skip to main content
10.1145/2602622.2602624acmconferencesArticle/Chapter ViewAbstractPublication PagesmodConference Proceedingsconference-collections
research-article

Automated schema design for NoSQL databases

Published:18 June 2014Publication History

ABSTRACT

Selecting appropriate indices and materialized views is critical for high performance in relational databases. By example, we show that the problem of schema optimization is also highly relevant for NoSQL databases. We explore the problem of schema design in NoSQL databases with a goal of optimizing query performance while minimizing storage overhead. Our suggested approach uses the cost of executing a given workload for a given schema to guide the mapping from the application data model to a physical schema. We propose a cost-driven approach for optimization and discuss its usefulness as part of an automated schema design tool.

References

  1. HBase: A Distributed Database for Large Datasets. Retrieved March 7, 2013 from http://hbase.apache.org.Google ScholarGoogle Scholar
  2. S. Agrawal, S. Chaudhuri, and V. R. Narasayya. Automated Selection of Materialized Views and Indexes in SQL Databases. In VLDB '00, pages 496--505, San Francisco, CA, USA, 2000. Morgan Kaufmann Publishers Inc. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Benoit Dageville, D. Das, K. Dias, K. Yagoub, and M. Zait. Automatic SQL tuning in oracle 10g. VLDB '04, 30:1098--1109, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. V. Benzaken, G. Castagna, K. Nguyen, and J. Siméon. Static and dynamic semantics of NoSQL languages. In POPL '13, pages 101--114, New York, New York, USA, 2013. ACM Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. K. S. Beyer, V. Ercegovac, R. Gemulla, A. Balmin, M. Y. Eltabakh, C.-C. Kanne, F. Özcan, and E. J. Shekita. Jaql: A Scripting Language for Large Scale Semistructured Data Analysis. PVLDB, 4(12):1272--1283, 2011.Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. A. Calil and S. Mello. SimpleSQL : A Relational Layer for SimpleDB. In Advances in Databases and Information Systems, pages 99--110. 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. R. Cattell. Scalable SQL and NoSQL data stores. ACM SIGMOD Record, 39(4):12--27, May 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. E. Hewitt. Cassandra: The Definitive Guide. O'Reilly Media, Sebastopol, CA, 2 edition, 2011.Google ScholarGoogle Scholar
  9. A. Lakshman and P. Malik. Cassandra: a decentralized structured storage system. ACM SIGOPS Operating Systems Review, 44(2):35, Apr. 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. A. Lamb, M. Fuller, R. Varadarajan, N. Tran, B. Vandiver, L. Doshi, and C. Bear. The Vertica Analytic Database : C-Store 7 Years Later. In VLDB '12, volume 5, pages 1790--1801, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. A. Rasin and S. Zdonik. An Automatic Physical Design Tool for Clustered Column-Stores. In EDBT '13, pages 203--214, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. G. L. Sanders and S. Shin. Denormalization effects on performance of RDBMS. In Proceedings of the 34th Annual Hawaii International Conference on System Sciences. IEEE Comput. Soc, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. S. Scherzinger, E. C. De Almeida, F. Ickert, and M. D. Del Fabro. On the necessity of model checking NoSQL database schemas when building SaaS applications. Proceedings of the 2013 International Workshop on Testing the Cloud - TTC 2013, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. M. Stonebraker, D. J. Abadi, A. Batkin, X. Chen, M. Cherniack, M. Ferreira, E. Lau, A. Lin, S. Madden, E. O. Neil, P. O. Neil, A. Rasin, N. Tran, and S. Zdonik. C-Store : A Column-oriented DBMS. In VLDB '05, pages 553--564, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. O. G. Tsatalos, M. H. Solomon, and Y. E. Ioannidis. The GMAP: a versatile tool for physical data independence. The VLDB Journal The International Journal on Very Large Data Bases, 5(2):101--118, Apr. 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. T. Vajk, L. Deák, K. Fekete, and G. Mezei. Automatic NoSQL Schema Development: A Case Study. In Artificial Intelligence and Applications, number Pdcn, pages 656--663. Actapress, 2013.Google ScholarGoogle Scholar
  17. D. C. Zilio, J. Rao, S. Lightstone, G. Lohman, A. Storm, C. Garcia-Arellano, and S. Fadden. DB2 design advisor: integrated automatic physical database design. In VLDB '04, pages 1087--1097, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Automated schema design for NoSQL databases

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      SIGMOD'14 PhD Symposium: Proceedings of the 2014 SIGMOD PhD symposium
      June 2014
      58 pages
      ISBN:9781450329248
      DOI:10.1145/2602622

      Copyright © 2014 ACM

      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 the author(s) 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: 18 June 2014

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article

      Acceptance Rates

      SIGMOD'14 PhD Symposium Paper Acceptance Rate10of13submissions,77%Overall Acceptance Rate40of60submissions,67%

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader