1. 1 Lecture 3: The relational model www.cl.cam.ac.uk/Teaching/current/Databases/ E.F. Codd

2. 2 Today’s lecture What’s the relational model? What’s SQL? How do we create databases in SQL? How do we convert E/R models to a relational model? How do we enforce real-life constraints in a relational database?

3. 3 Why study the relational model? It’s the dominant model in the marketplace –Vendors: Microsoft, Oracle, IBM, … SQL is the industrial realisation of the relational model SQL has been standardised (several times) Most of the commercial systems have substantially extended the standard!

4. 4 The relational model: Early history Proposed by E.F. Codd (IBM San José) ~1970 –Prior to this the dominant model was the network model (CODASYL) Mid 70’s: prototypes –Sequel at IBM San José –INGRES at UC Berkeley (M. Stonebraker) –PRTV at IBM UK 1976-: System R at IBM San José –Transactions (J. Gray et al.) –Query optimiser (P. Selinger et al.) –Extended  -testing (Boeing et al.) 1978/9-: CODD at Cambridge Computer Lab –Extended relational algebra query language (K. Moody)

5. 5 The relational model: Basics A relational database is a collection of relations A relation consists of two parts: –Relation instance: a table, with columns and rows –Relation schema: Specifies the name of the relation, plus the name and type of each column Can think of a relation instance as a set of rows or tuples

6. 6 Examples Relation schema Students(sid:string, name:string, login:string, age:integer) In general R(A 1 :  1, …, A n :  n ) Relation name Field name Domain

7. 7 Examples Relation instance sidname login age 1001MyleeneMK23 1002DannyDF22 1003NoelNS21 1004SuzanneSS20 1005JohnnyJS23 Field names Fields Tuples

8. 8 Relational terminology A domain is a set of values. All domains in a relation must be atomic (indivisible) Given a relation R=R(A 1 :  1, …, A n :  n ), R is said to have arity (degree) n Given a relation instance, its cardinality is the number of rows –For example, in Students, cardinality=5 (arity=4)

9. 9 Relations and sets A relation R=R(A 1 :  1, …, A n :  n ) can be defined more formally as R   1     n Thus a relation is a set of tuples, so there is no ordering of the tuples in the table Moreover, there are no duplicate rows in the table

10. 10 Keys Given a relation R=R(A 1 :  1, …, A n :  n ) a (candidate) key is a subset of fields K  {A 1, …, A n } that acts as a unique identifier for each tuple in the relation instance We annotate the schema accordingly, e.g. R=R(A 1 :  1, …, A n :  n )

11. 11 SQL SQL is the ubiquitous language for relational databases Standardised by ANSI/ISO in 1992: SQL/92 Part of SQL is a Data Definition Language (DDL) that supports the creation, deletion and modification of tables

12. 12 Creating tables The CREATE TABLE statement, e.g. CREATE TABLE Students (sid CHAR(20), name CHAR(20), login CHAR(10), age INTEGER); Note that the domain of each field is specified and enforced by the DBMS

13. 13 Removing and altering tables We can delete both the schema information and all the tuples, e.g. DROP TABLE Students; We can alter existing schemas, e.g. adding an extra field ALTER TABLE Students ADD COLUMN matric INTEGER;

14. 14 Adding and deleting tuples Can insert tuples into a table, e.g. INSERT INTO Students(sid,name,login,age) VALUES (“1006”, “Julia”, “jfg”, 21); Can remove tuples satisfying certain conditions, e.g. DELETE FROM Students WHERE name=“Myleene”;

15. 15 Querying relations We can list the current contents of a table with a query SELECT * FROM Students; We can add conditions to the query, e.g. SELECT * FROM Students S WHERE S.age=23;

16. 16 From E/R diagrams to relations The E/R model is convenient for representing the high-level database design Given an E/R diagram there is a reasonably straightforward method to generate a relation schema that corresponds to the E/R design

17. 17 Entity types to relations A (strong) entity type maps to a relation schema in the obvious way, e.g. is mapped to the relation schema Employees(NI:  1, Name:  2, dob:  3 ) NIdob Name Employees

18. 18 Relationship types to relations Given a relationship type, we generate a relation schema with fields consisting of: –The keys of each associated entity type –Any associated relationship attributes

19. 19 Example is mapped to the relation schema: Works_in(NI:  1, DID:  2, since:  3 ) Works_in NIdob Name Employees DIDbudget dname Departments since M N

20. 20 Recursive relationship sets Just pick appropriate field names! E.g. is mapped to Reports_to(sup_NI:  1, sub_NI:  1 ) Employees Reports-to NI name dob subordinatesupervisor

21. 21 Weak entity types Given a weak entity type, W, we generate a relation schema with fields consisting of the attributes of W, and the primary key attributes of the owner entity type For any relationship in which W appears we generate a relation schema which must take as the key for W all of its key attributes, including those from its owner set

22. 22 Example is mapped to the following schema: Dependents(pName:  1, NI:  2, age:  3 ) Policy(pName:  1, NI:  2, Cost:  4 ) Employees NI Name Policy Dependents Cost pNameage Alternatively: Policy(pName :  1, NI :  2, age : 3, Cost :  4 ) 1 N

23. 23 ISA Hierarchies Two choices: 1. 3 relations ( Employees, Temp_Emp and Contract_Emp ) 2. 2 relations ( Temp_Emp and Contract_Emp ) Employees ISA Temp_Emp Contract_Emp hours rate NI Name dob cid

24. 24 Other features Other features can also be mapped from the E/R model to relational model, including –Constraints –Aggregation The textbooks cover this material in detail

25. 25 Summary You should now understand: Relational model –Relation schema, relation instance, … How to create/update/delete tables in SQL/92 How to convert E/R model to a relational schema Next lecture: Relational Algebra