The average length of keys and functional dependencies in (random) databases

Abstract

Practical database applications engender the impression that sets of constraints are rather small and that large sets are unusual and caused by bad design decisions. Theoretical investigations show, however, that minimal constraint sets are potentially very large. Their size can be estimated to be exponential in terms of the number of attributes. The gap between belief and theory causes non-acceptance of theoretical results. However, beliefs are related to average cases.The theory known so far considered worst case complexity. This paper aims at developing a theory of average case complexity. Several statistic models and asymptotics of corresponding probabilities are investigated for random databases. We show that exponential complexity of independent key sets and independent sets of functional dependencies is rather unusual. Depending on the size of relations almost all minimal keys have a length which mainly depends on the size. The number of minimal keys of other length is exponentially small compared with the number of minimal keys of the derived length. Further, if a key is valid in a relation then it is probably the minimal key. The same results hold for functional dependencies.KeywordsRelational DatabaseFunctional DependencyFunctional IndependencyPoisson Random VariableDatabase MiningThese 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.