Mapping ERM to relational database

1. Mapping ERM to relational database Mapping the ER model to the relational model Logical Database Design Reading: e.g. Connolly/Begg DB systems: (4th ed) Ch 16 – step 2.2 and/or (3rd ed) Ch 15.1 Rob et al: Section 11.2

2. What does this ERM model? • Work with your neighbour and identify: • Entities (strong, weak) • Attributes (simple, composite, derived, multi-valued) • Relationships (cardinality, participation, attributes)

3. Mapping the conceptual model • Step-by-step “cookbook recipe” • Details how to create a logical (relational) model from a conceptual (ERM) model • Main ideas: • Entity with attributes  Relation with fields • Relationship  Foreign key • Let’s start with the steps we need for the books example

4. Steps 1&2: Entities • For each entity type create a relation • include all simple attributes • include composite attributes: • usually use one field per component, • or single field • Leave out multi-valued attributes • Strong entity: Choose a primary key • Weak entity: will get its primary key later • Now apply this to the books example

5. Mapping binary relationships • Identify one entity as “parent” • other entity as “child” • as general rule, PK of parent is added to child as FK • Any attributes of the relationship • are added to child relation

6. Step 3: (1:*) Relationships • Relation at “1” end is parent • Relation at “many” end is child • include parent's PK in child as foreign key. • Any attributes of the relationship are added to child • Apply this to the (1:*) relationships in the books example now • Note: for recursive (1:*) relationships, use same rule. Add primary key of the relation a second time as foreign key

7. Step 7: (*:*) relationships • For each binary many-to-many relationship type create a new relation. • Add PKs of both “parents” to the new relation (as FKs) and also any attributes of the relationship. • PK of the new relation is usually composite: simply combine both FKs. If this is not unique, include additional fields as needed • Apply this to the (1:*) relationships in the books example now • Note: Apply same method for unary *:*: create a new table, with two foreign keys both linking to the original PKs

8. Step 9: Multi-valued attributes For each multi-valued attribute: • create a new relation that contains • the attribute itself, plus • the primary key of the “parent” entity as foreign key. • The primary key of the new relation is usually made up of all its attributes. • Sometimes, not all attributes may be needed • Apply this to the books ERM now

9. Steps Summary (from Connolly/Begg) 1. Strong entities 2. Weak entities 3. Binary 1:* relationships 4. Binary 1:1 relationships 5. Recursive 1:1 relationships 6. Super- and subclasses  later!! 7. Binary *:* relationships 8. Complex relationships 9. Multi-valued attributes Check: all relations have PK; there are at least (n-1) FKs if you have n relations, and all relations are in 3NF

10. Steps Summary (from Rob et al) 1. Strong entities 2. Weak entities 3. Multi-valued attributes 4. Binary relationships 1:* 1:1 (also discusses 1:1 recursive) *:* 5. Ternary relationships 6. Super- and subclasses  later!! How does that compare with Connolly/Begg? Which do you prefer?

11. Step 8: complex relationships For each ternary (and higher order) relationship: • Create a new relation • made up of the primary keys from the n participating relations, as foreign keys • plus any attributes of the relationship. • PK of the new relation • usually the combination of all FKs • But may be able to use just a subset of the attributes • Or may need to add in other attributes to guarantee uniqueness.

12. Customer custID {PK} name Supplier suppID {PK} name address Product prodID {PK} type name datequantity Step 8 Example 1..* Orders 1.* 1..* • Map this ERM now!

13. Step 4: Binary (1:1) Three options, depending on participation • Option A (mandatory participation on both sides): • Merge both entities into a single entity • choose either of the original PKs as the new PK • include any attributes of the relationship • Option B (mandatory participation on one side): • relation with optional participation is parent • Relation with mandatory participation is child • add PK of parent to child as FK. • add any attribute of the relationship to child

14. Step 4: Binary (1:1) ctd. • Option C (optional participation on both sides) • Arbitrarily choose one entity as child, the other as parent • proceed as usual - add PK of parent to child as FK; also add any attributes of the relationship • also use this option if mandatory participation on both sides and want to keep separate relations • If one entity is close to mandatory participation, choose that one as child.

15. Manages 1..1 0..1 Manager managerID {PK} namesalary Branch bName {PK} address phone • “Each branch has one manager, each manager may manage a branch (but those at head office don’t)” Step 4 Example How would you map this?

16. Step 5: Unary (Recursive) 1:1 • Follow Step 4 in principle, but same entity on both sides of relationship • Mandatory participation both sides • keep single relation • add new attribute - “copy” of PK, to act as FK • Optional on both sides • create a new relation with just two copies of PK. They act as composite PK and separately as FKs to link back to entity • Optional one side • follow either of the two methods above.

17. Step 5 example 1..1 “Each staff member has one supervisor and may supervise one staff member” Supervises Staff ID {PK} name department 0..1 One relation: Staff(ID, supervisorID*, name, department) Or Two relations: Staff(ID, name, department) Supervision(staffID*, supervisorID*)

18. Directed Reading • Connolly/Begg “Database Systems” • (4th ed) Ch 16 – step 2.2 or (3rd ed) Ch 15.1 • Ignore “Step 6” (super- and sub-classes) for now or • Connolly/Begg “Database Solutions” • Chapter 10 – step 2.1 or • Rob et al: Section 11.2 ***************************************************************** Note that if you read any other database textbook or access any websites you may see other descriptions of the mapping “recipe”. They all do the same thing! We use the numbering of Connolly and Begg DB Systems. DB solutions uses the same method but no numbering. *****************************************************************

19. What about unary (recursive) relationships? • Textbooks usually discuss recursive 1:1 relationships explicitly • Often don't mention 1:* or *:* recursive relationships • Essentially, treat all recursive relationships like the equivalent binary ones, except the entities at both ends are one and the same.

20. Summary • Follow 9 Step procedure • should result in a “good” relational model, i.e. at least in 3rd Normal Form • Be careful!!! • Remember to identify Primary Keys • For relationships: • Identify one relation as “parent”, one as “child” • post parent’s PK to child as FK

21. Summary ctd. • In the relational model, • entities are represented as relations • simple attributes are represented as fields • multi-valued attributes represented as a relation • derived attributes are not usually stored • Composite attributes are usually split into several fields • relationships are represented indirectly through the use of foreign keys • 1:1 relationship  foreign key or single relation • 1:* relationship  foreign key in “child” • *:* relationship  relation and two foreign keys