Functional DependenciesReview: Database DesignThe Evils of RedundancyFunctional Dependencies (FDs)FD’s ContinuedExample: Constraints on Entity SetProblems Due to R WDetecting ReduncancyDecomposing a RelationRefining an ER DiagramReasoning About FDsRules of InferenceExampleAttribute ClosureAttribute Closure (example)Next Class…Functional DependenciesR&G Chapter 19Science is the knowledge of consequences, and dependence of one fact upon another. Thomas Hobbes (1588-1679)Review: Database Design•Requirements Analysis– user needs; what must database do?•Conceptual Design– high level descr (often done w/ER model)•Logical Design– translate ER into DBMS data model•Schema Refinement – consistency,normalization•Physical Design - indexes, disk layout•Security Design - who accesses whatThe Evils of Redundancy•Redundancy: root of several problems with relational schemas:–redundant storage, insert/delete/update anomalies•Functional dependencies: –integrity constraints that can identify redundancy and suggest refinements.•Main refinement technique: decomposition –replacing ABCD with, say, AB and BCD, or ACD and ABD.•Decomposition should be used judiciously:–Is there reason to decompose a relation?–What problems (if any) does the decomposition cause?A B C D A B B C D A C D A B DFunctional Dependencies (FDs)•A functional dependency X Y holds over relation schema R if, for every allowable instance r of R: t1 r, t2 r, X (t1) = X (t2) implies Y (t1) = Y (t2)(where t1 and t2 are tuples;X and Y are sets of attributes)•Explanation:– X Y means: If for 2 tuples X is the same, then Y must also be the same.•Read “” as “determines”CAUTION: The opposite is not true.FD’s Continued•An FD is a statement about all allowable relations.–Identified based on semantics, NOT instances–Given an instance of R, we can disprove a FD, but we cannot verify the validity of a FD.•Question: Are FDs related to keys?•if “K all attributes of R” then K is a superkey for R(does not require K to be minimal.)•FDs are a generalization of keys.Example: Constraints on Entity Set•Consider relation obtained from Hourly_Emps: Hourly_Emps (ssn, name, lot, rating, wage_per_hr, hrs_per_wk)•We sometimes denote a relation schema by listing the attributes: e.g., SNLRWH•This is really the set of attributes {S,N,L,R,W,H}.What are some FDs on Hourly_Emps?ssn is the key: S SNLRWH rating determines wage_per_hr: R Wlot determines lot: L L (“trivial” dependency)Problems Due to R W•Update anomaly: Should we be allowed to modify W in only the 1st tuple of SNLRWH?•Insertion anomaly: What if we want to insert an employee and don’t know the hourly wage for his or her rating? (or we get it wrong?)•Deletion anomaly: If we delete all employees with rating 5, we lose the information about the wage for rating 5! S N L R W H123-22-3666 Attishoo 48 8 10 40231-31-5368 Smiley 22 8 10 30131-24-3650 Smethurst 35 5 7 30434-26-3751 Guldu 35 5 7 32612-67-4134 Madayan 35 8 10 40Hourly_EmpsR=6, W=?Detecting ReduncancyS N L R W H123-22-3666 Attishoo 48 8 10 40231-31-5368 Smiley 22 8 10 30131-24-3650 Smethurst 35 5 7 30434-26-3751 Guldu 35 5 7 32612-67-4134 Madayan 35 8 10 40Hourly_EmpsQ: Why was R W problematic, but S W not?Decomposing a Relation•Redundancy can be removed by “chopping” the relation into pieces (vertically!)•FD’s are used to drive this process.R W is causing the problems, so decompose SNLRWH into what relations?S N L R H123-22-3666 Attishoo 48 8 40231-31-5368 Smiley 22 8 30131-24-3650 Smethurst 35 5 30434-26-3751 Guldu 35 5 32612-67-4134 Madayan 35 8 40R W8 105 7Hourly_Emps2WagesRefining an ER Diagram•1st diagram becomes: Workers(S,N,L,D,Si) Departments(D,M,B)–Lots associated with workers.•Suppose all workers in a dept are assigned the same lot: D L•Redundancy; fixed by: Workers2(S,N,D,Si) Dept_Lots(D,L) Departments(D,M,B)•Can fine-tune this: Workers2(S,N,D,Si) Departments(D,M,B,L) lotdnamebudgetdidsincenameWorks_InDepartmentsEmployeesssnlotdnamebudgetdidsincenameWorks_InDepartmentsEmployeesssnBefore:After:Reasoning About FDs•Given some FDs, we can usually infer additional FDs:title studio, star implies title studio and title star title studio and title star implies title studio, startitle studio, studio star implies title starBut, title, star studio does NOT necessarily imply that title studio or that star studio•An FD f is implied by a set of FDs F if f holds whenever all FDs in F hold.•F+ = closure of F is the set of all FDs that are implied by F. (includes “trivial dependencies”)Rules of Inference•Armstrong’s Axioms (X, Y, Z are sets of attributes):–Reflexivity: If X Y, then X Y –Augmentation: If X Y, then XZ YZ for any Z–Transitivity: If X Y and Y Z, then X Z•These are sound and complete inference rules for FDs!–i.e., using AA you can compute all the FDs in F+ and only these FDs.•Some additional rules (that follow from AA):–Union: If X Y and X Z, then X YZ–Decomposition: If X YZ, then X Y and X ZExample•Contracts(cid,sid,jid,did,pid,qty,value), and:–C is the key: C CSJDPQV–Proj purchases each part using single contract: JP C–Dept purchases at most 1 part from a supplier: SD P•Problem: Prove that SDJ is a key for Contracts•JP C, C CSJDPQV imply JP CSJDPQV(by transitivity) (shows that JP is a key)•SD P implies SDJ JP (by augmentation)•SDJ JP, JP CSJDPQV imply SDJ CSJDPQV (by transitivity) thus SDJ is a key.Q: can you now infer that SD CSDPQV (i.e., drop J on both sides)?No! FD inference is not like arithmetic multiplication.Attribute Closure•Computing the closure of a set of FDs can be expensive. (Size of closure is exponential in # attrs!)•Typically, we just want to check if a given FD X Y is in the closure of a set of FDs F. An efficient check:–Compute attribute closure of X (denoted X+) wrt F. X+ = Set of all attributes A such that X A is in F+•X+ := X•Repeat until no change: if there is an FD U V in F such that U is in X+, then add V to X+–Check if Y is in X+–Approach can also be used to find the keys of a relation.•If all attributes
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