Video
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Lecture Structure
- Überblick (00:00:01)
- WCIH (00:00:03)
- Überblick (00:00:07)
- WCIH Das Problem (00:01:45)
- öderiertes Schema (00:01:54)
- Modellierung von Datenquellen (00:01:59)
- Global as ÜEW Local EIS View (00:02:12)
- Überblick (00:02:13)
- Global S View Local 85 View (00:02:14)
- Global S ÜGW Local EIS View (00:04:15)
- Überblick (00:05:06)
- W Fl IlTl LGV? Eine andere SiChtWEiSe (00:05:08)
- Local S View LaV Beispiel (00:07:12)
- Local as View (Lav) Beispiel (00:07:30)
- Fi m(Tite Regie Jahr Genre) (00:07:30)
- SELECT = m e fFRO (00:07:54)
- vlDB(Tite Regie Jahr Genre) (00:07:54)
- CREATE V E ASSELECT FR Film (00:07:54)
- S12 vlDB(Tite Regie Jahr Genre) (00:07:55)
- Programm(Kiho Titel Zeit) (00:09:35)
- Local as View (La ) 1 pie (00:10:41)
- I i 10ÜB( il 10 ( 6ß ES) (00:10:41)
- JlUl )dl db DOI IEIIIGFi m(Tite Regie Jahr Genre)Programm(Kino Titel Zeit) (00:10:41)
- Local as View (Lav) Beispiel (00:11:01)
- Local S View LaV Beispiel (00:11:35)
- Local as View LaV Beispiel (00:12:44)
- Local as View (Lav) Beispiel (00:12:56)
- S82 IeueFi me(Tite Regie Genre) (00:12:56)
- Progfamm(KiF o Tire zen) (00:12:56)
- lS8 Ni äilme itel Regie (00:14:26)
- Local S View LaV Beispiel (00:15:01)
- Auch implizite Einschränkungen können in den View (00:15:01)
- S82 IeueFi me(Tite Regie Genre) (00:15:01)
- Local as View LaV Globale ICs (00:15:13)
- Local as View LaV G oba e ICS (00:15:17)
- Local as View (Lav) G oba e ICS (00:15:22)
- Local S View LaV G oba e ICy (00:15:41)
- Local as View (Lav) lokale ICs (00:16:56)
- Local as View (Lav) lokale (00:17:41)
- (WHERE Jahr = 2004) (00:17:41)
- FROM Film (00:17:41)
- bales SeheFi m(Tite Regie Jahr Genre) (00:17:41)
- Local as View (Lav) oka e ICs Ä CREATE VIEW S1 AS (00:19:00)
- REATEVIEW S5 AS SELECT Titel Regie Genre On Q (WHEREJahr 2004) (00:19:00)
- OO l CUCFllIllClNBLL lIlC h (Nebenbed ngung Jahr CC ) ( a r )S4 NeueF mel e(T te Reg e Genre)(Nebenbed ngung Jahr VOM EC te Re e GenreFROM F lm(Nebe bed 9L 9 ä 1 WHEREJahr 2000Z M C AJ Akrue e =i me(Tire Regie 9 = 1 REATE Vl EW S5 AS (00:19:00)
- Local as View (Lav) I CREATE VIEW S1 AS (00:21:07)
- raem mihu Lokale ICs (00:22:03)
- n e que ß (00:23:03)
- n enque m Lokale ICs (00:28:07)
- Local as View (Lav) ßg obaleßls (00:29:01)
- W) FROM NeuerFi m (00:29:01)
- a L r xu v Neue r n WHERE JAHR 2000) (00:29:01)
- CREATE V EWA eFi meNel1ASSELECT FROM NeuerFi mn u cnc mn fmnm (00:29:01)
- Überblick (00:29:39)
- LaV Anwendungen (00:29:43)
- Lav Anwendung Anfrageoptimierun (00:30:01)
- Anwendungen (00:30:02)
- Lav Anwendung Anfrageoptimierung (00:32:14)
- Lav Anwendung Anfrageoptimierur (00:34:22)
- Write auf Basisrelatio (00:34:22)
- 0 Write auf MV (00:34:22)
- (materialized views MV) auf (00:34:22)
- Materia isierte Sichten (00:34:22)
- Write auf Basisrelation (00:39:10)
- Ilv vay (00:39:10)
- Nl 4 (00:39:10)
- Table (00:39:10)
- Q62R1 R2 R3 (00:39:10)
- IQ2 R1 A=1o Q5 R4 (00:39:10)
- Q42 R1 x R2 (00:39:10)
- Lav Anwendung Datawa ehouese Design (00:39:39)
- Gegeben eine query workload welche Sichten sollte Ich (00:39:39)
- Gegeben eine query workluad (00:39:39)
- La Anwendung Semantisches Caching (00:39:40)
- Lav Anwendung Datenintegration (00:42:20)
- Überblick (00:42:28)
- Anfrageplanung (00:42:33)
- E1 Verschiedene Piäne werden durch UNION zusammengefasst (00:42:33)
- Die geeignete Verknüpfung von q (00:42:33)
- Eine Anfrage q an das globale Schema (00:42:33)
- Anfrageplan (00:44:25)
- Anfrageplanung (00:45:24)
- Anfrageplan (00:46:18)
- Query Containment (00:48:35)
- Der wichtige Teil ist der letzte für alle möglichen Instanzen I von S (00:48:35)
- q1 (I) q2(I) für alle möglichen I (00:48:35)
- gegen I Sei q(I) das Ergebnis einer Anfrage q angewandtauf I Dann ist (00:48:35)
- Anfrageplan (00:49:06)
- Die q heißen Teilanfragen oder Teilpläne (00:49:07)
- In der Regel gibt es viele Anfragepläne (00:49:07)
- Wir nennen q1 q einen Anfrageplan (00:49:07)
- Anfrageplanung (00:49:08)
- Überblick (00:49:09)
- Anfrageplanung (00:49:13)
- Verschiedene Pläne werden durch UNION zusammengefasst (00:49:13)
- Die geeignete Verknüpfung von q (00:49:13)
- Anfrageplan (00:49:50)
- Die q heißen Teilanfragen oder Teilpläne (00:49:50)
- Gegeben eine globale Anfrage q Ein Anfrageplan p für q ist eine (00:49:50)
- Wir nennen q1 q einen Anfrageplan (00:49:50)
- Query Containment (00:49:53)
- Semantische KOlTe theit (00:52:17)
- Anfragepläne (00:52:18)
- Anfragebearbeitung LaV (00:52:19)
- Anfragepläne (00:52:50)
- res r(q) (00:52:50)
- Gegeben eine globale Anfrage q Seien pl (00:52:50)
- 3 berechnet wird ist Sache der (00:52:54)
- es lr(p ) (00:52:54)
- Viele Anfragepläne (00:52:55)
- V ele Anfrageplär e (00:57:50)
- Anfragebearbeitung LaV (01:00:23)
- Beispiel (01:00:42)
- a v sua s erung (OWA) (01:05:29)
- Beispiel (01:06:19)
- AND (01:06:19)
- Quelle 2 Alle HPI Vorlesungen (01:06:19)
- Lehrt(prof kurs id sem eval univ)Kufslkufs Ü mel UWW) Quelle2 Alle HPI Vorlesungenn ankveranstat TE VIEW HPI VLASCREATE VIEW DB kursAS ECT e univ I sE SELECT K tite L prof K kurs id K uni FROM eh 11 Kurs KFROM LehrtL KursK WHERELkurs d Kkurs d (01:08:59)
- av v sua s erung (ovvA) (01:09:00)
- LaV ViSu alisierun (OWA (01:10:22)
- av v sua s erung (ovvA) (01:10:23)
- av v sua s erung (ovvA) (01:12:52)
- m @Nutze age (01:13:53)
- LaV Visualisierung 4 (ovv ) (01:13:54)
- Beispiel (01:14:27)
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Zu meinen Videolisten hinzufügen
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