ConQuer: Efficient Management of Inconsistent Databases Presented by: Presented by: Ariel Fuxman (Univ. of Toronto) Ariel Fuxman (Univ. of Toronto) Joint work with: Diego Fuxman (Univ. Nacional del Sur) Diego Fuxman (Univ. Nacional del Sur) Renée J. Miller (Univ. of Toronto) Renée J. Miller (Univ. of Toronto)

Ariel Fuxman, Diego Fuxman, Renée J. Miller 2 A system designed to answer SQL queries over inconsistent databases A system designed to answer SQL queries over inconsistent databases ConQuer 130KMary 110KMary 400KPaul 200KPeter 40KPeter IncomeName name should be the key INCONSISTENT DATABASE

Ariel Fuxman, Diego Fuxman, Renée J. Miller 3 One Application Sales Shipping Customer Support Web Forms Demographic Data IntegratedCustomerDatabase Customer Relationship Management (CRM)

Ariel Fuxman, Diego Fuxman, Renée J. Miller 4 Disagreement Between Sources Which tuple for Peter should we delete? Which tuple for Peter should we delete? Removing both tuples loses consistent information Removing both tuples loses consistent information Deciding the correct income may require human intervention Deciding the correct income may require human intervention 110K… 20 Union Street Mary 400K… 100 Bloor Street Paul …. … 276 College Street address 40KPeter incomename 400K… 100 Bloor Street Paul 130K… 20 Union Street Mary …. … 276 College Street address 200KPeter incomename sales web

Ariel Fuxman, Diego Fuxman, Renée J. Miller 5 Inconsistent Integrated Database name…income Peter…40K Paul…400K Mary…110K name…incomePeter…200K Paul…400K Mary…130K name…incomePeter…40K Peter…200K Paul…400K Mary…110K Mary…130K Sales Web Integrated Database Transfer all conflicting tuples to the integrated database INCONSISTENT DATABASE

Ariel Fuxman, Diego Fuxman, Renée J. Miller 6 Query Answering q=“Get customers who make more than 100K” 130K 110K 400K 200K 40K income web sales sales/web web sales Mary Mary Paul Peter Peter name Peter,Paul,Mary Peter should NOT be offered a Platinum card!! Offering a Platinum credit card…

Ariel Fuxman, Diego Fuxman, Renée J. Miller 7 Get customers who possibly make more than 100K Get customers who possibly make more than 100K Get customers who certainly make more than 100K Get customers who certainly make more than 100K There is considerable work in the literature about theoretical aspects of consistent answers There is considerable work in the literature about theoretical aspects of consistent answers ConQuer: Efficient computation of consistent answers ConQuer: Efficient computation of consistent answers Semantics of Query Answering CONSISTENT ANSWER [Arenas, Bertossi, Chomicki 99]

Ariel Fuxman, Diego Fuxman, Renée J. Miller 8 Commercial database engine Query Answering in ConQuer Query q Keys Keys Rewritten Q * ConQuer’sRewritingAlgorithm [ICDT 05] [SIGMOD 05] Inconsistentdatabase May not get consistent answers Consistent answer to q

Ariel Fuxman, Diego Fuxman, Renée J. Miller 9 Demo Present a case study of an inconsistent database about airports and cities Present a case study of an inconsistent database about airports and cities Explain the automatically generated rewritings Explain the automatically generated rewritings Deal with Select-Project-Join queries with grouping and aggregation Deal with Select-Project-Join queries with grouping and aggregation

Ariel Fuxman, Diego Fuxman, Renée J. Miller 10 ConQuer papers A. Fuxman, E. Fazli, and R. J. Miller. ConQuer: Efficient Management of Inconsistent Databases, SIGMOD A. Fuxman, E. Fazli, and R. J. Miller. ConQuer: Efficient Management of Inconsistent Databases, SIGMOD A. Fuxman and R. J. Miller. First-Order Query Rewriting for Inconsistent Databases, ICDT A. Fuxman and R. J. Miller. First-Order Query Rewriting for Inconsistent Databases, ICDT 2005.

Ariel Fuxman, Diego Fuxman, Renée J. Miller 11 Schema A_ICAO a_name a_city a_country a_latdeg a_latmin a_latsec a_latdir a_height C_IATA c_icao CI_NAME CI_COUNTRY ci_population ci_year CODES AIRPORTS CITIES