Vertical partitioning algorithms for database design

Navathe, Shamkant B.; Ceri, Stefano; Wiederhold, Gio; Dou, Jinglie

doi:10.1145/1994.2209

Cited by 332 publications

(184 citation statements)

References 17 publications

(20 reference statements)

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“…Moreover, TOPYDE can be easily extended with vertical fragmentation and materialization. We agree with Navathe et al [7] that vertical partitioning precedes the selection of a physical schema. In [7], vertical fragmentation algorithms are presented that partition a relation into a set of fragments.…”

supporting

confidence: 93%

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TOPYDE: A tool for physical database design

Choenni

Wagterveld

Blanken

et al. 1995

Lecture Notes in Computer Science

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Abstract. We describe a tool for physical database design based on a combination of theoretical and pragmatic approaches. The tool takes as input a relational schema, the workload defined on the schema, and some additional database characteristics and produces as output a physical schema. For the time being, the tool is tuned towards Ingres. IntroductionThe design of databases takes place on several levels. One of these levels is the physical level. Typical subproblems on this level are, among others, selection of storage structures, secondary index selection, vertical fragmentation, materialization, etc. Solving these subproblems requires a sophisticated understanding of physical design options and query optimization strategies of the optimizer, and involve estimating query costs, which is a tedious and error-prone process when done manually. Moreover, several subproblems are NP-complete, such as the selection of an optimal set of secondary indices. Research in this area has been shifted to the problem of determining a good physical design instead of an optimal design [2,5]. A physical design is considered as good if a competent human database designer would produce the same or a worse design with the same available information. We present a tool, called TOPYDE, that takes as input, among others, a relational schema, the workload defined on the schema, and other database characteristics, such as page size, cardinality of a relation, etc., and produces for each relation a storage structure (including an ordering attribute or clustering index) and a set of secondary indices. This is called a physical schema. An overall physical schema is obtained by the union of the physical schema of each relation involved in the relational schema. For the time being, ordering attributes and indices concern single attributes, and a secondary index is stored as a Btree.Although TOPYDE does not cover the overall problem of physical design, it covers the most crucial parts. Moreover, TOPYDE can be easily extended with vertical fragmentation and materialization. We agree with Navathe et al. [7] that vertical partitioning precedes the selection of a physical schema. In [7], vertical fragmentation algorithms are presented that partition a relation into a set of fragments. Such algorithms can serve as a preprocessor for TOPYDE. In practice, materialization is often done as last; this means after the selection of a physical schema. So, TOPYDE can be extended by a postprocessor that aims to improve the physical schema selected by it.

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supporting

confidence: 93%

“…We agree with Navathe et al [7] that vertical partitioning precedes the selection of a physical schema. In [7], vertical fragmentation algorithms are presented that partition a relation into a set of fragments. Such algorithms can serve as a preprocessor for TOPYDE.…”

supporting

confidence: 93%

TOPYDE: A tool for physical database design

Choenni

Wagterveld

Blanken

et al. 1995

Lecture Notes in Computer Science

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“…Hoffer and Severance [25] consider the vertical partitioning problem by applying bond energy algorithm on similarity of attributes, which are based on access patterns of transactions. Their work was extended by Navathe, Ceri, Widerhold, and Dou [30] by presenting vertical partitioning algorithms for three contexts: a data base stored on devices of a single type; in different memory levels; and a distributed database. They used affinity between attributes for partitioning, which is based on number of disk accesses.…”

Section: Related Workmentioning

confidence: 99%

“…An important characteristic that distinguishes multi-relation schema from single relation case is referential integrity constraints enforcement due to update transactions. Our approach makes use of a 2-attribute affinity, as used in previous studies of Navathe et al [30] and Cornell and Yu [19]. However, we differ from their approach in that our attribute affinity 45 metric is based on differential access times of transactions rather than number of disk accesses.…”

Section: Related Workmentioning

confidence: 99%

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Fuzzy Based Approach for Load Balanced Distributing Database on Sensor Network

Zeynali

Jamali

2009

Communications in Computer and Information Science

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Abstract.A wireless sensor network consists of tiny sensing devices, with limited energy and processing ability. Some time we have to distribute a database on sensor network, because of limited energy in sensors, load balanced distributing database can increase the lifetime of this networks. In this paper we propose Fuzzy based approach for Load balanced distributing database on sensor Network that prolonging the network lifetime. We use vertical partitioning algorithms for distributing database on sensors. First we clustering the network and then distribute partitions on clusters. A simulator was built and Results of various simulation runs are consistent with the hypothesis.

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Note: On the set-union knapsack problem

Nehme-Haily

1994

Naval Research Logistics

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We consider a generalization of the 0‐1 knapsack problem called the set‐union knapsack problem (SKP). In the SKP, each item is a set of elements, each item has a nonnegative value, and each element has a nonnegative weight. The total weight of a collection of items is given by the total weight of the elements in the union of the items' sets. This problem has applications to data‐base partitioning and to machine loading in flexible manufacturing systems. We show that the SKP remains NP‐hard, even in very restricted cases. We present an exact, dynamic programming algorithm for the SKP and show sufficient conditions for it to run in polynomial time. © 1994 John Wiley & Sons, Inc.

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Vertical partitioning algorithms for database design

Cited by 332 publications

References 17 publications

TOPYDE: A tool for physical database design

TOPYDE: A tool for physical database design

Fuzzy Based Approach for Load Balanced Distributing Database on Sensor Network

Note: On the set-union knapsack problem

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