On Propagation of Deletions in addition to Annotations through Views Wang-C

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On Propagation of Deletions in addition to Annotations through Views Wang-C

Chapman University, US has reference to this Academic Journal, On Propagation of Deletions in addition to Annotations through Views Wang-Chiew Tan University of Pennsylvania Database Group Joint work alongside Peter Buneman in addition to Sanjeev Khanna Data Annotations (share annotations) Knowledge sharing through ?annotations? Annotations on data at various levels of granularity, annotations on annotations Improve accuracy of data data in addition to annotations can be reviewed by independent parties Annotations: loosely structured Source Data: proprietary fixed schema A system that overlays annotations on existing data ?big business? in scientific databases All Restaurants (View 1) Cheap Restaurants (View 2) Yummy chicken curry!! NYRestaurants (Source Table) Restaurant Cost Type Peacock Alley Bull & Bear Pacifica Soho Kitchen & Bar Zip $$$ French 10022 $$$ Seafood 10022 $ Chinese 10013 $ American 10022 Data Annotations (share annotations)

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Data Annotations Communicate ?meta data? through annotations ?bounce? or ?spread? annotations around by piggybacking annotations on data items in the source-query-view model. An annotation is placed in the view where do we place the annotation on source? Annotation placement problem presented in relational setting results carry over so that fragments of XML (hierarchical model) Source: Relational Database View : result of query applied on source Model: Not an easy problem! Location in addition to Propagation Rules A location is a triple: (R, t, A) A1 A2 A3 A1 A2 A3 A3 A1 A2 A3 A1 A2 A2 A3 A1 A2 A3 A1 A2 A3 A1 A2 A3 A1 A2 A3 R R R1 R2 R1 R2 relation name tuple in R A is an attribute in schema of R Propagation Rules: Select: Project: Join: Union: Annotation Placement Problem Annotation Placement Problem: Given a view V = Q(S) in addition to an annotation A placed in the view V, decide if there is an annotation in the source that when propagated so that the view, produces no other annotation except A. Q = query S = data source ?side-effect-free annotation? : an annotation on the source that produces no other annotation except A in the view S

A Dichotomy Theorem (a) It is NP-hard so that decide if there is a side-effect-free annotation in consideration of a PJ query. (b) There is a polynomial time algorithm in consideration of queries which do not simultaneously contain a Project in addition to a Join operation. Theorem: Project in addition to Join Query Intuition: PJ can encode 3SAT (x1 + x2 + x3) . . . ( x3 + x5 + x2) x1 x2 x3 C1 C1 Cm . T – true F – false . . . Project in addition to Join Query Intuition: PJ can encode 3SAT (x1 + x2 + x3) ? ( x3 + x5 + x2) Assignment tuples: All possible satisfying assignments in consideration of C1 x1 x2 x3 C1 C1 C1 C1 Assignment tuples: All possible satisfying assignments in consideration of Cm d d d C1 . Cm Output C1 Cm F F F T F F C1 F T F C1 T T F C1 F F T C1 F T T x3 x5 x2 Cm Cm Cm Cm d d d T F F F T F Cm T T F Cm F F T Cm T F T Cm F T T T – true F – false C1 T T T Cm T T T Dummy tuple Dummy tuples C?m d d d C1 . C?m . Query: Join, then Project on C1 ? Cm

Alternative Switching Technologies: Optical Circuit Switches Hakim Weatherspoon Where are we in the semester? Goals in consideration of Today Technology: Optical Circuit Switch Wavelength Division Multiplexing Design requirements c-Through (a specific design) c-Through – traffic de-multiplexing Testbed setup Evaluation MapReduce Overview MapReduce sort 10GB random data MapReduce sort 10GB random data Yahoo Gridmix benchmark Summary Related Work Before Next time

Related Work on Annotations Superimposed Information (D. Maier, L. Delcambre [WebDB?99]) data ?placed over? existing information eg. bookmark files, schema of a database Annotation Systems Annotea (W3C) annotate web pages location is defined alongside XPointer Multivalent Browser (R. Wilensky, T. A. Phelps. UC Berkeley DL Project) annotate on PDF files, HTML, etc. robust locations BioDAS (Distributed Annotation Server) (L.Stein et. al ) annotate on genome sequences notion of location is genome specific No one has formally studied annotation placement problem The classical view deletion problem A view tuple is so that be deleted What changes should be made so that the source? Many kinds of view-to-source deletion translations eg. deletion-to-insertion, deletion-to-modification, etc. Update Semantics of Relational Views (F. Banchilon, N. Spyratos, [TODS?81]) On the correct translation of Update Operations on Relational Views (U. Dayal, P. Bernstein, [TODS?82]) Algorithms in consideration of Translating View Updates so that Database Updates in consideration of Views Involving Selections, Projections in addition to Joins (A. M. Keller, [PODS?85]) deletion-to-deletion Run-Time translations of View Tuple Deletions Using Data Lineage (Y. Cui, J. Widom, [2001]) exploits lineage information so that find ?side-effect free? deletions whenever possible View Deletion Problem (Deletion-to-deletion translation) View Deletion Problem (minimize view side-effect): Given a view V=Q(S) in addition to a tuple t in V, decide if there is a side-effect free deletion in consideration of t ?side-effect-free deletion? : a set of source tuples whose removal from the database will only remove t from the view Source: Relational Database View : result of query applied on source

A Dichotomy Theorem Theorem (a) is true even in consideration of a constant size PJ query involving only two relations! (a) It is NP-hard so that decide if there is a side-effect free deletion in consideration of a PJ or JU query in normal form. (b) There is a polynomial time algorithm so that find the set of source deletions alongside minimum side-effects in consideration of all other queries, i.e., queries that involve only S,P,U or S,J operators). Theorem: PROJ A,C(R1 JOIN R2) View Deletion: PJ Query It is NP-hard so that decide if there is a side-effect free deletion in consideration of a PJ query in normal form. A B B C R1 R2 Theorem: Ongoing in addition to Future Work Implementation of annotation system on RDBMS special cases of PJ queries alongside polynomial time algorithm PJ queries that do not project out key information on XML effects on query languages?

Do we need an ?annotation-conscious? QL? The same query in different languages, but different annotation behavior Emp(Name, Sal, Dept) [Name:?Joe?, Sal:50K , Dept:?Marketing? ] Relational Algebra: Emp JOIN Department SQL: SELECT e.Name, e.Sal, e.Dept, d.Manager FROM Emp e, Department d WHERE e.Dept = d.Dept [Name:?Joe?, Sal:50k] Department(Dept, Manager) [Dept:?Marketing? , Manager:?Jane?] Do we need an ?annotation-conscious? QL? Relational algebra seems so that suggest a natural set of propagation rules SQL seems so that suggest another natural propagation rule one that is based on variable bindings Not clear how we extend the semantics of query languages so that annotation propagation is ?well-behaved?. Should a query language be ?annotation-conscious? ? OR Should the user be allowed so that control which annotation gets propagated so that where? End of Talk

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