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In [[computer science]] the concept of a '''Lossless-Join Decomposition''' is central in removing redundancy safely from [[database]]s while preserving the original data. | |||
==Lossless-join Decomposition== | |||
Can also be called Nonadditive. | |||
If you decompose a relation <math>R</math> into relations <math>R_1</math> and <math>R_2</math> you will guarantee a Lossless-Join if <math>R_1</math>⋈<math>R_2</math> = <math>R</math>. | |||
If R is split into R1 and R2, for the decomposition to be lossless then at least one of the two should hold true. | |||
Projecting on R1 and R2, and joining back, results in the relation you started with.<ref>http://stackoverflow.com/questions/5771810/lossless-join-property</ref> | |||
Let <math>R</math> be a relation schema. | |||
Let <math>F</math> be a set of [[Functional dependency|functional dependencies]] on <math>R</math>. | |||
Let <math>R_1</math> and <math>R_2</math> form a decomposition of <math>R</math>. | |||
The decomposition is a lossless-join decomposition of R if at least one of the following functional dependencies are in <math>F</math><sup>+</sup> (where <math>F</math><sup>+</sup> stands for the closure for every attribute in <math>F</math>):<ref>{{cite news | first= | last= | coauthors= | title=Lossless Join Decomposition | date= | publisher=Jan Chomicki | url =http://www.cse.buffalo.edu/~chomicki/560/handout-design.pdf | work =[[University at Buffalo]] | pages = | accessdate = 2012-02-08 | language = }}</ref> | |||
* <math>R_1</math> ∩ <math>R_2</math> → <math>R_1 - R_2</math> | |||
* <math>R_1</math> ∩ <math>R_2</math> → <math>R_2 - R_1</math> | |||
==Example== | |||
* Let <math>R = (A, B, C, D)</math> be the relation schema, with <math>A</math>, <math>B</math>, <math>C</math> and <math>D</math> attributes. | |||
* Let <math>F = \{ A \rightarrow BC \}</math> be the set of functional dependencies. | |||
* Decomposition into <math>R_1 = (A, B, C)</math> and <math>R_2 = (A, D)</math> is lossless under <math>F</math> because <math>R_1 \cap R_2 = (A)</math> and <math>A \rightarrow BC</math> so <math>R_1 \cap R_2 \rightarrow R_1 - R_2</math>. | |||
==References== | |||
{{Reflist}} | |||
[[Category:Databases]] | |||
[[Category:Data modeling]] | |||
[[Category:Database constraints]] | |||
[[Category:Database normalization| ]] | |||
[[Category:Relational algebra]] |
Latest revision as of 16:44, 9 January 2013
In computer science the concept of a Lossless-Join Decomposition is central in removing redundancy safely from databases while preserving the original data.
Lossless-join Decomposition
Can also be called Nonadditive. If you decompose a relation into relations and you will guarantee a Lossless-Join if ⋈ = .
If R is split into R1 and R2, for the decomposition to be lossless then at least one of the two should hold true.
Projecting on R1 and R2, and joining back, results in the relation you started with.[1] Let be a relation schema.
Let be a set of functional dependencies on .
Let and form a decomposition of .
The decomposition is a lossless-join decomposition of R if at least one of the following functional dependencies are in + (where + stands for the closure for every attribute in ):[2]
Example
- Let be the relation schema, with , , and attributes.
- Let be the set of functional dependencies.
- Decomposition into and is lossless under because and so .
References
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