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Functional Dependencies

Functional Dependencies. Definition: If two tuples agree on the attributes . A , A , … A . 1. 2. n. then they must also agree on the attributes. B , B , … B . 1. 2. m. Formally:. A , A , … A . B , B , … B . 1. 2. m. 1. 2. n.

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Functional Dependencies

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  1. Functional Dependencies Definition: If two tuples agree on the attributes A , A , … A 1 2 n then they must also agree on the attributes B , B , … B 1 2 m Formally: A , A , … A B , B , … B 1 2 m 1 2 n Motivating example for the study of functional dependencies: Name Social Security Number Phone Number

  2. Examples Product: name price, manufacturer Person: ssn name, age Company: name stock price, president Key of a relation is a set of attributes that: - functionally determines all the attributes of the relation - none of its subsets determines all the attributes. Superkey: a set of attributes that contains a key.

  3. Finding the Attributes of a Relation Given a relation constructed from an E/R diagram, what is its key? Rules: 1. If the relation comes from an entity set, the key of the relation is the set of attributes which is the key of the entity set. Person name ssn address

  4. Rules for Binary Relationships name buys Person Product price name ssn Several cases are possible for a binary relationship E1 - E2: 1. Many-many: the key includes the key of E1 together with the key of E2. What happens for: 2. Many-one: 3. One-one:

  5. Rules for Multiway Relationships None, really. Except: if there is an arrow from the relationship to E, then we don’t need the key of E as part of the relation key. Product Purchase Store Payment Method Person

  6. Some Properties of FD’s A , A , … A B , B , … B Is equivalent to 1 2 m 1 2 n B A , A , … A 1 1 2 n Splitting rule and Combing rule B A , A , … A 2 1 2 n … B A , A , … A m 1 2 n A , A , … A A Always holds. 1 2 n i

  7. Comparing Functional Dependencies Functional dependencies: a statement about the set of allowable databases. Entailment and equivalence: comparing sets of functional dependencies Entailment:a set of functional dependencies S1 entails a set S2 if: any database that satisfies S1 much also satisfy S2. Example: {A B, B C} entails A C Equivalence:two sets of FD’s are equivalent if each entails the other. {A B, B C } is equivalent to {A B, A C, B C}

  8. Closure of a set of Attributes Given a set of attributes A and a set of dependencies C, we want to find all the other attributes that are functionally determined by A. In other words, we want to find the maximal set of attributes B, such that for every B in B, C entails A B.

  9. Closure Algorithm Start with Closure=A. Until closure doesn’t change do: if is in C, and B is not in Closure then add B to closure. B A , A , … A 1 2 n are all in the closure, and A , A , … A 1 2 n

  10. Example A B C A D E B D A F B Closure of {A,B}: Closure of {A, F}:

  11. Problems in Designing Schema Name SSN Phone Number Fred 123-321-99 (201) 555-1234 Fred 123-321-99 (206) 572-4312 Joe 909-438-44 (908) 464-0028 Joe 909-438-44 (212) 555-4000 Problems: - redundancy - update anomalies - deletion anomalies

  12. Relation Decomposition Break the relation into two relations: Name SSN Fred 123-321-99 Joe 909-438-44 Name Phone Number Fred (201) 555-1234 Fred (206) 572-4312 Joe (908) 464-0028 Joe (212) 555-4000

  13. Decompositions in General Let R be a relation with attributes A , A , … A 1 2 n Create two relations R1 and R2 with attributes B , B , … B C , C , … C 1 2 m 1 2 l Such that:  = B , B , … B C , C , … C A , A , … A 1 2 m 1 2 l 1 2 n And -- R1 is the projection of R on -- R2 is the projection of R on B , B , … B 1 2 m C , C , … C 1 2 l

  14. Boyce-Codd Normal Form A simple condition for removing anomalies from relations: A relation R is in BCNF if and only if: Whenever there is a nontrivial dependency for R , it is the case that { } a super-key for R. A , A , … A B 1 2 n A , A , … A 1 2 n In English (though a bit vague): Whenever a set of attributes of R is determining another attribute, should determine all the attributes of R.

  15. Example Name SSN Phone Number Fred 123-321-99 (201) 555-1234 Fred 123-321-99 (206) 572-4312 Joe 909-438-44 (908) 464-0028 Joe 909-438-44 (212) 555-4000 What are the dependencies? What are the keys? Is it in BCNF?

  16. And Now? SSN Name 123-321-99 Fred 909-438-44 Joe SSN Phone Number 123-321-99 (201) 555-1234 123-321-99 (206) 572-4312 909-438-44 (908) 464-0028 909-438-44 (212) 555-4000

  17. What About This? Name Price Category Gizmo $19.99 gadgets Question: Find an example of a 2-attribute relation that is not in BCNF.

  18. More Decompositions Name Address Move-Date Name Address Name Move-Date What’s wrong?

  19. More Careful Strategy Find a dependency that violates the BCNF condition: A , A , … A B , B , … B 1 2 m 1 2 n Others A’s B’s R1 R2

  20. Example Decomposition Name Social-security-number Age Eye Color Phone Number Functional dependencies: Name + Social-security-number Age, Eye Color What if we also had an attribute Draft-worthy, and the FD: Age Draft-worthy

  21. Decomposition Based on BCNF is Necessarily Correct Attributes A, B, C. FD: A C Relations R1[A,B] R2[A,C] Tuples in R1: (a,b) Tuples in R2: (a,c), (a,d) Tuples in the join of R1 and R2: (a,b,c), (a,b,d) Can (a,b,d) be a bogus tuple?

  22. Multivalued Dependencies Name SSN Phone Number Course Fred 123-321-99 (206) 572-4312 CSE-444 Fred 123-321-99 (206) 572-4312 CSE-341 Fred 123-321-99 (206) 432-8954 CSE-444 Fred 123-321-99 (206) 432-8954 CSE-341 The multivalued dependencies are: Name, SSN Phone Number Name, SSN Course 4th Normal form: replace FD by MVD.

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