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Advanced OLAP ConceptsAdvanced OLAP Concepts
Part 4Part 4
<OLAP Concepts 201 Series>
Ren Sin!"
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OLAP O%er%ie
• On#Line Anal'tical Processin! is a decision spport
so(tare t"at allos t"e ser to )ic*l' anal'+e in(or,ationt"at "as -een s,,ari+ed into ,ltidi,ensional %ies and"ierarc"ies.
• /"ere are t"ree ,ain (eatres o( OLAP s'ste,
ltidi,ensional iein! – OLAP spports
,ltidi,ensional ,odel "ic" consists o( (acts anddi,ensions also called as Star Sc"e,a.
Calclation Intensi%e Capa-ilities – 3e to data is storedin (acts and di,ensions ta-les4 it ena-les sers toanal'+e data it"ot ,c" calclations.
/i,e Series anal'sis – 5na-les sers to anal'+e dataacross ti,e.
• /"is odle ill co%er t"e details in (or parts
– Part 1 – OLAP odelin! – 6ildin! 6loc*s
– Part 2 – OLAP /'pes & Arc"itectres – Part 7 – OLAP reportin! St'les
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OLAP O-ecti%es
:pon co,pletion o( t"is ,odle 'o ill -e a-le to
• We- Access Soltions (or OLAP Applications
• Isses in OLAP
• /ips on OLAP Opti,i+ation
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OLAP Otline
Lesson 2 OLAP Isses
Lesson 7 OLAP Opti,i+ation
Lesson 1 OLAP – We- Ser%ices
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OLAP # We- Ser%ices
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We- -ased OLAP
We- Access is t"e data access and anal'sis t"ro!" t"e e-.
A We- Ser%ice is a standardi+ed a' (or applications to
co,,nicate it" eac" ot"er o%er standard internetprotocols
OLAP We- ser%ices deli%er c-es4 slices4 or cells (ro, a,ltidi,ensional ,odel to -e sed in a client anal'ticalapplication
We- ser%ice is increasin!l' -eco,in! poplar
= Si,ple to se
= o separate client are necessar' ?(or t"e sers@
= Lo cost o( internet
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5BternalApplication 3ata
are"ose
C-eSOAP
//P
We- ser%ices
SOAP
//P
We- ser%ices
C-e
OLAP We- Ser%ice Arc"itectre
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Ad%anta!es o( :sin! We- Ser%ices
Interopera-ilit'= We- ser%ices allo de%elopers to se %arios
pro!ra,,in! lan!a!es
= We- Ser%ices are %irtall' plat(or,#independent
:sa-ilit'= We- Ser%ices allo t"e -siness lo!ic o( ,an' diEerent
s'ste,s to -e eBposed o%er t"e We-
Resa-ilit'= Fero#codin! deplo',ent
3eplo'#a-ilit' 5as' to deplo'4 !eneric standard procedres
GleBi-ilit' 5as' to csto,i+e to re)ire,ents as and "en re)ired
and adapt to c"an!in! -siness needs
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OLAP
Isses
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3ata-ase eBplosion W"' data-ase 5Bplosion H
:nderstandin! 3ata-ase 5Bplosion -asics
Sparse 3ata conse)ences
A%oidin! data-ase eBplosion W"at to pre#calclate H
o ,c" to Pre#calclation H
Isses it" OLAP
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Case Per(or,ance I,pro%e,ent /o !et a (ast response ,ltidi,ensional applications
need to pre#calclate t"e in(or,ation t"at ill -e needed(or anal'sis
In 336s4 t"e stora!e o( pre#calclated data is sall'ato,atic and transparent
S,,ar' ta-les are nor,all' sed in ROLAP option
I,pact ltidi,ensional data-ases can !ro to a-nor,al si+e
de to t"e n,-er o( pre#calclations in%ol%ed
W"' 3ata-ase 5Bplosion H
7/23/2019 Bts(Fs-tmt) Dwh - Ucf 2.x Advanced Olap Concepts v1.0 - Part 4
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6le – 5Bternal Sorce
Red – OLAP c-e o(-ase data
:nderstandin! 3ata-ase5Bplosion # I
lti#colored -ric* # Pre
calclated data
Wooden stac* – 3ata o( ont"e ' calclations
7/23/2019 Bts(Fs-tmt) Dwh - Ucf 2.x Advanced Olap Concepts v1.0 - Part 4
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:nderstandin! 3ata-ase5Bplosion # II
0
500
1000
1500
2000
2500
3000
G r o w t h r a t i o n f o
r f u l l c a l c u l a t i o n s i n %
5 6 7 8 9Number of Dimensions
Database Explosion using aggregates
7/23/2019 Bts(Fs-tmt) Dwh - Ucf 2.x Advanced Olap Concepts v1.0 - Part 4
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Sparse 3ata Sparse data is )ite co,,on in t"e sorce data
Conse)ences Sparsit' o( data can "a%e a "!e i,pact in t"e si+e o(
t"e data -ase
It "as -een (ond t"at t"e data %ol,e increases -'
(actor o( 7 or 8 "en t"e data is sparse
As t"e n,-er o( sparse di,ensions increase t"e !rot"can -e disastros
Sparse data conse)ences
7/23/2019 Bts(Fs-tmt) Dwh - Ucf 2.x Advanced Olap Concepts v1.0 - Part 4
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A%oid (ll' pre#calclatin! an' ,ltidi,ensionalo-ect it" ,ore t"an $%e sparse di,ensions
Redce t"e sparsit' o( indi%idal data o-ects -'= Jood application desi!n
= :sin! a ,lti#c-e rat"er t"an a "'perc-eapproac"
A%oidin! data-ase eBplosions
7/23/2019 Bts(Fs-tmt) Dwh - Ucf 2.x Advanced Olap Concepts v1.0 - Part 4
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It is -est to c"oose pre#calclate data t"at is
= Slo to calclate at rn#ti,e4 -ecase it depends on,an' ot"er cells or co,pleB (or,lae or
= Gre)entl' %ieed
= /"e -asis o( ,an' ot"er calclations.
W"at to pre#calclateH
7/23/2019 Bts(Fs-tmt) Dwh - Ucf 2.x Advanced Olap Concepts v1.0 - Part 4
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W"at is t"e !eneral !idelines (or "o ,c" pre#calclate
o ,c" to pre#calclateH
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Relati%el' s,all applications ?a (e ,illion inpt cells@
= W"ic" can -e easil' calclated in t"e a%aila-le ti,e indo
= Gor "ic" dis* space is not a pro-le,4
Applications "ic" "a%e no ,ore t"an a-ot $%e di,ensions
W"en calclations are co,pleB and interdependent4 and oldt"ere(ore -e slo to eBecte at rn#ti,e
W"en )er' per(or,ance is all#i,portant ?(or eBa,ple4 in so,e
5IS applications@
Applications it" potentiall' t"osands o( concrrent sers?,ost pro-a-l'4 %ia t"e We-@
W"en to pre#calclate allH
7/23/2019 Bts(Fs-tmt) Dwh - Ucf 2.x Advanced Olap Concepts v1.0 - Part 4
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OLAP Opti,i+ation
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aor -ottlenec* in OLAP )er' and c-eprocessin!
• Koin o( central ?sall' %er' lar!e@ (act ta-le it"srrondin! di,ension ta-les ?Star oin@.
Opti,i+ation /ec"ni)es= Appropriate indeBin! sc"e,a ?incldin! proper order@
= Pre#co,pte a!!re!ated reslts ?sa!e is li,ited in caseo( ad#"oc )eries@
= ierarc"ical clsterin! o( data= Inclde onl' critical ,easres (or 'or -siness
= ltit"readin!
= I,ple,ent 6it#,ap indeB
OLAP opti,i+ation # I
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ierarc"ical clsterin!6ased on "ierarc"ical srro!ate *e' ?S@ attri-te. ale o( t"is
attri-te is co,pted -ased on %ale o( "ierarc"ical attri-tes o(t"e di,ension.
Example:
/"is concept o( HSK is eBtre,el' "elp(l in ad#"oc )er' -ecase itena-les clsterin! o( (act ta-le accordin! to di,ension"ierarc"ies
OLAP opti,i+ation # II
RegionA
(0)
AreaA
(0)
AreaB
(1)
StoreA
(0)
StoreB
(1)
StoreC
(2)
StoreD
(3)
Hs(storeC) ! 0"1"2
7/23/2019 Bts(Fs-tmt) Dwh - Ucf 2.x Advanced Olap Concepts v1.0 - Part 4
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6it,ap IndeB – 6it,ap indeBes or* ell (or data4 "ic" "as a s,all
n,-er o( distinct %ales.
– 6it,ap indeBes are se(l (or ni)e %aled data "ic" is
not pdated (re)entl'.
– 6it,ap indeBes "a%e a si!ni$cant space and per(or,ancead%anta!e o%er ot"er strctres.
= Ad%anta!es o%er "as" and tree indeBes ..• :se(l (or lo cardinalit' do,ain as co,parison• Si!ni$cant redction o( space and IMO
*Reference: Data Mining by Jiawei Han, Micheline Kamber
OLAP opti,i+ation # III
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Con!ratlationsN o "a%e no co,pletedt"e ,odle OLAP #ss$es %Opti&i'ation
o s"old no -e a-le to
– :nderstand OLAP We- Ser%ices
– no OLAP Isses
– /ips o( OLAP Opti,i+ation
odle S,,ar'
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$i'
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1. We- Access is t"e data access and anal'sist"ro!".
a@ 3ata-ases
-@ We-c@ Personal data Pro%iders
d@ A and 6
estion 1
Anser 6
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2. Ad%anta!es o( :sin! We- Ser%ices are t"at t"e'
a@ are plat(or, independent
-@ allo de%elopers to se %arios pro!ra,,in!lan!a!es
c@ "a%e Fero#codin! deplo',ent
d@ All t"e a-o%e
estion 2
Anser 3
7/23/2019 Bts(Fs-tmt) Dwh - Ucf 2.x Advanced Olap Concepts v1.0 - Part 4
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7. Jeneric We- Ser%ice Arc"itectre does notcontain
a@ 3ata access la'er
-@ 6siness Lo!icc@ 6siness Intelli!ence
d@ Listener
estion 7
Anser C
7/23/2019 Bts(Fs-tmt) Dwh - Ucf 2.x Advanced Olap Concepts v1.0 - Part 4
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8. 3ata-ase eBplosion is a p"eno,enon casin!%ast a,onts o( stora!e space and occr,ostl' in
a@ ROLAP 3ata-ases
-@ OLAP 3ata-asesc@ OLAP 3ata-ases
d@ 3OLAP 3ata-ases
estion 8
Anser 6
7/23/2019 Bts(Fs-tmt) Dwh - Ucf 2.x Advanced Olap Concepts v1.0 - Part 4
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;. As ,ore sparse di,ensions are added4t"e data-ase si+e lti,atel' !ros
a@ Linearl'
-@ Co,pondin!
c@ 5Bponentiall'
d@ Lo!arit",icall'
estion ;
Anser 6
7/23/2019 Bts(Fs-tmt) Dwh - Ucf 2.x Advanced Olap Concepts v1.0 - Part 4
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. C"oosin! Pre#calclated data ,a' -e anoption so,eti,es "en
a@ calclation is slo at rn#ti,e.
-@ calclations "a%e co,pleB (or,lae
c@ I( t"e data is (re)entl' %ieedd@ It (or,s a -asis o( ,an' ot"er calclations
e@ All o( t"e a-o%e
estion
Anser 5
7/23/2019 Bts(Fs-tmt) Dwh - Ucf 2.x Advanced Olap Concepts v1.0 - Part 4
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. OLAP opti,i+ation "elps t"e co,panies toadd %ale to t"eir applications -'
a@ redcin! data load ti,es
-@ decreasin! )er' response ti,es
c@ ,ini,i+in! c-e si+e
d@ ,ini,i+in! data stora!e re)ire,ents
estion
Anser ALL
7/23/2019 Bts(Fs-tmt) Dwh - Ucf 2.x Advanced Olap Concepts v1.0 - Part 4
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D. ierarc"ical clsterin! is done -ased on
a@ (orei!n e' attri-tes
-@ pri,ar' e' attri-tes
c@ "ierarc"ical srro!ate *e' attri-ted@ 6it#,ap indeB
estion D
Anser C
7/23/2019 Bts(Fs-tmt) Dwh - Ucf 2.x Advanced Olap Concepts v1.0 - Part 4
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9. 6it,ap indeB is a special *ind o( data-aseindeB t"at ses
a@ /ree IndeB
-@ 6it,aps
c@ as" IndeB
d@ one o( t"e a-o%e
estion 9
Anser 6
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Reerences
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Re(erences
Library:
Tek-tips reporting solutions oru!
"ttp:##$$$%&!re'ie$%(o!#
"ttp:##$$$%&$ino(enter%org
)ata $are"ouse an& *L+, –on(epts. +r("ite(ture an&/olutions by obertre!ber "ristianon(ilia
T"e *L+, eport by 4igel,en&se an& i("ar& reet"
T"e *L+, /olutions – uil&ing
ulti&i!ensional nor!ation
/yste!s /e(on& &ition by
rik T"o!sen. iley
&rea!te(" n&ia ,'t% Lt&%2002 /4 81-265-0275-
Publications Publications
Training ProgramsURL’s
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*+an ,o$
Ren Sin!" /ec"nical Lead
renu%sing"$ipro%(o!