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Database Design

Database Design. Dr. M.E. Fayad, Professor Computer Engineering Department, Room #283I College of Engineering San José State University One Washington Square San José, CA 95192-0180 http://www.engr.sjsu.edu/~fayad. Lesson 05: Normalization. 2. Lesson Objectives.

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Database Design

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  1. Database Design Dr. M.E. Fayad, Professor Computer Engineering Department, Room #283I College of Engineering San José State University One Washington Square San José, CA 95192-0180 http://www.engr.sjsu.edu/~fayad SJSU -- CmpE

  2. Lesson 05: Normalization 2 SJSU – CmpE M.E. Fayad

  3. Lesson Objectives • Understand the goals of normalization • Explore the problems of DB bad design • Understand normalization • Learn how to deal with normalization 3 SJSU – CmpE M.E. Fayad

  4. Goals: Reduce data redundancy (undesirable replication of data values) Minimize anomaly problems (data model is structured in an improper manner) Maintain (correct) information Enforce semantic & integrity constraints, e.g., using dependency & domain constraints Relational Database Design 4 SJSU – CmpE M.E. Fayad

  5. Data replication: extra storage, update anomalies Anomaly: costly & data inconsistency Loss of information: poor decomposition Un-enforced dependency constraints: dependencies are lost Problems of Bad DB Design 5 SJSU – CmpE M.E. Fayad

  6. A db schemedesign tool A process of replacing associations among attributes in a relation scheme An approximation of the relation schemes that should be created Objectives: accomplish the goals of relational database design Two approaches: decomposition & synthesis Normalization 6 SJSU – CmpE M.E. Fayad

  7. A process to split or decompose a relation until the resultant relations no longer exhibit the undesirable problems, e.g., data redundancy, data inconsistency, anomaly, etc. Decomposing a relation scheme R means breaking R into a pair of schemes, possibly intersecting + this process is repeated until all the decomposed relation schemes are in the desired (normal) form. Decomposition 7 SJSU – CmpE M.E. Fayad

  8. Normal Forms (NFs) 1NF 2NF 3NF BCNF 4NF PJNF 8 SJSU – CmpE M.E. Fayad

  9. restrictions on the db scheme that preclude certain undesirable properties (data redundancy, update anomaly, loss of information, etc.) from the DB. A relation scheme R is in PJNF if R is in 4NF if R is in BCNF if R is in 3NF if R is in 2NF if R is in 1NF Normal Forms (NFs) 9 SJSU – CmpE M.E. Fayad

  10. Definition.A data value v is atomic if v is not a (i) set of values or (ii) composite value; otherwise, v is non-atomic. First Normal Form (1NF). A relation scheme R is in 1NF if for every attribute A in R, the values in the domain of A, i.e., dom(A), are atomic. Normal Forms (NFs) 10 SJSU – CmpE M.E. Fayad

  11. Boyce-Codd Normal Form (BCNF). A relation scheme R is in BCNF if for every non-trivial FD X Y applied to R, X is a superkey for R. Definition.Let A be an attribute in a relation scheme R, and let F be a set of FDs over R. A is a prime attribute in R if A is contained in some candidate key of R; otherwise, A is a non-prime attribute in R. Normal Forms (NFs) 11 SJSU – CmpE M.E. Fayad

  12. Third Normal Form (3NF).A relation scheme R is in 3NF if R is in 1NF, and For every non-trivial FD X Y applied to R, either X is a superkey of R, or every attribute in Y is an attribute of some candidate key of R, i.e., prime. Normal Forms (NFs) 12 SJSU – CmpE M.E. Fayad

  13. Lossy decomposition: a decomposition is lossy if the natural join of all the decomposed relations contain additional tuples and the original relation is lost. Lossless decomposition: a decomposition is lossless if the natural join of all the decomposed relations always yields the original relation without any extra tuples, i.e., a decomposition {R1, R2, …, Rn} of R is lossless if r(R), r(R) = R1(r)  R2(r)  …  Rn(r) Normal Forms (NFs) 13 SJSU – CmpE M.E. Fayad

  14. 2-Relational lossless-join decomposition: Let R1 and R2 be decomposed schemes of R. Let F be a set of FDs on R. The decomposition is lossless if R1 R2  R1  F+ or R1 R2  R2  F+ 2-Relational lossless-join decomposition 14 SJSU – CmpE M.E. Fayad

  15. a decomposition is dependency preserving if nodependency is lost in the process. Let F be the set of FDs on R. Let R1, … , Rn be a decomposition of R. Let Fi, 1  i  n, be the set of FDs in F+ which applies to Ri. Let F’ = i=1..nFi. If F’+ = F+, then the decomposition is dependencypreserving. Dependency preserving 15 SJSU – CmpE M.E. Fayad

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