Encyclopedia of Database Systems

Living Edition
| Editors: Ling Liu, M. Tamer Özsu

Distributed Query Processing

Living reference work entry
DOI: https://doi.org/10.1007/978-1-4899-7993-3_704-2



Distributed query processing is the procedure of answering queries (which means mainly read operations on large data sets) in a distributed environment where data is managed at multiple sites in a computer network. Query processing involves the transformation of a high-level query (e.g., formulated in SQL) into a query execution plan (consisting of lower-level query operators in some variation of relational algebra) as well as the execution of this plan. The goal of the transformation is to produce a plan which is equivalent to the original query (returning the same result) and efficient, i.e., to minimize resource consumption like total costs or response time.

Historical Background

Motivated by the needs of large companies and organizations that manage their data at different sites, distributed database systems are subject of research since the late 1970s. In these years, three important prototype systems were...


Query Processing Relational Algebra Query Execution Query Operator Global Relation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in to check access

Recommended Reading

  1. 1.
    Bernstein PA, Goodman N, Wong E, Reeve CL, Rothnie Jr JB. Query processing in a system for distributed databases (SDD-1). ACM Trans Database Syst. 1981;6(4):602–25.CrossRefMATHGoogle Scholar
  2. 2.
    Ceri S, Pelagatti G. Correctness of query execution strategies in distributed databases. ACM Trans Database Syst. 1983;8(4):577–607.CrossRefMATHGoogle Scholar
  3. 3.
    Franklin M, Jonsson B, Kossmann D. Performance tradoffs for client-server query processing. In: Proceedings of ACM SIGMOD International Conference on Management of Data: Montreal, Canada; 1996. p. 149–60.Google Scholar
  4. 4.
    Levy A (ed): Special Issue on Adaptive Query Processing, Bulletin of Tech Committee on Data Eng. 200; 23(2).Google Scholar
  5. 5.
    Kossmann D. The state of the art in distributed query processing. ACM Comput Surv. 2000;32(4):422–69.CrossRefGoogle Scholar
  6. 6.
    Kossmann D, Franklin M, Drasch G, Ag W. Cache investment: integrating query optimization and distributed data placement. ACM Trans Database Syst. 2000;25(4):517–58.CrossRefMATHGoogle Scholar
  7. 7.
    Özsu MT, Valduriez P. Principles of distributed database systems. 2nd ed. Upper Saddle River: Prentice-Hall; 1999.Google Scholar
  8. 8.
    Stonebraker M. The design and implementation of distributed INGRES. In: Stonebraker M, editor. The INGRES papers. Reading: Addison-Wesley; 1986.Google Scholar
  9. 9.
    Stonebraker M, Aoki P, Litwin W, Pfeffer A, Sah A, Sidell J, Staelin C, Yu A. Mariposa: a wide-area distributed database system. VLDB J. 1996;5(1):48–63.CrossRefGoogle Scholar
  10. 10.
    Stonebraker M, Hellerstein JM. Distributed database systems. In: Stonebraker M, Hellerstein JM, editors. Readings in database systems. 3rd ed. San Francisco: Morgan Kaufmann; 1998.Google Scholar
  11. 11.
    Williams R, Daniels D, Hass L, Lapis G, Lindsay B, Ng P, Obermarck R, Selinger P, Walker A, Wilms P, Yost R. R*: an overview of the architecture. IBM Research Lab, San Jose, Technical Report RJ3325; 1981.Google Scholar
  12. 12.
    Yu CT, Chang CC. Distributed query processing. ACM Comput Surv. 1984;16(4):399–433.CrossRefMATHGoogle Scholar
  13. 13.
    Yu CT, Meng W. Principles of database query processing for advanced applications. San Francisco: Morgan Kaufmann; 1998.Google Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Technische Universität IlmenauIlmenauGermany