Synonyms
GiST; GIST
Definition
The Generalized Search Tree (GiST) is an extensible, disk-based index structure for large data sets, enabling the easy design and implementation of domain-specific index structures. The GiST provides a general-purpose implementation of many of the difficult systems issues inherent in indexing (data storage and access, search, concurrency and recovery), with a compact extensibility interface sufficient for the specification of the domain-specific, algorithmic aspects of indexing (clustering of data into pages, labeling of subtrees, and prioritization of the search frontier).
Historical Background
A key research challenge in database systems in the 1980s and 1990s was to support an extensible set of abstract data types, beyond the alphanumeric types typically used in business data processing. One critical component of database extensibility is the ability to easily add new access methodscustomized to specific data types and query operators. Ideally,...
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Recommended Reading
Aoki PM. Generalizing “search” in generalized search trees. In: Proceedings of the 14th International Conference on Data Engineering; 1998.
Aoki PM. How to avoid building dataBlades that know the value of everything and the cost of nothing. In: Proceedings of the 11th International Conference on Scientific and Statistical Database Management; 1999. p. 122–33.
Aref WG, Ilyas IF. SP-GiST: an extensible database index for supporting space partitioning trees. J Intell Inf Syst. 2001;17(2/3):215–40.
Hellerstein JM, Koutsoupias E, Miranker D, Papadimitriou C, Samoladas V. On a model of indexability and its bounds for range queries. J ACM. 2002;49(1):35–55.
Hellerstein JM, Naughton JF, Pfeffer A. Generalized search trees for database systems. In: Proceedings of the 21st International Conference on Very Large Data Bases; 1995. p. 562–73.
Hellerstein JM, Pfeffer A. The RD-tree: an index structure for sets. Madison: University of Wisconsin Technical Report #1252; 1994.
Kornacker M. High-performance generalized search trees. In: Proceedings of the 25th International Conference on Very Large Data Bases; 1999.
Kornacker M, Mohan C, Hellerstein JM. Concurrency and recovery in generalized search trees. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 1997. p. 62–72.
Kornacker M, Shah MA, Hellerstein JM. Amdb: a design tool for access methods. Data Eng Bull. 2003;26(2):3–11.
Thomas MC, Hellerstein JM. Boolean bounding predicates for spatial access methods. In: Proceedings of the International Conference on Database and Expert Systems Applications; 2002. p. 925–34.
Stonebraker M. Inclusion of new types in relational data base systems. In: Proceedings of the 2nd International Conference on Data Engineering; 1986.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Section Editor information
Rights and permissions
Copyright information
© 2018 Springer Science+Business Media, LLC, part of Springer Nature
About this entry
Cite this entry
Hellerstein, J.M. (2018). Generalized Search Tree. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_743
Download citation
DOI: https://doi.org/10.1007/978-1-4614-8265-9_743
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-8266-6
Online ISBN: 978-1-4614-8265-9
eBook Packages: Computer ScienceReference Module Computer Science and Engineering