Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
article
Free access

Maintaining views incrementally

Published: 01 June 1993 Publication History
  • Get Citation Alerts
  • Abstract

    We present incremental evaluation algorithms to compute changes to materialized views in relational and deductive database systems, in response to changes (insertions, deletions, and updates) to the relations. The view definitions can be in SQL or Datalog, and may use UNION, negation, aggregation (e.g. SUM, MIN), linear recursion, and general recursion.
    We first present a counting algorithm that tracks the number of alternative derivations (counts) for each derived tuple in a view. The algorithm works with both set and duplicate semantics. We present the algorithm for nonrecursive views (with negation and aggregation), and show that the count for a tuple can be computed at little or no cost above the cost of deriving the tuple. The algorithm is optimal in that it computes exactly those view tuples that are inserted or deleted. Note that we store only the number of derivations, not the derivations themselves.
    We then present the Delete and Rederive algorithm, DRed, for incremental maintenance of recursive views (negation and aggregation are permitted). The algorithm works by first deleting a superset of the tuples that need to be deleted, and then rederiving some of them. The algorithm can also be used when the view definition is itself altered.

    References

    [1]
    Krzysztof R. Apt, Howard A. Blair, and Adrian Walker. Towards a Theory o} Declarative Knowledge. In Foundations o} Deductive Databases and Logic Programming. Editor J. Minker, 1988 Morgan Kaufmann.
    [2]
    Peter O. Buneman and Eric K. Clemons. Efficiently Monitoring Relational Databases. In A C#I TODS, Vol 4, No. 3, 1979, 368-382.
    [3]
    J.A. Blakeley, N. Coburn, and P. Larson. Updating Derived Relations: Detecting Irrelevant and Autonomously Computable Updates. In A CM TODS Vol 14, No. 3, 369-400, 1989.
    [4]
    Veronique Benzaken, Christophe Lecluse, and Philippe Richard. Enforcing Integrity Constraints in Database Programming Languages. TR Altair 68-91, Altair, France, 1991.
    [5]
    J.A. Blakeley, P. Larson, and F. W. Tompa. Ej#- c#ently Updating Materiahzed V#ews. In SIGMOD 1986, pages 61-71.
    [6]
    F. Bry, R. Manthey, and B. Martens. Integrity Verification in Knowledge Bases. In Logic Programm#ng, LNAI #9#, pages 114-189, 1992.
    [7]
    J.A. Blakeley and F. W. Tompa. Maintaining Materialized Views without Accessing Base Data. Information Systems, 13(4):393-406, 1988.
    [8]
    Stefano Ceri and Jennifer Widom. Deriving Production Rules for Incremental View Maintenance. In 17th VLDB, 1991.
    [9]
    Stefano Ceri and Jennifer Widom. Deriving Incremental Production Rules for Deductive Data. IBM RJ 9071, IBM Almaden, 1992.
    [10]
    S. Dar, R. Agrawal, and H. V. Jagadish. Optimization of generalized transitive closure, in Seventh IEEE International Con}erence on Data Engineering, Kobe, Japan, 1991.
    [11]
    Guozhu Dong and Jianwen Su. Incremental and Decremental Evaluation of Transitive Closure by First-Order Queries. TRCS 92-18, University of California, Santa Barbara, 1992.
    [12]
    Guozhu Dong and Rodney Topor. Incremental Evaluation o} Datalog Queries. In ICDT, 1992.
    [13]
    Ashish Gupta, Dinesh Katiyar, and Inderpal Singh Mumick. Counting Solutions to the View Maintenance Problem. In Workshop on Deductive Databases, JICSLP, 1992.
    [14]
    Ashish Gupta, Inderpal Singh Mumick, and V. S. Subrahmanian. Maintaining views incrementally. TR 921214-19-TM, AT&T Bell Labs, 1992.
    [15]
    John V. Harrison and Suzanne Dietrich. Maintenance of Materialized Views in a Deductive Database: An Update Propagation Approach. In Workshop on Deductive Databases, JICSLP, 1992.
    [16]
    ISO_ANSI. ISO-ANSI Working Draft: Database Language SQL2 and SQL3; X3H2; ISO/IEC JTC1/SC21/WG3, 1990.
    [17]
    V. Kuchenhoff. On the Efficient Computation of the Difference Between Consecutive Database States. In DOOD, LNCS 566, 1991.
    [18]
    Inderpal Singh Mumick and Oded Shmueli. Finiteness Properties of Database Queries. In Fourth Australian Database Conference, 1993.
    [19]
    Inderpal Singh Mumick. Query Optimization in Deductive and Relational Databases. Ph.D. Thesis, Stanford University, CA 94305, 1991.
    [20]
    J.M. Nicolas and Yazdanian. An Outline of BDGEN: A Deductive DBMS. In In}ormation Processing, pages 705-717, 1983.
    [21]
    Xiaolei Qian and Gio Wiederhold. Incremental Recomputation o} Active Relational Expressions. In A CM TKDE, 1991.
    [22]
    Torre Risch and Martin SkSld. Active rules based on object-oriented queries. To Appear, A CM TKDE, 1993.
    [23]
    Oded Shmueli and Alon Itai. Maintenance o} lQews. In Sigmod Record, 14(2):240-255, 1984.
    [24]
    Ulf Schreier, Hmnid Pirahesh, Rakesh Agrawal, and C. Mohan. Alert: An Architecture for Transforming a Passive DBMS Into an Active DBMS. In 17th VLDB, pages 469-478, 1991.
    [25]
    Jeffrey D. Ullman. Principles o} Database and Knowledge-Base Systems, Volumes I and 2. Computer Science Press, 1989.
    [26]
    Toni Urpi and Antoni Olive. A Method for Change Computation in Deductive Databases. In 18th VLDB, pages 225-237, 1992.
    [27]
    Allen Van Gelder. Negation as failure using tight derivations for general logic programs. In Third IEEE Symposium on Logic Programming, 1986. Springer-Verlag.
    [28]
    Ouri Wolfson, Hasanat M. Dewan, Salvatore J. Stolfo, and Yechiam Yemini. Incremental Evaluation of Rules and its Relationship to Parallelism. In SIGMOD 1991, pages 78-87.

    Cited By

    View all
    • (2024)Early detection of temporal constraint violationsInformation and Computation10.1016/j.ic.2023.105114296(105114)Online publication date: Jan-2024
    • (2024)Temporal graph patterns by timed automataThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-023-00795-z33:1(25-47)Online publication date: 1-Jan-2024
    • (2023)Enhancing datalog reasoning with hypertree decompositionsProceedings of the Thirty-Second International Joint Conference on Artificial Intelligence10.24963/ijcai.2023/377(3383-3393)Online publication date: 19-Aug-2023
    • Show More Cited By

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM SIGMOD Record
    ACM SIGMOD Record  Volume 22, Issue 2
    June 1, 1993
    558 pages
    ISSN:0163-5808
    DOI:10.1145/170036
    Issue’s Table of Contents
    • cover image ACM Conferences
      SIGMOD '93: Proceedings of the 1993 ACM SIGMOD international conference on Management of data
      June 1993
      566 pages
      ISBN:0897915925
      DOI:10.1145/170035
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 01 June 1993
    Published in SIGMOD Volume 22, Issue 2

    Check for updates

    Qualifiers

    • Article

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)342
    • Downloads (Last 6 weeks)60
    Reflects downloads up to

    Other Metrics

    Citations

    Cited By

    View all
    • (2024)Early detection of temporal constraint violationsInformation and Computation10.1016/j.ic.2023.105114296(105114)Online publication date: Jan-2024
    • (2024)Temporal graph patterns by timed automataThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-023-00795-z33:1(25-47)Online publication date: 1-Jan-2024
    • (2023)Enhancing datalog reasoning with hypertree decompositionsProceedings of the Thirty-Second International Joint Conference on Artificial Intelligence10.24963/ijcai.2023/377(3383-3393)Online publication date: 19-Aug-2023
    • (2023)A Step Toward Deep Online AggregationProceedings of the ACM on Management of Data10.1145/35892691:2(1-28)Online publication date: 20-Jun-2023
    • (2023)Foreign Keys Open the Door for Faster Incremental View MaintenanceProceedings of the ACM on Management of Data10.1145/35887201:1(1-25)Online publication date: 30-May-2023
    • (2023)Riffle: Reactive Relational State for Local-First ApplicationsProceedings of the 36th Annual ACM Symposium on User Interface Software and Technology10.1145/3586183.3606801(1-16)Online publication date: 29-Oct-2023
    • (2023)What Can Database Query Processing Do for Instance-Spanning Constraints?Business Process Management Workshops10.1007/978-3-031-25383-6_11(132-144)Online publication date: 9-Feb-2023
    • (2022)Parallel Maintenance of Materialized Views in Large-Scale Analytic PlatformsInternational Journal of Organizational and Collective Intelligence10.4018/IJOCI.30520912:1(1-19)Online publication date: 21-Jul-2022
    • (2022)Declarative smart contractsProceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3540250.3549121(281-293)Online publication date: 7-Nov-2022
    • (2022)Efficient Incrementialization of Correlated Nested Aggregate Queries using Relative Partial Aggregate Indexes (RPAI)Proceedings of the 2022 International Conference on Management of Data10.1145/3514221.3517889(136-149)Online publication date: 10-Jun-2022
    • Show More Cited By

    View Options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Get Access

    Login options

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media