LAS Exception Aggregation (see note 310791)

Should only be used with non-cumulative key figures

Generally use time characteristic as reference characteristic

If being used for cumulative key figures:Completeness of values with respect to reference characteristicnecessary.

If being used with non time char. as reference characteristic:Sorting is done ascending according to key (internal presentation)

Plant Posting Date Value

1 06/15/03 25

1 06/16/03 15

2 06/15/03 20

Plant Posting Date Value

1 15


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K ey Figure (Selec t ion, Form ula) Propert ies

Note, that the thosecalculations always act ondisplayed data only


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CK F Aggregat ion Behavior Ass ignment

Complexity Assignment, if of type= KF

Exception Aggregation Behavior (and reference) can be set freely Default is setting of underlying Basic KF

PROPERTIES


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CK F Aggregat ion Behavior Simple

Complexity Simple, if exclusively operands of same aggregation, where

operands can have complexity Simple themselves (KF, Constants, CKF) Before / After Aggregation can be set


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CK F Aggregat ion Behavior Complex

Complexity Complex applies to all other cases

Enhance options are not ready for input (greyed out) Calculation always occurs after aggregation


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Overview





Formula Collision



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OLAP Ini t ia l izat i on

Check Authorizations

Is it ok to execute query?

Is it ok to read data from InfoProvider?

Process Variables

Exit for global variables (before variable input) is processed

Prompt for variable input

Exit for global variables (that failed before input) is processed

Variable values are distributed to fixed filter, hierarchy settings, dynamicfilter, conditions & exceptions, formulas,

Initialize OLAP Processor

Notify Presentation hierarchies (if used)

Check time stamps for OLAP cache (and release respective Ids)


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OLAP Proc essor i n Detai l I

1. OLAP request arrives from client

Request for free characteristics

Request for Dynamic filters2. Include additional characteristics necessary for aggregation /

calculation. For example:

Exception aggregation

Elimination of internal business volume

Formula variables with replacement from attribute value, if used inrestricted key figure (RKF)

3. Check authorization for navigation state (where necessary)

4. Search for Cached data in OLAP Cache

Skip steps 5-14 and go to step 15 if cached data is found


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OLAP Proc essor i n Detai l I I

5. Request data from database

6. Receive data from database Data arrives in blocks up to 1000 rows

Data is still separated by InfoProvider (in case of MultiProvider)

Data is still separated by Aggregate of InfoCube

Data is still separated into cumulative and non-cumulative key figures

7. Call BusinessAdd-In Virtual Characteristics and Key Figures

8. Check global filters (if not already done by database)9. Add attributes values for variables with replacement from attribute

used in RKF

10.Separate data according to RKFs and selections in structureelements

11.Perform currency translation

12.Process sums and calculated key figures (CKFs)before aggregation

13.Aggregate data to detail level (see 2.)

14.Perform Hierarchy aggregation

ifOLAPCacheis

NOTutilized


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OLAP Proc essor in Det ai l I I I

15.Filter and aggregate data (result lines)

16.Perform Elimination of Internal Business Volume (where applicable)

17.Perform Exception aggregation

18.Execute Currency/Unit aggregation

19.Add attributes values for variables with replacement from attributeused in formulas

20.Calculate formulas and CKFs after aggregation Check Currencies/Units

21.Perform List Operations, e.g.

Sort

Conditions

Local calculations/aggregations

Cumulated values


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Overview





Formula Collision



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OLAP Engine, w / Ex am ple of Revenue Calc ulat ion

KH_ATTRIBUTE_REPLACEMENT

Calendar year

Key Figures Quantity, CKF (QU * PR)

KHMAT2

KHMAT2 Quantity CKF (QU * PR)

M1 11.000 PC $ 110.00000 PC

M2 15.000 PC $ 300.00000 PC

Overall Result 26.000 PC $ 410.00000 PC

KH_ATTRIBUTE_REPLACEMENT

Calendar year

Key Figures Quantity, CKF (QU * PR)

KHMAT2

Calendar year Quantity CKF (QU * PR)

2001 12.000 PC $ 190.00000 PC

2002 14.000 PC $ 220.00000 PC


InfoCube contains field Quantity

Material Attribute contains field Price

Revenue should be calculated by the OLAP Processor


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Dat a Model (1)

InfoCube Definition

Key Figure Quantity


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Dat a Model (2)

InfoCube Definition

Price Attributes


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Data

InfoCube

Material Master


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Formula Var iable, based on At t r ibute Value

Create


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1. Try: Usage in Form ula

KHMAT2 Quantity 'KHF1' * 'Quantity'

M1 11.000 PC $ 110.00000 PC

M2 15.000 PC $ 300.00000 PCOverall Result 26.000 PC X

Calendar year Quantity 'KHF1' * 'Quantity'

2001 12.000 PC X

2002 14.000 PC X

Overall Result 26.000 PC X

Formula Editor


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2. Try: RK F, Before Aggregat ion (1)

C

reate

Properties

Price


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2. Try: RK F, Before Aggregat ion (2)

KHMAT2 Quantity KHK1_BEFORE

M1 11.000 PC $ 20.00

M2 15.000 PC $ 40.00

Overall Result 26.000 PC $ 60.00

Calendar year Quantity KHK1_BEFORE

2001 12.000 PC $ 30.00

2002 14.000 PC $ 30.00


Quantity = AVG, CKF, Before

Material Year Quantity Price

M1 2001 5 10

M1 2001 6 10

M2 2002 7 20

M2 2002

Material Year Quantity PriceM1 11 20

M2 15 40

Result 26 60

Query Definition

OLAP Processor

Explanation


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3. Try: RK F, Af t er Aggregat ion

KHMAT2 Quantity KHK1_AFTER

M1 11.000 PC $ 10.00M2 15.000 PC $ 20.00


Calendar year Quantity KHK1_AFTER

2001 12.000 PC $ 30.00

2002 14.000 PC $ 30.00


Quantity = SUM, CKF, After


M1 2001 11

M2 2001 15


M1 11 10

M2 15 20

Result 26 30

OLAP Processor

Explanation


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4. Try: Form ula, using CKF from before

KHMAT2 Quantity KHK1_AFTER 'Quantity' * 'KHK1_AFTER'

M1 11.000 PC $ 10.00 $ 110.00000 PC

M2 15.000 PC $ 20.00 $ 300.00000 PC

Overall Result 26.000 PC $ 30.00 $ 780.00000 PC

Calendar year Quantity KHK1_AFTER 'Quantity' * 'KHK1_AFTER'2001 12.000 PC $ 30.00 $ 360.00000 PC

2002 14.000 PC $ 30.00 $ 420.00000 PC

Overall Result 26.000 PC $ 30.00 $ 780.00000 PC

Quantity = SUM, CKF, After Qu * Pr = Formula

Material Year Quantity Price Qu * Pr

M1 2001 5M1 2002 6

M2 2001 7

M2 2002 8


2001 12 30 360

2002 14 30 420

Result 26 30 780

Quantity = SUM, CKF, After Qu * Pr = Formula


M1 2001 5

M1 2002 6

M2 2001 7

M2 2002 8


M1 11 10

M2 15 20Result 26 30


M1 11 10 110

M2 15 20 300

Result 26 30 780

OLAP Processor

Explanation


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5. Try: Revenue Calc ulat ion w i t hin RK F (1)


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5. Try: Revenue Calc ulat ion w i t hin RK F (2)

KHMAT2 Quantity CKF (QU * PR)

M1 11.000 PC $ 110.00000 PC

M2 15.000 PC $ 300.00000 PC


Calendar year Quantity CKF (QU * PR)

2001 12.000 PC $ 190.00000 PC

2002 14.000 PC $ 220.00000 PC


Quantity = SUM, CKF, After Qu * Pr = CKF


M1 2001 5

M1 2002 6

M2 2001 7

M2 2002 8

Material Year Quantity Price Qu * PrM1 11 10 110

M2 15 20 300

Result 26 30 410

OLAP Processor

Explanation


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Some addi t ional Not es

Be careful when using multiple aggregation types (see example below,for a mix of before and after).

Allowed in CKF:

= KF * Attribute, e.g. = Quantity * Price

= KF / Attribute, e.g. = Quantity / Price

Not allowed in CKF (i.e. leading potentially to unwanted results):

= Attribute, e.g. = Price

= Attribute / KF e.g. = Price / Quantity

Performance impacts, in case of before aggregation All required records have to be read into OLAP processor (and processed individually)

No aggregates cannot be applied

In case of MultiProviders

Datasets are processed individually per InfoProvider first

In case of Inventory (non cumulative) InfoCubes

Before aggregation does not allow formulas with mix of KF types

Always consider calculation already in UpdateRules (see Note 379832)KHMAT2 Quantity KHK1_BEFORE KHK1_AFTER CKF (QU * PR)

M1 11.000 PC $ 20.00 $ 20.00 $ 110.00000 PC

M2 15.000 PC $ 40.00 $ 40.00 $ 300.00000 PC

Overall Result 26.000 PC $ 60.00 $ 60.00 $ 410.00000 PC

Calendar year Quantity KHK1_BEFORE KHK1_AFTER CKF (QU * PR)

2001 12.000 PC $ 30.00 $ 30.00 $ 190.00000 PC

2002 14.000 PC $ 30.00 $ 30.00 $ 220.00000 PC

Overall Result 26.000 PC $ 60.00 $ 60.00 $ 410.00000 PC


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Overview





Formula Collision



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Mot ivat ion

Mostly, the OLAP first aggregates data and then applies

calculations

Sometimes you would like to change this sequence(however you do not want to use before aggregation for allcharacteristics combinations, due to performance reasons)

Example Cube Data:

Here, it would be ok to aggregate first by Material and Month, butits required to perform the calculation prior to aggregation onOrder.

Price per Unit


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A f te r Aggrega t ion w ou ld del i ve r w rong resul t s


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Usage of Re fe rence to Charac t e r i st i c (1 )


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Usage of Re fe rence to Charac t e r i st i c (3 )

This attribute is available for every Characteristic (also 2.0b/2.1c)

Also here: Consider performance impacts

Perhaps calculation can already occur in Update Rules.


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Overview


OLAP Processor Under the Hood Case Study Revenue Calculation


Formula Collision



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Form ula Col l is ion

Q uant ity Q uantit y 'Q uantity ' * 'Quant it y'

2001 12.000 P C 12.000 P C 144.00000 P C^2

2002 14.000 P C 14.000 P C 196.00000 P C^2

S um m ary 26 P C 26 P C 676.00000 P C^2


2001 12.000 P C 12.000 P C 144.00000 P C^2

2002 14.000 P C 14.000 P C 196.00000 P C^2

S um m ary 26 P C 26 P C 676.00000 P C^2


2001 12.000 P C 12.000 P C 144.00000 P C^2

2002 14.000 P C 14.000 P C 196.00000 P C^2

S um m ary 26 P C 26 P C 340.00000 P C^2

Available in case of formulas with multiple structures,under Formula Properties.

Collisions always occur when point and dash calculations orfunctions are mixed in competing formulas.

If you do not make a definition, the formula that was set(defined and saved) last takes priority.

+

*


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Overview


OLAP Processor Under the Hood Case Study Revenue Calculation


Formula Collision



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Percent age Funct ions (1)

a%b difference in percentage:How much does a value deviate from the absolute amount of b: = (a-)/abs(b)?

a%Ab share in percentage:How large is a share a for the total value b: = a/abs(b)

%CTa share in terms of percentage for the result:The value of the key figure a is related to the next higher value that is aggregated (the

"subresult" of a with respect to a characteristic is 100%).

GTa share in terms of percentage for the total result:The value of the key figure a is related to the aggregated value for all characteristics (the"result" of the entire table for the key figure a is 100%).

%RTa share in terms of percentage for the report result:The value of the key figure a is related to the aggregated value for all characteristics, forwhich the dynamic filter is ignored. If, for example, a free characteristic is restricted by afilter value, the global result of the key figure a in the displayed table is not 100%. The

aggregation via all filter values results in 100%.


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Percent age Funct ions (2)

KHMAT2

KHMAT2 Calendar year Quant ity 'Quant ity' % 10 'Quant ity' %A 10 %CT 'Quant ity' %GT 'Quant ity' %RT 'Quant ity'

M1 2001 5.000 PC -50.00000 % 50.00000 % 45.45455 % 19.23077 % 19.23077 %

2002 6.000 PC -40.00000 % 60.00000 % 54.54545 % 23.07692 % 23.07692 %

Result 11.000 PC 10.00000 % 110.00000 % 42.30769 % 42.30769 % 42.30769 %

M2 2001 7.000 PC -30.00000 % 70.00000 % 46.66667 % 26.92308 % 26.92308 %

2002 8.000 PC -20.00000 % 80.00000 % 53.33333 % 30.76923 % 30.76923 %

Result 15.000 PC 50.00000 % 150.00000 % 57.69231 % 57.69231 % 57.69231 %

Overall Result 26.000 PC 160.00000 % 260.00000 % 100.00000 % 100.00000 % 100.00000 %

KHMAT2 M1

Calendar year Quant ity 'Quant ity' % 10 'Quant ity' %A 10 %CT 'Quant ity' %GT 'Quant ity' %RT 'Quant ity'2001 5.000 PC -50.00000 % 50.00000 % 45.45455 % 45.45455 % 19.23077 %

2002 6.000 PC -40.00000 % 60.00000 % 54.54545 % 54.54545 % 23.07692 %

Overall Result 11.000 PC 10.00000 % 110.00000 % 100.00000 % 100.00000 % 42.30769 %

a%b difference in percentage a%Ab share in percentage %CTa share in terms of percentage for the result GTa share in terms of percentage for the total result %RTa share in terms of percentage for the report result


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Summ ary Func t ions

KHMAT2

KHMAT2 Calendar year Quant ity SUMCT 'Quant ity' SUMGT 'Quant ity ' SUMRT 'Quantity '

M1 2001 5.000 PC 11.000 PC 26.000 PC 26.000 PC

2002 6.000 PC 11.000 PC 26.000 PC 26.000 PC

Result 11.000 PC 26.000 PC 26.000 PC 26.000 PC

M2 2001 7.000 PC 15.000 PC 26.000 PC 26.000 PC

2002 8.000 PC 15.000 PC 26.000 PC 26.000 PC

Result 15.000 PC 26.000 PC 26.000 PC 26.000 PC

Overall Result 26.000 PC 26.000 PC 26.000 PC 26.000 PC

KHMAT2 M1

Calendar year Quant ity SUMCT 'Quant ity ' SUMGT 'Quant ity' SUMRT 'Quant ity'

2001 5.000 PC 11.000 PC 11.000 PC 26.000 PC

2002 6.000 PC 11.000 PC 11.000 PC 26.000 PC

Overall Result 11.000 PC 11.000 PC 11.000 PC 26.000 PC

SUMGTaThe value of the key figure a is related to the aggregate value via all characteristics.Aggregation is completed using the deepest-level characteristic.

SUMCTaThe value of the key figure a is related to the next highest aggregate value.

SUMRTaThe value of the key figure a is related to the aggregate value of all characteristics inwhich the dynamic filter is ignored.


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