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 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. Step 8 Example 1..* 1.* Orders 1..* Map this ERM now! Customer
custID {PK}
name
1..*
Supplier
suppID {PK}
name
address
Product
prodID {PK}
type
name
Orders
1.*
1..*
date quantity
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. Step 4 Example
Manages
1..1
0..1
“Each branch has one manager, each manager may manage a branch (but those at head office don’t)”
Manager
managerID {PK}
name salary
Branch
bName {PK}
address
phone
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 or 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
Rob et al: Section 11.2
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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