Video
1
284
380
382
383
385
386
394
398
399
499
500
503
504
505
507
508
567
591
636
637
811
976
1069
1072
1107
1110
1118
1120
1141
1143
1311
1467
1472
1545
1616
1741
1746
1785
1887
1964
2024
2189
2258
2259
2299
2397
2443
2444
2487
2490
2496
2510
2519
2634
2813
2866
2867
2868
2928
2954
2955
2965
3031
3045
3194
3613
3655
3669
3698
3699
3728
3729
3743
3804
3805
3824
3825
4279
4280
4360
4361
4617
4620
4736
4864
4867
4975
5097
5135
5137
5138
5141
Lecture Structure
- Local as View (LaV) oka CREATEV EW S1 AS (00:03:36)
- v v 1 (WHEREJahr= 2OC (00:03:36)
- OO l lELlQ llIIlCl lEl l llU l I Cgl Jc1IlI J( lIIC)( lebenbed ng ng a) r 21300)S42 NeueFi meBöse(Tite Regie Genre)(Hebenbed ng g Jahr 2000S53 AktuelleFi me(Tite Regie Gen(T IebenbedmgL ng Ja (WHEREJahr 2000)CREATE VlE N S4 ASSELECT Titel Reg e GenreFROM FilmHEREJahr 2000CREATEVIEW S5 AS (00:03:36)
- Local as View (LaV) globale ICs (00:05:21)
- dem globalen Schema kann (00:05:21)
- SELECT Titel Regie Genre (00:05:21)
- cREATE V1EWAIIeFi meBöseAS (00:05:21)
- Überblick (00:06:20)
- LaV Anwendung Anfrageoptirnierung (00:06:22)
- LaV Anwendung Anfrageoptimierung (00:06:24)
- La Anwendung Datawarehouse Design (00:06:25)
- LaV Anwendung Semantisches Caching (00:06:26)
- La Anwendung Anfrageoptimierung (00:06:37)
- Write auf MV (00:06:37)
- Welche Sichten helfen bei der (00:06:37)
- AST Advanced Summary (00:06:37)
- (mater alized views MV) auf (00:06:37)
- La Anwendungen (00:06:38)
- Local as View (Lav) globale ICs (00:06:42)
- geprüft werden (00:06:42)
- SELECT T e Regie Genre (00:06:42)
- CREATEv EWA e =nmeBöseAs (00:06:42)
- Nebenbedingung Jahr 2000 (00:06:42)
- Menenbecnngung Jak r = ZÜOÜ (00:06:42)
- LaV Anwendungen (00:08:19)
- LaV Anwendung Anfrageoptimierung (00:08:22)
- La Anwendung Datawarehouse Design (00:08:23)
- Überblick (00:08:24)
- Anfrageplar ung (00:08:25)
- Query Containment (00:08:27)
- Anfrageplär e (00:08:28)
- Anfragebearbeitung (00:09:27)
- Beispiel (00:10:34)
- u SELECT profFROM DB kurs DWHERE D univ = HPI M n 71 rmn = = G =m= = (00:10:34)
- rageSELECT prof FROM Lehrt L Kurs KWHERE L kurs id = K kurs idAND Ktitel L KE47 Datenbanken (00:10:34)
- LaV Visualisierung (OWA) (00:10:36)
- Beispiel (00:11:35)
- WHERE L L niv = HPI (00:11:35)
- FROM Kurs K (00:11:35)
- Umgeschriebene Anfrage (00:11:35)
- Kuniv HP (00:11:35)
- AND (00:11:35)
- WH ERE L kurs d = K kurs d (00:11:35)
- FROM Lehrt L Kurs K (00:11:35)
- Quelle 1 Alle Datenbankveranstalt (00:11:35)
- EIV Beispiel vergleich (00:13:42)
- CWA (00:16:16)
- Anfrageergebnisse können sich ändern (00:16:16)
- Open World Assumption (OWA) (00:16:16)
- Closed World Assumpt on (CWA) (00:16:16)
- La Beispiel Vergleich (00:17:51)
- geschriebene AnfragSELECT titel kurs idFROM DB kurs DWHERE D univ = HPI ELECT titel kurs idFROM H Pl VLMaximaleAntwort (00:17:51)
- ä fÜ ? L Kurs gE gf f D 9WHERE L Kurs u = urs u WHERE = Pr AHWVOFT (CWA)AND K tite = Datenbanken G ba eA f a9e geschriebe Anfrag Vollstand eAND L univ (00:17:51)
- Antwort (00:17:52)
- Maximale (00:17:52)
- Vollständige (00:17:52)
- Umgäfzl rieäene Anfrage (00:17:52)
- CWA OWA (00:18:27)
- Welchen Anteil an der wofld hat das Ergebnis? (00:18:27)
- Closed World Assumption (CWA) (00:18:27)
- Anfrageergebnisse können sich ändern (00:18:30)
- Open World Assumption (OWA) (00:18:30)
- Lav Beispiel Vergleich (00:18:39)
- Beispiel (00:18:43)
- WHERE L univ = HPI (00:18:43)
- FROM Kurs K (00:18:43)
- Umgeschriebene Anfrage (00:18:43)
- Quelle 1 Alle Datenbankveranstalt (00:18:43)
- Kurs(Rurs id i univ) (00:18:43)
- Beispiel Vergleich (00:19:02)
- CWA OWA Beispiel (00:19:03)
- CWA OWA (00:23:00)
- w 4if CREATE VIEW V2 ASSELECTB FROM R frage SELECT FROM R CCWA (a b) muss in der Exte n von R se n (00:24:30)
- l VIGW 1 f TE v1Ev @ DAs 7 ELECTA FROM R Evrnncinn 1 1 (00:24:30)
- CWA OWA Beispiel (00:24:32)
- Anfrage SELECT FROM R (00:24:32)
- Relation R(A B) (00:24:32)
- OWA (a b) muss nicht in der Extension von R säml (00:25:54)
- CWA (a b) muss in der Extension von Ffsein (00:25:54)
- 3ELE Ü rf 1 Extension b Öl kw (00:25:54)
- Anfragebearbeitung (00:26:56)
- Überblick (00:29:01)
- Anfrageumschreibungen (00:29:06)
- Anfrageumschreibungen (WdH) (00:31:26)
- Beispiele (00:31:27)
- L univ = Humbo di (00:34:48)
- NP vollständigin Q Q nach (00:36:29)
- t l l Q i W FROM äi ily (00:36:29)
- Prüfung von containment durch Prüfung (00:36:29)
- Mehrere Algorithmen (00:37:38)
- N P vollständig in Q Q nach (00:37:38)
- I Prüfung von containment durch Existenz (00:37:38)
- Zu komplex (00:37:38)
- E5C (00:37:38)
- I aller möglichen Datenbanken? (00:37:38)
- Prüfung von containment durch Prüfung (00:37:38)
- CM77 (00:37:39)
- Prüfung von containment durch Existenz (00:37:39)
- aller möglichen Datenbanken? (00:37:39)
- Datalog Notation (00:38:19)
- SQL Datalog (00:40:17)
- product (PID PN PGN) 1 (00:40:17)
- @ducc (PID PN Pam (00:40:43)
- S prc uct d = (00:40:43)
- SELECT (00:41:29)
- ducc d AND (00:41:29)
- uct d (00:41:30)
- WHERE s c agyea (00:41:30)
- 1999 S (00:41:49)
- Notation (00:41:50)
- 1 uq = I die Menge aller Symbole von (00:41:50)
- ( die Menge aller Konstanten von q (00:41:50)
- J H lp die Menge aller Variablen vun f (00:41:50)
- r beliebige (00:41:50)
- min ex ensionalen Pr dikaben (00:41:50)
- Kons amen Eine k j Da g f g as eine Anfrage (00:41:50)
- Sei I eine Menge vun Variablensymbolen und ( eine Menge von (00:41:50)
- Query Containment (00:42:52)
- map(Mn Ms) c one(Mn Cn ) map(Mn Ms) (00:42:52)
- map(Mn Ms) Mn (00:42:52)
- rnap(Mn Ms) g map(Mn Ms) (00:42:52)
- A query p is containedin a QUEÜ u (p gu) iff al tup es computed (00:42:52)
- Beweis für Query Containment (00:46:52)
- map(IV n l4s) clone(Mn Cn ) (00:46:52)
- p ugd einx (00:46:52)
- map(Mh MS) (00:46:53)
- map(I fn fs) clone(Mn Cn ) (00:46:53)
- Finden von Containmenth Mappings (00:47:46)
- Bei Interesse siehe Buch (00:47:46)
- Auffächerung nach möglichen CMS (00:47:46)
- Problem ist NP vollständig (00:47:46)
- Weitere Containment Beispiele (00:47:47)
- Q product(PID PN PGID PGN) (00:47:47)
- product(PID PN PGID PGN) PGN= Wasser (00:47:47)
- product(PID PN PGID PGN) Q localization(SID SN RID RN) (00:47:47)
- Finden von Containment Map ppings (00:47:49)
- Weitere Containment Beispiele (00:48:48)
- Finden von Contair ment Mappings (00:49:14)
- Beweis für Query Containment (00:49:18)
- map(Mh I TS) (00:49:18)
- map(IV n 4s) clone(Mn Cn ) (00:49:18)
- p u gdw ein containment mapping von u nach p existiert (00:49:18)
- Weitere Cor tainment Beispiele (00:49:25)
- pm ucr(P1 3 PN pero PGN) Q Rn) RN) (00:49:25)
- prod C1ft(PID PI k PGID Wasser ) proüuct(P1D PN PGID PGN) (00:49:25)
- fä f Uä z Zh) ? (00:50:31)
- product(PID PN PGID PGN) PGN= Wasser (00:50:31)
- proauct( = 1D PN PGID W er g pr duct(P1 PN PG1 2 j (00:50:31)
- Weitere Containment Beispiele (00:53:09)
- product(PID PN PGID PGN) PGN= Wasser (00:53:09)
- product(PID PN PGID PGN) Q localization(SID SN RID RN) (00:53:09)
- Beispiel (00:58:25)
- patnLA ) patn k 7 Patn u) path(A B) path(B C) path(C D) path(D E) (00:58:25)
- MÄF (00:58:25)
- h(D) 28 h(D) 3l (01:00:13)
- sales (X Y Z ) time(f Ü (01:00:13)
- Erzeugung der Anfragen (01:00:55)
- d DB Beobachtung SW d ß äf g lnterpretat on als F In j ? f f f@ 1 Ecor ta nment 22 Ä J g aa mg UIQID Ws om V 2 s rwqS rma n Neger i = =s enu n new inep lß vmewb d PYU Shmgpf f if ucnung n mm d 5 am spendenDB rmen) i l i g buchung 7 ? 1 uugnung u me US 13 IDB SladKH3l lS 1E l 0 g) V datum fm 4 menge e mw w U 2 Lmw mk w (01:01:38)
- be rag Q M projekt Sm (01:01:40)
- mm mm r na n T14 name N9 stadt W fw f Sn nde omname = m (01:01:40)
- uummgnu=nun yn (01:02:23)
- E eLspendenDB rmen haushaItDB skadlHausha t oru 5 End ID euvg pmp n wspend r Ü an (01:02:23)
- s iif i f i lf 7stadt M Tm arg z mß (01:02:23)
- (spendenDB rm a oßen) stadtHausha t org)5PEmrm n Wegespena n wiebetrag Q9 Mpmje mspender =Üa r Ei ahm spena nproj fvw bucmm nhuch nnlß wwdatum me menue 1 mmnewwmahuch mg rx (01:03:24)
- m mm nna n @= T f 1 f9 i gn W 1name mSladl =1rrv J omname rmxSpende 77 VW V f n M einnahmespena n f f Spepdel = V nru (01:03:24)
- Üa (01:03:25)
- pm fm Jbunhunglß mv ne u7ct f ng Anu h ng n (01:03:25)
- rm rmal ale v name nrw Sladl ir ndSn ndes au Worg g urgn @ 1 omname mf w (01:03:25)
- Erzeugung cler Anfragen (01:03:44)
- Anfrageumschreibung (01:03:45)
- Überblick (01:11:19)
- Anfrageumschreibung (01:11:20)
- Bucket Algorithmus (nächster Foliensatz) (01:11:20)
- Sichte e Prädikate) (01:11:20)
- e Prädikate) (01:12:40)
- Anfrageumschreibung (01:16:55)
- Überblick (01:16:57)
- Global Local as View 4 (GLAV) (01:17:54)
- Anfrageplanung (01:18:56)
- Überblick (01:21:04)
- Vergieich GaV (01:21:07)
- Vergleich Gav (01:23:27)
- Literatur (01:24:57)
- LMSS95 Alan Y Levy (01:24:57)
- CP 77 fshm f a g qr d af a 1 Qpt mal implernen at o f of (01:24:57)
- Hul 97 Manag ng Semantic Heterogene ty n Databases1A Theoret cal (01:24:57)
- UIIOO Jeffrey D Ullmanz Information Integration Using Logica View (01:24:57)
- Levy01 A on Y Halevyz Answerir g queries us ng views A survey in (01:24:57)
- Mw gqn v wmm nnrm (01:25:37)
- Mw gqn v wmm (01:25:38)
- g=v (01:25:55)
Links added to this content
No links have been added to this content so far.
Tags added to this content
No tags have been added to this content so far.
Create Note
Dear user,
with the manuscript function you'll be able to create your own digital lecture manuscript.
However, in order to link all your notes with your user profile it is required that you
login to the tele-TASK portal to use this functionality.
If you don't have an account yet, you may register for a tele-TASK account here.
with the manuscript function you'll be able to create your own digital lecture manuscript.
However, in order to link all your notes with your user profile it is required that you
login to the tele-TASK portal to use this functionality.
If you don't have an account yet, you may register for a tele-TASK account here.
Place a Marker
Dear user,
with the marker function you'll be able to create your own digital time markers.
However, in order to link all your markers with your user profile it is required that you
login to the tele-TASK portal to use this functionality.
If you don't have an account yet, you may register for a tele-TASK account here.
with the marker function you'll be able to create your own digital time markers.
However, in order to link all your markers with your user profile it is required that you
login to the tele-TASK portal to use this functionality.
If you don't have an account yet, you may register for a tele-TASK account here.
Please enable javascript to use this function.
Keyword
Please enable javascript to use this function.
Zu meinen Videolisten hinzufügen
Dear user,
with the playlist function you'll be able to create your own lecture video playlists.
However, in order to link all your playlists with your user profile it is required that you
login to the tele-TASK portal to use this functionality.
If you don't have an account yet, you may register for a tele-TASK account here.
with the playlist function you'll be able to create your own lecture video playlists.
However, in order to link all your playlists with your user profile it is required that you
login to the tele-TASK portal to use this functionality.
If you don't have an account yet, you may register for a tele-TASK account here.
Playlists
This content is not used in any playlist.