System optimization: Mathematical programming techniques for optimal computer use
ACM '65 Proceedings of the 1965 20th national conference
A clustering approach to the generation of subfiles for the design of a computer data base.
A clustering approach to the generation of subfiles for the design of a computer data base.
alpha-Partitioning Algorithm: Vertical Partitioning Based on the Fuzzy Graph
DEXA '01 Proceedings of the 12th International Conference on Database and Expert Systems Applications
A Heuristic Approach to Fragmentation Incorporating Query Information
Proceedings of the 2007 conference on Databases and Information Systems IV: Selected Papers from the Seventh International Baltic Conference DB&IS'2006
Data structures and data accessing in data base systems past, present, future
IBM Systems Journal
Cost-based fragmentation for distributed complex value databases
ER'07 Proceedings of the 26th international conference on Conceptual modeling
Vertical partitioning for flash and HDD database systems
Journal of Systems and Software
HYRISE: a main memory hybrid storage engine
Proceedings of the VLDB Endowment
SQL server column store indexes
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
A vertical partitioning algorithm for distributed multimedia databases
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part II
DYMOND: an active system for dynamic vertical partitioning of multimedia databases
Proceedings of the 16th International Database Engineering & Applications Sysmposium
Enhancements to SQL server column stores
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
A comparison of knives for bread slicing
Proceedings of the VLDB Endowment
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The physical structure and relative placement of information elements within a data base is critical for the efficient design of a computerized information system which is shared by a community of users. Traditionally the selection among alternative structural designs has been handled largely via heuristics. Recent research has shown that a number of significant design problems can be stated mathematically as nonlinear, integer, zero-one programming problems. In concept, therefore, mathematical programming algorithms can be used to determine "optimal" data base designs. In practice, one finds that realistic problems of even modest size are computationally infeasible. This paper presents a means for overcoming this difficulty in the design of data base records. A metric with which to measure the similarity of usage among data items is developed and used by a clustering algorithm to reduce the space of alternative designs to a point where solution is economically feasible.