Information Integration Using Logical Views Jeffrey D. Ullman

Overview Theoretical Background Synthesizing Queries From Views Information Integration Systems Conclusions

Theoretical Background

Conjunctive Queries (CQ) (NP-Complete) – Query containment – Query equivalence – Q1: p(X,Z) :- a(X,Y) & a(Y,Z) – Q2: p(X,Z) :- a(X,Y) & a(V,Z) CQ’s With Negation ( -Complete) – Q1: p(X,Z) :- a(X,Y) & a(Y,Z) & NOT a(X,Z) CQ’s With Arithmetic Comparision ( -Complete) – Q1: p(X,Z) :- a(X,Y) & a(Y,Z) & X<Y Datalog Programs – p(A,C) :- a(A,B) & b(B,C)

Synthesizing Queries From Views Views Assumption: – Conjunctive Queries Answers – Equivalence – Containment

Solving Queries by Views Views – v1(Y,Z) :- p(X,Y) & p(Y,Z) – v2(X,Z) :- p(X,Y) & p(Y,Z) Query: q(c) :- p(O,A) & p(A,B) & p(B,C) Answer: s1(C) :- v2(O,D) & v1(D,C) Expansion: – e1(C) :- p(O,E) & p(E,D) & p(F,D) & p(D,C)

Solving Queries by Views (Cont. ) Query: q(c) :- p(O,A) & p(A,B) & p(B,C) Answer: – s1(C) :- v2(O,D) & v1(D,C) – e1(C) :- p(O,E) & p(E,D) & p(F,D) & p(D,C) Other Solutions – s2(C) :- v1(O,D) & v2(D,C) – s3(C) :- v1(O,D) & v2(D,E) & v1(E,C) – s4(C) :- v2(O,D) & v1(D,C) & v2(C,E)

Minimal-Solution Theorems NP-complete (Query Length) Minimal Solution – S  Q – There is no solution T for Q such that S  T  Q and T has fewer sub goals than S Theorem1 Theorem2

Information Integration Systems Information Manifold (IM) – AT&T – Local-as-View (Lav) – Source relations defined as views of mediator relations Tsimmis – Stanford and IBM – Global-as-View (Gav) – Mediator relations defined as views of source relations

Information Manifold (IM) Local-as-view approach Description Logic called CARIN Characters (top-down) – A collection of global predicates – Views as source descriptions (some) – Constraints

IM Example Global Predicates

IM Example (Cont.) Views Query: “What are Sally’s phone and office?” Mediator

Query Rewriting

IM Example (Cont.) Answer: Expansion:

Answering Queries in IM Global Predicates View Definitions Source Constraints How much do the mediators know? What’s the hard part? (Query Rewriting!)

Tsimmis OEM and MSL

Tsimmis Example Exported OEM Objects Query: “What are Sally’s phone and office?” Mediator

Answering Queries in Tsimmis MSL Mediator Description View Definitions How much do the mediators know? What’s the hard part? (Mediator description!)

IM vs. Tsimmis Query Processing Adding Sources Levels of Mediation Semistructured Data Constraints Automatic Generation of Components