BI2015 Berg Advanced Performance Optimization With SAP BW v05

7/24/2019 BI2015 Berg Advanced Performance Optimization With SAP BW v05

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Advanced performance

optimization with SAP BW 7.3

and SAP BW 7.4

r. !"arne !ergComerit



2

In #his Session

• $et practical tips and techni%&es for maintaining and cleaning an

SA' !W system for optimal performance, incl&ding 'SA

optimi(ation, compression, maintaining statistical c&)es, and

controlling gro*th, red&cing log file si(es, removing #' temporary

storage, #' error logs, and temporary data)ase o)"ects.

• +ed&ce the si(e of an SA' !W system )y as m&ch as 0- )y taing

steps s&ch as removing 'SAs, aggregating, and optimi(ing

InfoC&)es, and implementing the ne* /SA architect&re

•

o* to clean )atch ta)les and red&ce the footprints &nneededdata.

• /earn ho* to tae advantage of ne* performance feat&res in !W

.3 and !W .4



3

What Well Cover

•

!W .3 'erformance !asics• o&seholding tass in SA' !W .3 and .4

• emo6 7ptimal SA' !W .4 on A8A performance

• 12step preA8A migration clean&p tass

• emo6 !W .4 performance monitoring• !W 7ptimi(ation after A8A migration

• /SA vs. /SA 7ptimi(ation and S'7s

• Wrap&p



4

9:plore the &se of line item dimensions for fields thatare fre%&ently conditioned in %&eries. #his model

change can yield faster %&eries.

!W .3 ;nonA8A< InfoC&)e esign /ine Item imensions

• /ine item dimensions are )asically

fields that are transaction oriented

• 7nce flagged as a line item dimension,

the field is act&ally stored in the factta)le and has no ta)le "oins

#his may res&lt in improvements to %&ery speeds for c&)es not

in !WA or A8A



5

!W .3 ;nonA8A< InfoC&)e esign = igh Cardinality >lags

•

ighCardinality flag for large InfoC&)es *ith more than 10 million ro*s

• At this company there *ere 11 InfoC&)es *ith a ratio of more than 30- of the

records in the dimensions vs. fact ta)le

• SA' recommends for Inde:ing and performance reasons to flag these as ?high

cardinality@ dimensions. o*ever, it has minor impact to smaller c&)es.

• In this e:ample, there *ere fo&r medi&m and large InfoC&)es that are not

follo*ing the )asic design g&idelines, and s&)se%&ently had slo* performance

any companies sho&ld redesign large InfoC&)es *ith highcardinality to

tae advantage of the standard performance enhancements availa)le.

R e a l E x a m p l e



6

!W .3 ;nonA8A< S7 esign and /ocs on /arge 7racle #a)les

In this e:ample, many of the verylarge S7s are not partitioned,

and several o)"ects have over 250

million records

Additionally, 101 S7 o)"ects

*ere flagged as )eing reporta)le.#his res&lted in System Is ;SIs<

)eing created d&ring activation.

Com)ined, these res&lted in

fre%&ent locs on the 7racle

data)ase and failed parallelactivation "o)s

'artition S7s. #he loc on very large S7s d&ring parallel loads are *ellno*n and SA' has iss&ed several notes on the topic6 B3445 D7S o)"ect6

Activation fails 9A/7CED and 434 D7racle deadlocs, 7+A000B0.D




• SA' 8etWeaver !W .3 has a ne*, step)ystep *i(ard that allo*s yo& to generate data

flo*s from flat files or e:isting data so&rces

•A great )enefit is that the *i(ards

*or against any Info'roviderF

i.e., yo& can &se the *i(ards to

create loads from S7s to S7s

or InfoC&)es

#his *i(ard red&ces the n&m)er or man&al steps needed to load data. It

also simplifies the development process and maes 9#/ *or m&ch easier.

#he !W .3 ata>lo* $eneration Wi(ard



ata)ase 'erformance ;nonA8A systems<

• ata)ase statistics are &sed )y the

data)ase optimi(er to ro&te %&eries.

7&tdated statistics leads to

performance degradation.

• 7&tdated inde:es can lead to very poor search performance in all

%&eries *here conditioning is &sed ;i.e., mandatory prompts<

• #he c&rrent sampling rates for this e:ample *ere too lo*, and

statistics sho&ld only )e r&n after ma"or data loads, and co&ld )esched&led *eely

>or many systems, data)ase statistics are o&tdated and may ca&se data)aseperformance to perform significantly poorer than other*ise *o&ld )e the case.

Sampling sho&ld often )e changed and process chains may )e resched&led.




•

#he 7/A' Cache is )y defa&lt 100 ! for local and 200 !for glo)al &se

• #he system at this company *as cons&ming no more than

0! on average

• #his means that most %&eries *ere ree:ec&ting the same

data ;good hit ratio of over G0-<

#he 7/A' emory Cache Si(e Htili(ation




SA' A8A and !W .4

>or !W .4 on A8A, SA' has contin&ed to move more of the process intensive

f&nctions from the application to the ! server

#he )enefits of this approach are dramatically faster dataactivation, data transformations, and %&ery e:ec&tions

• #his taes advantage of the performance improvements of an inmemory !

• It also red&ces the need for data transfers )et*een application and ! server



What Well Cover

•






• Wrap&p



'reSteps = Cleaning &p o&r !W System

• o& can save significant amo&nts of *or )y doing a

clean&p effort )efore yo& start yo&r A8A migration

or !W &pgrade pro"ect

• >or e:ample, an international company had a !W system *ith over

10 #!, *ith only 3B #! in the prod&ction )o: and the remaining

data on their 8ear/ine Storage ;8/S< sol&tion

• #his cleaned !W system saved them potentially millions of dollars

in hard*are and A8A licensing costs

It is not &n&s&al to red&ce a !W system

si(e )y 2030- d&ring a clean &p effort



#he SA'J!WJ7HS9E99'I8$ #as /ist

• If yo& are on .0 S'32 of higher, yo& can generate an SA' !W o&seeeping tas

list and get a&tomated help in cleaning the system *ees )efore &pgrading it

o& first have to install the program from SA' 8ote 12G2 )efore yo& cangenerate the SA'J!WJ7HS9E99'I8$ tas list &sing tcode S#C01

. +eassign re%&ests *ritten into the incorrect 'SA partition

. Kerify ataSo&rce segments assignment to 'SA

G. eletes the entries no longer re%&ired in ta)le +SILW10. Clear all 7/A' Cache parameters

11. +epair InfoC&)e fact ta)le indices at ata ictionary level

12. +eorgani(e and delete )oomar Is M vie* Is

1. Checs !W metadata *ith IC

2. elete +S## traces

3. elete !W statistical data 4. elete Aggregate data via deactivation

5. 9ns&re partitioned ta)les are correctly

inde:ed for 'SA

B. 9ns&re re%&est consistencies in the 'SA



A #ool to elp to igrate and Clean Hp

• SA' has created a cocpit to6 Clean &p the SA' !W system +ed&ce system si(e Cond&ct prechecs

;readiness checs< Si(e the system >ind s&)optimal code ;i.e.,

transformations< /oo at ta)le distri)&tions

and loads

#here are over 235 tests in this

tool #hese tools are thans to SA's arc !ernard

and his team at SA' /a)s Canada



ore #ips to ae the ata)ase Smaller

•

Hse *riteoptimi(ed S7s as first level data stores. #hese caneasily )e offloaded o&t of main memory in A8A and save yo& money.

• Eeep yo&r 'ersistent Staging #a)les ;'SA< clean. !#W6 #he 'SA is often not

needed at all in !W .4.

• If yo& are on !W .3 Service 'ac and A8A *ith at least Service 'ac 5,

the *riteoptimi(ed S7s and 'SAs are flagged as ?early &nload@ from the

A8A memory. #his *ill help yo& eep the system smaller and re%&ire less

memory.

• o& can also flag other InfoC&)es, S7s, ta)les, and partitioned as ?not

active@. If yo& do so, they *ill only )e loaded into memory *hen act&ally

re%&ired.

#he si(ing program in SA' 8ote 13BGB taes these si(esavings settings into acco&nt *hen si(ing yo&r A8A system



16

What Well Cover

•






• Wrap&p



17

emo6 7ptimal SA' !W on A8A performance



18

What Well Cover

•






• Wrap&p



19

12 'reSteps = Cleaning &p o&r !W System

1. Clean the 'ersistent Staging Area ;'SA< for data already loaded to S7s.2. elete the Aggregates ;s&mmary ta)les<. #hey *ill not )e needed again.

3. Compress the 9 and > ta)les in all InfoC&)es. #his *ill mae InfoC&)es

m&ch smaller.

4. +emove data from the statistical c&)es ;they start *ith the technical

name of 0C#CJ:::<. #hese contain performance information for the !Wsystem r&nning on the relational data)ase. o& can do this &sing the

transaction +SS#A# or the program +SS#A#JA#AJ9/9#9 to help

yo&.

5. /oo at the log files, )oomars, and &n&sed !9: %&eries and templates

;transaction +SN9/9#9<.

B. +emove as m&ch as possi)le of the #' temporary storage, #' error

logs, and temporary data)ase o)"ects. elp and programs to do this

are fo&nd in SA' 8otes 113G3GB and 110B3G3.



20

12 'reSteps = Cleaning &p o&r !W System ;cont.<

. >or *riteoptimi(ed S7s that p&sh data to reporta)le

S7s ;/SA approach<, remove data in the *rite

optimi(ed S7s. It is already availa)le in higher level o)"ects.

. igrate old data to 8ear/ine Storage ;8/S< on a smallserver. #his *ill still provide access to the data for the fe* &sers *ho

infre%&ently need to see this old data. o& *ill also )e a)le to %&ery it

*hen !W is on A8A, )&t it does not need to )e inmemory.

G. +emove data in &n&sed S7s, InfoC&)es, and files &sed for staging inthe !W system. #his incl&des possi)le reorgani(ation of master data

te:t and attri)&tes &sing process type in +S'C.



21

12 'reSteps = Cleaning &p o&r !W System ;cont.<

10. o& may also *ant to clean &p )acgro&nd information stored in theta)le +S!A#CA#A. #his ta)le can get very )ig if not managed. o&

sho&ld also consider archiving any Iocs and clean the t+>C %&e&es.

All of this *ill red&ce the si(e of the A8A system and help yo& fit the

system ta)les on the master node.

11. In SA' 8ote 0B4, SA' provides some ideas on ho* to eep the

!asis ta)les from gro*ing too fast in the f&t&reF if yo& are on Service

'ac 23 on !W .0 or higher, yo& can also delete &n*anted master

data directly ;see SA' 8ote6 1304<.

12. >inally, yo& can &se the program +SCK9+JIJH8HS9 to delete

any &n&sed dimension entries in yo&r InfoC&)es to red&ce the overall

system si(e.



22

What Well Cover

•






• Wrap&p



23

emo6 !W .4 'erformance onitoring

In this demo *e *ill e:plore the !W .4 on A8A !A Cocpit >eat&res



24

emo6 !W .4 'erformance onitoring



25

!W .3 'erformance and Cocpit Capa)ilities

•

!W .3 monitors and cocpit capa)ilities also incl&de6 onitor of data)ase &sage and o)"ect si(es ;i.e., InfoC&)es, S7s<

O&ery &sage statistics are more visi)le ;similar to +S+#, +S+K, +S##<

We can see more of the &se of SA' 8etWeaver !W Accelerator and si(es

onitor for the act&al &se of 7/A'PL Cache and hit ratios

o& can no* selectively delete internal statistics in +SS#A#W )ydate thro&gh the &pdated +SS#A#JA#AJ9/9#9 A!A' program

#here is also a L 9ditor for coding and synta: assistance

Sol&tion anager has )een

&pdated to tae advantage of

these ne* monitors.



26

What Well Cover

•






• Wrap&p



27

Converting Info'roviders andPor ata >lo*s

• While not re%&ired, InfoC&)es can )e

optimi(ed f&rther for A8A performance• #his )asically means ?flattening@ the

data str&ct&res and removing the

dimensions in !W from the physical

layer ;they still loo as if they e:ists<

any refer to this optional step as a ?f&nctional migration@ and do this after the A8A

migration has )een completed, often as a separate initiative ;see SA' 8ote 14G4G<



28

A8A 7ptimi(ed !W .4 S7s and 'erformance Improvements

•

!W optimi(ed S7s are no* created )y ?defa&lt@ in A8A

• #his means that data activations are done m&ch faster at the A8A

data)ase layer• #he change log is ept in a calc&lation vie* res&lting in smaller S7s

A8A optimi(ed S7s are also availa)le for !W .3, )&t no* they are created )y

defa&lt, so do not convert S7s to A8Aoptimi(ed. >ast activation is availa)le for

all standard S7s *itho&t conversion to A8Aoptimi(ed.



29

Converting Info'roviders andPor ata >lo*s

• #o help yo&, the SA' igration Cocpitalso allo*s yo& to migrate yo&r data

flo*s from 3.: to ata #ransfer 'rocesses

;#'s< as &sed in versions .0 and higher

• If yo& convert the data flo*s yo& get

)etter a&tomated data pacage #'optimi(ation, *hich loads data faster into

A8A.

• o& can also sim&late the data flo* )efore yo& do the real

conversion. When doing so, data is loaded for )oth versions

;3.: and .:< of the dataflo*s and the res&lts are stored incl&ster ta)les. #he data is then compared to verify that the

dataflo* after migration calc&lates the same data as it did

)efore migration

• Since the differences are displayed separately, yo& can

analy(e the res&lts and changes in details



30

What Well Cover

•






• Wrap&p



31

9W esign Ks. 9vol&tion

An organi(ation has t*o f&ndamentalchoices6

1. !&ild a ne* *ell architected 9W

2. 9volve the old 9W or reporting system

!oth sol&tions are feasi)le, )&t organi(ations

that selects an evol&tionary approach sho&ld

)e selfa*are and monitor &ndesira)le add

ons and Q*oraro&nds@.

>ail&re to )rea *ith the past can )e

detrimental to an 9Ws longterm s&ccessR



32

ata esign #he Hse of /ayered Scala)le Architect&re ;/SA<

#he /SA consists logically of6 Ac%&isition layer armoni(ationP%&ality layer 'ropagation layer !&siness transformation layer +eporting layer Kirt&ali(ation layer

Since SA' !W .3 S'3 *e have

had a set of 10 templates to help

)&ild a layered data architect&re for

largescale data *areho&sing



3333

BWERP

Germany

FLEXIBLE

REPORTI

NG

Europe

(excl. Germany)

Europe 2

Europe 3

USA

Amerca! 1

Amerca! 2

A!a

Germany

BUSINES

S

TRANS.

Europe

(excl.Germany)

Europe 2

Europe 3

USA

Amerca! 1

Amerca! 2

A!a

Germany

DATA

PROPAGATI

ON

Europe

(excl.Germany)

Europe 2

Europe 3

USA

Amerca! 1

Amerca! 2

A!a

DATA

ACQUISITI

ON

"a#a

Ac$u!#on

"a#a Source

%ran!&er 'ule

n&o Source

E' %a*le

Germany

CORPORATE

MEMORY

Europe(excl.Germany)

Europe 2

Europe 3

USA

Amerca! 1

Amerca! 2

A!a

Germany

DIMENSION

AL

REPORTING

Europe

(excl. Germany)

Europe 2

Europe 3

USA

Amerca! 1

Amerca! 2

A!a

semantic

partitions

B /SA /ayers

41 total

o)"ects

9:ample6 C&rrent /SA ata Architect&re in SA' !W



3434

9:ample6 Simplified /SA ata Architect&re

BWERP FLEXIBLE

REPORTING

BUSINES

S

TRANS.

Europe

Amerca!

A!a

DATA

PROPAGATI

ON

Europe

Amerca!

A!a

DATA

ACQUISITION

"a#a Source

%ran!&er 'ule

n&o Source

E' %a*le

CORPORAT

E MEMORY

Europe

Amerca!

A!a

DIMENSIONAL

REPORTING

Remove 5

semantic

partitions

Remove 3 LSA

layers

41 shrins

to G total

o)"ects



35

Conformed

Reportale

!S"

Write

"ptimized

!S"

9W Comple: /ayered Architect&res

• #his !'C on !W system *as e:periencing

s&)stantial load performance iss&es• Some of this *as d&e to &nderlying SA' !W

config&ration, *hile some *as d&e to the

technical config&ration of the data store

architect&re and data flo* inside SA' !W

ro+uc#on !!ue! nclu+e+,1) "epen+en# -o*! no# runnn

!e$uen#ally/ .e./ loa+ &rom

Summary cu*e #o S#an cu*e

! !ome#me! execu#e+ *e&ore#e !ummary cu*e +a#a ! loa+e+

an+ ac#a#e+/ re!ul#n n ero

recor+! n #e !#an cu*e.

2) on la#ency # 6 layer! o&

SA/ "S!/ an+ n&ou*e!

*e&ore con!ol+a#on proce!!e!

can *e execu#e+.

#$%&'!()S #$%&'!(*S #$%&'!*+#$%&'!(3S #$%&'!((S

#$%&'!,( #$%&'!(7 #$%&'!(4#$%&'!,* #$%&'!(+

%& S-mmar

C-e

/#$%&'C*30

BPC Sta1in1

C-e

/BPC'C*(0

Con2olidation

C-e

/"C'C"0

ECC .*

A2ia5Pacific

ECC .*

orth5America

ECC 4.7

&atin5America

R63 3.(i

E

ECC 4.7

AS$A

Per2i2tent Sta1in1 Area /PSA0

Con2olidation Proce22e28

1) learn

2) oa+

3) oren Excane

4) Elmna#on!5) p#ma#on!




36

Write

"ptimized

!S"

>i:es to Comple: 9W Architect&re

•

#he fi: to this system incl&ded removing the conformed S7layer, *ith !9: flags for data stores that are never reported on.

• Also, the !'C staging c&)e served

little practical p&rpose since the data is

already staged in the $/ S&mmary c&)e

and the logic can )e maintained in the

load from this c&)e directly to the

consolidation c&)e.

#$%&'!()S #$%&'!(*S #$%&'!*+#$%&'!(3S #$%&'!((S

%& S-mmar

C-e

/#$%&'C*30

Con2olidation

C-e

/"C'C"0

ECC .*

A2ia5Pacific

ECC .*

orth5America

ECC 4.7

&atin5America

R63 3.(i

E

ECC 4.7

AS$A

Per2i2tent Sta1in1 Area /PSA0

Con2olidation Proce22e28

1) learn

2) oa+

3) oren Excane4) Elmna#on!

5) p#ma#on!

on#erm *ene&#! nclu+e+

re+uce+ +a#a la#ency/ &a!#er

+a#a ac#a#on/ le!! +a#a

replca#on/ !maller !y!#em

*acup! a! ell a! !mpl&e+

!y!#em man#enance.




37

9W ata esign Classical Hse of &lti'rovider ints in !W

• If a %&ery has restrictions on this characteristic, the 7/A' processor is

already checed to see *hich part of the c&)es can ret&rn data for the %&ery.

#he data manager can then completely ignore the remaining c&)es.

'ro)lem6 #o red&ce data vol&me in each InfoC&)e,data is partitioned )y #ime period.

A %&ery m&st no* search in all Info'roviders to find

the data. #his is very slo*.

Sol&tion6 We can add ?hints@ to g&ide the %&ery e:ec&tion. In the

++EH/#I'+7KI8# ta)le, yo& can specify one or several

characteristics for each &lti'rovider, *hich are then &sed to

partition the &lti'rovider into !asicC&)es.

An entr in RR9:&;$PR"<=$; onl ma>e2 2en2e if a few attri-te2 of thi2

characteri2tic /that i2? onl a few data 2lice20 are affected in the ma@orit of? or

the mo2t important? -erie2 /SAP ote28 ((3. See al2o8 )4++ and (()+(0.



38

!W .3 and higher Semantic 'artitioned 7)"ects ;S'7<

• When data stores and InfoC&)es are allo*ed to gro* over time, the data load

and %&ery performance s&ffers

• 8ormally o)"ects sho&ld )e physically partitioned *hen the n&m)ers of

records e:ceed 100 200 million

o*ever, this may )e different depending on the si(e of yo&r hard*are and

the type of data)ase yo& &se• In SA' 8etWeaver !W .3 *e get an option to create a Semantic 'artitioned

7)"ect ;S'7< thro&gh *i(ards

o& can partition )ased on fields s&ch as calendar year, region, co&ntry, etc.



39

ata esign Semantic 'artitioned 7)"ects ;cont.<

•

When an S'7 is created, a reference str&ct&re eeps trac of thepartitions. #he str&ct&re is placed in the &lti'rovider for %&erying.

S'7 Wi(ards create all ata #ransfer 'rocesses ;#'<,

transformations, filters for each data store, and a process chain



40

What Well Cover

•




•

emo6 !W .4 performance monitoring• !W 7ptimi(ation after A8A migration


• Wrap&p



41

Where to >ind ore Information

•

Introd&ction to SA' A8A )y !"arne !erg and 'enny Silvia, SA''ress 3rd edition.

• http6PPscn.sap.comPdocsP7C350GB SC8 SA' 8etWeaver !&siness Wareho&se .4

• http6PPhelp.sap.comPn*Jplatform elp SA' !W .4 *e) site

• http6PP***.stechno.netPsapnotes.htmlTvie*UsapnoteMidU153GB SA' !&siness content release note for !W .4

http://scn.sap.com/docs/DOC-35096

http://help.sap.com/nw_platform

http://www.stechno.net/sap-notes.html?view=sapnote&id=153967

http://www.stechno.net/sap-notes.html?view=sapnote&id=153967

http://help.sap.com/nw_platform

http://scn.sap.com/docs/DOC-35096



42

Eey 'oints to #ae ome

• !W .4 is the first release to tae f&ll advantage of SA' A8A

• Some of the f&nctions in .4 are also availa)le to nonA8A

c&stomers

• #he ne* Composite'roviders and the 7pen 7S Kie* maes A8A

and !W tightly integrated and capa)le to s&pport 9Ws )etter• & sho&ld )reafrom the past and start designing *ith the ne* !W

.4 feat&res inmind

• #he ne* monitoring feat&res in the !W !A Cocpit and the A8A

systems maes it m&ch easier to see *hat is occ&rring from adata)ase level for the non)asis team.

• !efore yo& si(e yo&r system, clean it &p and save hard*are costs.

• All c&stomers sho&ld consider the !W move to A8A in 2015V



43

o&r #&rnV

o* to contact me6

r. !erg))ergcomerit.com

'lease remem)er to complete yo&r session eval&ation



isclaimer

SAP, R/3, mySAP, mySAP.com, SAP NetWeaver®

, Duet®

, Partner!"#e, an" ot$er SAP pro"ucts an" services mentione" $erein as %ell as t$eirrespective lo#os are tra"emar&s or re#istere" tra"emar&s o' SAP A( in (ermany an" in several ot$er countries all over t$e %orl". All ot$er pro"uct

an" service names mentione" are t$e tra"emar&s o' t$eir respective companies. Wellesley )n'ormation Services is neit$er o%ne" nor controlle" *y

SAP.

BI2015 Berg Advanced Performance Optimization With SAP BW v05

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Transcript of BI2015 Berg Advanced Performance Optimization With SAP BW v05