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

BookT itle

ISBN {PK}

au tho r [1 ..*]

title

ma inT itle

subT itle

pub lishe r

yea r

BookC opy

copyID {PPK}

loanT ype

pu rchaseD a te

she lf

H as1 . .2 01

da teO u t

re tu rnD a te

\dueD a te

\fine

B o rro ws

0 . .* 0 . .*

R eade r

reade rNo {PK}

name

firs tName

la stName

add ress

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 entities2. Weak entities3. Binary 1:* relationships4. Binary 1:1 relationships5. Recursive 1:1 relationships6. Super- and subclasses later!!7. Binary *:* relationships8. Complex relationships9. Multi-valued attributesCheck: 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 entities2. Weak entities3. Multi-valued attributes4. Binary relationships

1:*1:1 (also discusses 1:1 recursive)

*:*5. Ternary relationships6. 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

Orders

CustomercustID {PK}name

SuppliersuppID {PK}nameaddress

ProductprodID {PK}typename

datequantity

1..*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

Step 4 Example

Manages1..1 0..1

• “Each branch has one manager, each manager may manage a branch (but those at head office don’t)”

ManagermanagerID {PK}namesalary

BranchbName {PK}addressphone

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

StaffID {PK}namedepartment

Supervises

0..1

1..1“Each staff member has one supervisor and may supervise one staff member”

One relation: Staff(ID, supervisorID*, name, department)OrTwo 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