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6NF : ウィキペディア英語版
Sixth normal form
Sixth normal form (6NF) is a term in relational database theory, used in two different ways.
==6NF (C. Date's definition)==
A book by Christopher J. Date and others on temporal databases,〔Date et al., 2003〕 defined sixth normal form as a normal form for databases based on an extension of the relational algebra.
In this work, the relational operators, such as ''join'', are generalized to support a natural treatment of interval data, such as sequences of dates or moments in time.〔op. cit., chapter 9: ''Generalizing the relational operators''〕 Sixth normal form is then based on this generalized join, as follows:
A relvar R () is in sixth normal form (abbreviated 6NF) if and only if it satisfies no nontrivial join dependencies at all — where, as before, a join dependency is trivial if and only if at least one of the projections (possibly U_projections) involved is taken over the set of all attributes of the relvar () concerned.(et al. )〔op. cit., section 10.4, p. 176〕

-Also a new definition - not as clear as the first
* - has been given by the same authors (2014):
Relvar R is in sixth normal form (6NF) if and only if every JD of R is trivial — where a JD is trivial if and only if one of its components is equal to the pertinent heading in its entirety. (et al. ) 〔op. cit., chapter 12, p. 213〕

(Where JD state for join dependency.
*We can wonder if a unary relvar has a trivial join dependency; also trivial refer to another ambiguous term, knowing: "pertinent".)
Any relation in 6NF is also in 5NF.
Sixth normal form is intended to decompose relation variables to irreducible components. Though this may be relatively unimportant for non-temporal relation variables, it can be important when dealing with temporal variables or other interval data. For instance, if a relation comprises a supplier's name, status, and city, we may also want to add temporal data, such as the time during which these values are, or were, valid (e.g., for historical data) but the three values may vary independently of each other and at different rates. We may, for instance, wish to trace the history of changes to Status.
For further discussion on Temporal Aggregation in SQL, see also Zimanyi.〔Zimanyi 2005〕 For a different approach, see TSQL2.〔Snodgrass, Richard T. (TSQL2 Temporal Query Language ). Describes history, gives references to standard and original book.〕

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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