1. 1 The Relational Data Model David J. Stucki

2. Relational Model Concepts 2 Fundamental concept: the relation  The Relational Model represents an entire database as a collection of relations  Idea of a relation: A table of values Each row is some collection of facts about an entity Each column is a single attribute about the entities in the table

3. Relational Model Concepts 3 Tuple – one row of a relation Attribute – one column of a relation Relation – the whole table Domain of an Attribute – all the values that attribute can have

4. Domain All the possible values an attribute can take  Atomic  Remember your mathematics?  Example domains: US Phone Numbers: the set of all 10-digit phone numbers Local Phone Numbers: the set of all 7-digit phone numbers Social Security Numbers: the set of all 9-digit numbers Names: the set of all possible names GPAs: the set of all possible values between 0.0 and 4.0  Data type: a format for a domain US Phone Numbers: (ddd)ddd-dddd GPAs: any real-valued number 4

5. Relation Schema Denoted by R(A 1, A 2,...,A n )  Consists of a relation name and a list of attributes  Description of what the relation should contain STUDENT relation:  STUDENT(Name, SSN, Address, GPA)  Can also include data type:  STUDENT(Name:String, SSN:Social_Security_Nums, Address: String, GPA: Real) Degree (or arity) of a relation  Number of attributes n of its relation schema 5

6. Relation A particular set of tuples for a given relation schema (also known as a relation state) Set of n-tuples r = {t 1, t 2,..., t m } The “state” of the relation is its current configuration (i.e. current contents)  Each tuple in the set is an ordered list of values Each element of the tuple corresponds to a particular attribute for the relation 6

7. Characteristics of Relations Ordering of tuples  Relation is a set  Sets have no order  Relation is not sensitive to ordering of tuples Uniqueness of tuples  No duplicate tuples in a relation! Unknown values  NULL value – used when value can’t be known or does not exist Interpretation  Relation is an assertion of facts  Each tuple can be thought of as a fact about the world Or as a predicate in first order logic 7

8. Characteristics of Relations Order of attributes and values is not that important  As long as correspondence between attributes and values maintained Alternative definition of a relation  Tuple considered as a set of (, ) pairs  Each pair gives the value of the mapping from an attribute A i to a value v i from dom(A i ) Use the first definition of relation  Attributes and the values within tuples are ordered  Simpler notation  But alternative has application in later formalisms

9. Characteristics of Relations Values in tuples  Each value in a tuple is atomic  Flat relational model Composite and multivalued attributes not allowed First normal form assumption  Multivalued attributes Must be represented by separate relations  Composite attributes Represented only by simple component attributes in basic relational model

10. Relational Model Constraints A constraint is a restriction on the values in a database state  Implicit constraints (model-based constraints) Inherent in the data model itself  E.g. no duplicate tuples in a relation  Explicit constraints (schema-based constraints) Can be explicitly enforced/expressed in the schema  Application-based constraints (business rules) Derived from miniworld represented by database Cannot be explicitly enforced by the schema Must be enforced by application programs themselves 10

11. Schema-based constraints Domain constraints  Data type constraint  Each attribute in a tuple may only take on a value from the domain of that attribute 11

12. Schema-based constraints Key constraints  Remember – each tuple in a relation must be unique No duplicate tuples! This means that no two tuples have the same combination of attributes for all of their attributes  Usually there is a subset of attributes that control uniqueness We call this subset a superkey Definition: Let SK be a subset of attributes of the relation R that form a superkey. Then for any two distinct tuples t1 and t2 in a relation state r of R: t1[SK] != t2[SK] 12

13. Schema-based constraints  Superkeys can have redundant attributes Ex: {First Name, Last Name, SSN} could be a superkey Don’t really need First Name and Last Name to be unique – SSN is guaranteed to be unique  keys A key is a minimal superkey  Remove one attribute from a key and it is no longer a superkey! A key is always a superkey, but not all superkeys are keys There can be more than one key in a relation  Ex: {SSN} {Student ID}  Common to identify one of these keys as as a primary key  Primary key uniquely identifies tuples in a relation to other relations and outside applications 13

14. Schema-based constraints Constraints can apply not just to single relations  We need to be able to talk about constraints that cross relations  More Terminology! Relational Database Schema  Set of relation schemas S = {R 1, R 2,..., R m }  Set of integrity constraints IC Relational Database State  Set of relation states for a relational database such that all integrity constraints are satisfied Invalid state – state that violates an integrity constraint 14

15. Schema-based constraints Entity integrity constraint  No primary key can have a NULL value  Remember – primary key uniquely identifies a tuple! Referential integrity constraint  Specified between two relations  A tuple in one relation that refers to a tuple in a second relation MUST refer to an existing tuple You can’t put in “placeholder” references – every reference must be resolvable when you make the reference  Uses the concept of a foreign key 15

16. Schema-based constraints Where do referential integrity constraints come from?  Connections in the data 16

17. Other constraints Semantic integrity constraints  Constraints that come from outside the basic relationships between tuples “Business rules”  “no employee can have a salary larger than their supervisor”  “no employee can log more than 60 hours of time in a week”  Usually modeled at the application level, but sometimes can be modeled in the database “Triggers” – “when event X occurs perform action Y” “Assertions” – “make sure that no matter what action X does, condition Y is always true” 17

18. Operations The relational model has two types of operations:  Retrievals Getting information out of the database  Updates Adding/changing information in the database Different kinds of updates:  INSERT  Add new tuple to a relation  DELETE  Remove a tuple from a relation  UPDATE  Change an attribute value in a tuple in a relation 18

19. Updates & Constraints The DBMS must make sure that updates are not allowed to violate integrity constraints  Check to make sure that attributes in an INSERT do not violate constraints  DELETE can cause referential constraint violations Removing a tuple being referred to by another tuple  UPDATE can cause referential constraint violations Changing a primary key can cause all sorts of referential problems for any tuple referring to the updated tuple Changing a foreign key can only happen if the tuple the foreign key refers to already exists 19

20. ER-Relational Mapping 20

21. ER-Model to Relational Model Once we have our ER-Model, we use it to come up with our Relational model  Must map elements of ER-model to elements of relational model Entities, Relationships, Attributes, etc. must become Relations, Attributes, etc. 21

22. Strong Entity Types Each strong entity type in an ER model becomes a relation  Entity type E -> Relation R  Simple attributes of E become attributes of R  Include only the component attributes of a composite attribute  Choose one key of E to become the primary key of R 22 EMPLOYEE SsnAddressName FnameLnameM SsnFnameMLnameAddress EMPLOYEE

23. Weak Entity Types Each weak entity type becomes a relation  Weak entity W owned by entity E Entity E -> Relation R1 Entity W -> Relation R2  All simple attributes of W become attributes in R2 Include as a foreign key the primary key attribute of R1 Primary key of R2 will be that foreign key, plus the partial key of W 23 EMPLOYEE Dependents_of DEPENDENT Sex Relationship Bdate Name N 1 SsnFnameMLnameAddress EMPLOYEE EssnNameSexBdateRelationship DEPENDENT

24. Binary 1:1 Relationships Three approaches:  Foreign Key Approach  Merged relation Approach  Cross-reference Approach  Should use “Foreign key approach” unless there is good reason not to 24

25. Binary 1:1 Relationships Foreign key approach  Two entities in the relationship – E1 and E2 1. Generate two relations R1 and R2 associated with E1 and E2 2. Include in R1 a foreign key pointing at the primary key of R2  R1 should be an entity with Total Participation if possible 25 SsnFnameMLnameAddress EMPLOYEE DnameDnumberMgrSsn DEPARTMENT

26. Binary 1:1 relationships Merged relation approach  If both entities have TOTAL participation in the relationship, you can merge them into a single entity Each table would have an exact one-to-one correspondence between rows, so they’re essentially the same entity Cross-reference approach  Set up a third relation as a “lookup table” for the relationship Required for many-to-many relationships 26

27. Binary 1:N Relationships Use the foreign key approach  Identify which relation represents the entity on “many” side of the relationship  Give that relation a foreign key pointing at the primary key on the “one” side of the relationship Or use cross-reference 27 SsnFnameMLnameAddressDno EMPLOYEE DnameDnumberMgrSsn DEPARTMENT

28. Binary M:N Relationships Cross-reference approach  For Entities E1 and E2 connected by Relationship R  Create a new relation for R Include as attributes foreign keys pointing at the primary keys of E1 and E2 – combination will be the primary key Include any attributes tied to R Think of this as a “lookup table ” 28 SsnFnameMLnameAddressDno EMPLOYEE NamePnumberLocation PROJECT SsnPnumberHours WORKS_ON

29. Multivalued Attributes Each multi-valued attribute A in the entity E1 gets its own relation  Relation includes the attribute A and a foreign key pointing at the primary key of the relation associated with E1  Primary key of the new relation is a combination of A and the foreign key 29 DnameDnumberMgrSsn DEPARTMENT DnoDlocation DEPT_LOCATIONS

30. N-ary Relationships N-ary relationships modeled using cross- reference approach  Each n-ary relationship is made into a new relation Attributes of this relation include foreign keys pointing at the primary keys of all the participating entity relations Include all simple attributes as well Primary key is usually a combination of all foreign keys  Be careful – cardinality constraints may mean that we need to leave some of these out 30

31. Summary of ER-to-Relational mapping 31