CS317 File and Database Systems

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1 CS317 File and Database Systems Lecture 3 Relational Model & Languages Part-1 September 7, 2018 Sam Siewert

2 More Embedded Systems Summer - Analog, Digital, Firmware, Software Reasons to Consider Catch up over summer Cultural mind expansion High Tech Jobs abroad Fairly affordable Full Stack HW -> SW Beautiful West Coast English and Irish Language Weather nice in summer! Sam Siewert 2

3 RDBMS Fundamental Theory Relational Model & Languages Part-1 (Relational Properties) Sam Siewert September 7,

4 Nota Bene! Relational Algebra is the basis of SQL - Summarized on p. 121 and p. 132 of our textbook Relational Algebra is Useful (non-sql) Method to Discuss Relational Query Tuple Calculus is Useful Set-Theoretic Method to Discuss Data Organization, But less practical - we won t emphasize The book has great coverage of RA in Chapter 5, SQL in Chapter 6 for DML (Queries) Sam Siewert 4

5 For Discussion Consider Competitive RDBMS Implementations (MS SQL, Oracle Enterprise, MySQL) Scan and Question E.F. Codd Paper Uploaded on Canvas [option for Assignment #1, problem #1] Scan and review Codd contributions to R-DBMS, SQL in notes Read Connolly-Begg Chapters 4 & 5, then 6 SQL practice Assignment #1 - Grading this week Assignment #2 POSTED on Canvas Relational Algebra (and some Relational Calculus) SQL Data Manipulation Sam Siewert 5

6 1. Relational Recall Data Models 3 View 1. branchno is a candidate key 2. staffno is a candidate key 3. postcode is a candidate key? 2. Network (1 to Many) 3. Hierarchical (Node has 1 parent) Sam Siewert 6

7 Dream Home Improved Example Basic Relations Added - All have PK and Some have FK Sam Siewert 7

8 Observations Best to Design Schema From Data Model Analysis Focus on Logical Defer Physical Implementation Validate Logical Model First Super Candidate Primary Alternate Foreign Select Keys for Relational Schema (SK, CK, PK, AK, FK) Normalized minimal redundancy (except foreign keys) Sam Siewert 8

9 Goals Relational Algebra or Views Language with Operations that work on One or More Relations (tables) to Define new Relation with no Change to Base Relations Relational Base (Schema) Define from Data Model Relational Calculus What Information Should be Retrieved via Predicate Calculus (True/False Assertions and Tests) rather than How Today, Focus is Understanding a Relational Base Sam Siewert 9

10 5 basic Relational Operations Specific Learning Objectives Why are they necessary and sufficient? 1) Selection [Restriction], 2) Projection [Projection], 3) Union [Join Specific Union], 4) Set Difference [Codd Omits], 5) Cartesian Product [Permutation] Join and Other Features are Convenient Constructed from basic operations (Page 121) Page 132 lists all RA operations Sam Siewert 10

11 Join Cheat Sheet - Visual SQL Joins Textbook Simple JOIN operations 1) Theta join (<,,>,,=, ) 2) Equi-join (=) 3) Natural join (common attribute) 4) Outer join - in book on p. 128 SQL JOIN - Manual Page (many options) JOIN INNER JOIN CROSS JOIN LEFT RIGHT JOIN Sam Siewert 11

12 JOIN Options in MySQL Testing JOIN variations on simple table relations (dreamhome) 1. SELECT r.rno,fname,lname,pno FROM Renter r, Viewing v WHERE r.rno=v.rno; 2. SELECT r.rno,fname,lname,pno FROM Renter r JOIN Viewing v ON r.rno=v.rno; 3. SELECT r.rno,fname,lname,pno FROM Renter r NATURAL JOIN Viewing v; 4. SELECT r.rno,fname,lname,pno FROM Renter r INNER JOIN Viewing v ON r.rno=v.rno; 5. SELECT r.rno,fname,lname,pno FROM Renter r CROSS JOIN Viewing v ON r.rno=v.rno; 6. SELECT r.rno,fname,lname,pno FROM Renter r LEFT JOIN Viewing v ON r.rno=v.rno; 7. SELECT r.rno,fname,lname,pno FROM Renter r RIGHT JOIN Viewing v ON r.rno=v.rno; 8. SELECT r.rno,fname,lname,pno FROM Renter r RIGHT OUTER JOIN Viewing v ON r.rno=v.rno; 9. SELECT r.rno,fname,lname,pno FROM Renter r LEFT OUTER JOIN Viewing v ON r.rno=v.rno; Sam Siewert 12

13 Connolly-Begg Chapter 4 Discussion & Examples Sam Siewert 13

14 Two Relations in Example Math vs Codd s Relations 1. Tuple Attribute Order (An, A2, A1) = (A1,A2, An) in DBMS 2. NULL allowed except for PK in Base Relations 3. Relation Cardinality (rows) and Degree (columns) Sam Siewert 14

15 Relational Model Terminology A relation is a table with columns and rows. Only applies to logical structure of the database, not the physical structure. Attribute is a named column of a relation. Domain is the set of allowable values for one or more attributes. Pearson Education

16 Relational Model Terminology Tuple is a row of a relation. Degree is the number of attributes in a relation. Cardinality is the number of tuples in a relation. Relational Database is a collection of normalized relations with distinct relation names. Pearson Education

17 Instances of Branch and Staff Relations Pearson Education

18 Examples of Attribute Domains Pearson Education

19 Alternative Terminology for Relational Model Pearson Education

20 Mathematical Definition of Relation Consider two sets, D 1 & D 2, where D 1 = {2, 4} and D 2 = {1, 3, 5}. Cartesian product, D 1 D 2, is set of all ordered pairs, where first element is member of D 1 and second element is member of D 2. D 1 D 2 = {(2, 1), (2, 3), (2, 5), (4, 1), (4, 3), (4, 5)} Alternative way is to find all combinations of elements with first from D 1 and second from D 2. Pearson Education

21 Mathematical Definition of Relation Any subset of Cartesian product is a relation; e.g. R = {(2, 1), (4, 1)} May specify which pairs are in relation using some condition for selection; e.g. second element is 1: R = {(x, y) x D 1, y D 2, and y = 1} first element is always twice the second: S = {(x, y) x D 1, y D 2, and x = 2y} Pearson Education

22 Mathematical Definition of Relation Consider three sets D 1, D 2, D 3 with Cartesian Product D 1 D 2 D 3 ; e.g. D 1 = {1, 3} D 2 = {2, 4} D 3 = {5, 6} D 1 D 2 D 3 = {(1,2,5), (1,2,6), (1,4,5), (1,4,6), (3,2,5), (3,2,6), (3,4,5), (3,4,6)} Any subset of these ordered triples is a relation. Pearson Education

23 Mathematical Definition of Relation Cartesian product of n sets (D 1, D 2,..., D n ) is: D 1 D 2... D n = {(d 1, d 2,..., d n ) d 1 D 1, d 2 D 2,..., d n D n } usually written as: n XD i i = 1 Any set of n-tuples from this Cartesian product is a relation on the n sets. Pearson Education

24 Database Relations Relation schema Named relation defined by a set of attribute and domain name pairs. Relational database schema Set of relation schemas, each with a distinct name. Pearson Education

25 Properties of Relations Relation name is distinct from all other relation names in relational schema. Each cell of relation contains exactly one atomic (single) value. Each attribute has a distinct name. Values of an attribute are all from the same domain. Pearson Education

26 Properties of Relations Each tuple is distinct; there are no duplicate tuples. Order of attributes has no significance. Order of tuples has no significance, theoretically. Pearson Education

27 Superkey Relational Keys An attribute, or set of attributes, that uniquely identifies a tuple within a relation. Candidate Key Superkey (K) such that no proper subset is a superkey within the relation. In each tuple of R, values of K uniquely identify that tuple (uniqueness). No proper subset of K has the uniqueness property (irreducibility). Pearson Education

28 Primary Key Relational Keys Candidate key selected to identify tuples uniquely within relation. Alternate Keys Candidate keys that are not selected to be primary key. Foreign Key Attribute, or set of attributes, within one relation that matches candidate key of some (possibly same) relation. Pearson Education

29 Two table are said to be union compatible if both the table have same number of attributes (column) and corresponding attributes have the same data type (int, char, float, date etc.). Union Compatible Sam Siewert 29

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