CMP-3440 – Database Systems

Logical Design

Lecture 03“zain”

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Database Design Process

ConceptualModel

LogicalModel

External Model

Conceptual requirements

Conceptual requirements

Conceptual requirements

Conceptual requirements

Application 1

Application 1

Application 2 Application 3 Application 4

Application 2

Application 3

Application 4

External Model

External Model

External Model

Internal Model

Logical Model: Mapping to a Relational Model

• Each entity in the ER Diagram becomes a relation.

• A properly normalized ER diagram will indicate where intersection relations for many-to-many mappings are needed.

• Relationships are indicated by common columns (or domains) in tables that are related.

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Data Dependencies

• Functional Dependency:• Given a relation R(A,B,C,D) where A, B, C, D are attributes• Functional Dependencies A -> BCD, BC -> D

• Full Functional Dependency:• A -> B,C,D

• Partial Dependency:• (A,B,C,D,E,F) • AB -> C,D,EF• A -> C,E and B -> D,F

• Transitive Dependency:• (A,B,C,D)• A -> B B - > C C -> D

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Normalization

• Normalization theory is based on the observation that relations with certain properties are more effective in inserting, updating and deleting data than other sets of relations containing the same data

• Normalization is a multi-step process beginning with an “unnormalized” relation

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Normal Forms

• First Normal Form (1NF)

• Second Normal Form (2NF)

• Third Normal Form (3NF)

• Boyce-Codd Normal Form (BCNF)

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Normal Forms

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Boyce-

Codd and

Higher

Functional

dependency

of nonkey

attributes on

the primary

key - Atomic

values only

Full

Functional

dependency

of nonkey

attributes on

the primary

key

No transitive

dependency

between

nonkey

attributes

All

determinants

are candidate

keys - Single

multivalued

dependency

Unnormalised Form (UNF)

• A table that contains one or more repeating groups.

• To create an unnormalized table:• Transform data from information source (e.g. form) into table format with

columns and rows.

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First Normal Form

• To move to First Normal Form a relation must contain only atomic values at each row and column.

• A relation in which intersection of each row and column contains one and only one value.• Disallows composite attributes, multivalued attributes & nested relations

• UNF to 1NF• Nominate an attribute or group of attributes to act as the key for the

unnormalized table.

• Identify repeating group(s) in unnormalized table which repeats for the key attribute(s).

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UNF to 1NF

• Remove repeating group by:

• Entering appropriate data into the empty columns of rows containing repeating data (‘flattening’ the table).

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Second Normal Form

• A relation is said to be in Second Normal Form when every nonkey attribute is fully functionally dependent on the primary key.• That is, every nonkey attribute needs the full primary key for unique

identification

• Identify primary key for the 1NF relation.

• Identify functional dependencies in the relation.

• If partial dependencies exist on the primary key remove them by placing them in a new relation along with copy of their determinant.

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2NF Example

• EMP_PROJ

• SSN, PNUMBER -> HOURS

• SSN -> ENAME

• PNUMBER -> PNAME, PLOCATION

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SSN PNUMBER HOURS ENAME PNAME PLOCATION

Third Normal Form

• A relation is said to be in Third Normal Form if there is no transitive functional dependency between nonkey attributes• When one nonkey attribute can be determined with one or more

nonkey attributes there is said to be a transitive functional dependency.

• 3NF - A relation that is in 1NF and 2NF and in which no non-primary-key attribute is transitively dependent on the primary key.

• 3NF - All non-prime attributes are fully & directly dependent on the PK.

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3NF

• EMP_PROJ

• SSN -> ENAME, BDATE, ADDRESS, DNUMBER

• DNUMBER -> DNAME, DMGRSSN

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SSN ENAME BDATE ADDRESS DNUMBER DNAME DMGRSSN

SSN ENAME BDATE ADDRESS DNUMBER

DNUMBER DNAME DMGRSSN

Boyce-Codd Normal Form

• Most 3NF relations are also BCNF relations.

• A 3NF relation is NOT in BCNF if:• Candidate keys in the relation are composite keys (they are

not single attributes)• There is more than one candidate key in the relation, and

• A relation is in BCNF if & only if every determinant is a candidate key.

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BCNF Example

• 2 composite candidate keys:• FD1:{Client, Subject} → Staff

• FD2:{Client & Staff} → Subject

• These candidate keys are overlapping on Client.

• Staff is a determinate but not a candidate key

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Client Subject Staff

Client Staff Subject

Data Integrity

• Ensuring the integrity of the organization’s databases is a key component of the DBA’s job. A database is of little use if the data it contains is inaccurate or if it cannot be accessed due to integrity problems. The DBA has many tools at his disposal to ensure data integrity.

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Entity Integrity

• That each occurrence of an entity must be uniquely identifiable.

• Although most DBMSs do not FORCE the creation of a primary key for each table, it is a tenet of the Relational Model.

• Enforce entity integrity by creating a PK for each table in the database.• A primary key constraint can consist of one or more columns from the

same table that are unique within the table.

• A table can have only one primary key constraint, which cannot contain nulls.

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Uniqueness

• A unique constraint is similar to a primary key constraint. • However, each table can have many unique constraints. • Unique constraints cannot be used to support referential

constraints.

• The values stored in the column, or combination of columns, must but unique within the table.• That is, no other row can contain the same value.

• A unique constraint most likely requires a unique index to enforce.

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Data Types

• Data type and data length are the most fundamental integrity constraints applied to data in the database. • DBAs must choose data types wisely.• The DBMS will automatically ensure that only the correct type of data is

stored in that column.

• Choose the data type that most closely matches the domain of values for the column. • For example, a numeric column should be defined as one of the

numeric data types: integer, decimal, or floating point. • If you specify a character data type for a column that will contain

numeric data the DBMS cannot automatically enforce the integrity of the data.

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Default Values

• Each column can be assigned a default value that will be used if subsequent INSERTs do not provide a value.

• Each column can have only one default value.

• The column’s data type, length, and property must be able to support the default value specified.

• The default may be null, but only if the column is created as a nullable column.

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CHECK Constraints

• A check constraint is a DBMS-defined restriction placed on the data values that can be stored in a column or columns.

• The expression is explicitly defined in the table DDL and is formulated in much the same way that SQL WHERE clauses are formulated.

• Any attempt to modify the column data (INSERT or UPDATE) causes the expression to be evaluated.

• If the modification conforms to the expression, the modification is permitted to proceed.

• If not, the statement will fail with a constraint violation.

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CHECK Constraints Example

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Referential Integrity

• Referential Integrity (RI) is a method for ensuring the “correctness” of data.

• The identification of the primary and foreign keys that constitute a relationship between tables is a component of defining referential integrity.

• RI also requires the definition of rules that dictate how modification of data stored in columns involved in the relationship can be accomplished.

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RI: Parent / Child

• For any given referential constraint, the parent table is the table that contains the primary key, and the child table is the table that contains the foreign key.

• The parent table in the employed-by relationship is the DEPT table.

• The child table is the EMP table.

RI Rules

Three types of rules can be attached to each referential constraint:

• INSERT rule

• UPDATE rule

• DELETE rule

INSERT Rules

• The INSERT rule indicates what will happen if you attempt to insert a value into a foreign key column without a corresponding primary key value in the parent table. There are two aspects to the RI INSERT rule:

1. It is never permissible to insert a row into a dependent table with a foreign key value that does not correspond to a primary key value. This is known as the restrict-INSERT rule.

2. Whether actual values must be specified instead of nulls.

UPDATE Rule

• The UPDATE rule controls updates such that a foreign key value cannot be updated to a value that does not correspond to a primary key value in the parent table.

• There are, however, two ways to view the update rule:

• Foreign key perspective.

• Primary key perspective.

UPDATE Rule: FK Perspective

• Once you have assigned a foreign key to a row, either at insertion or afterward, you must decide whether that value can be changed.

• This is determined by looking at the business definition of the relationship and the tables it connects.

• If you permit a foreign key value to be updated, the new value must either be equal to a primary key value currently in the parent table or be null.

UPDATE Rule: PK Perspective

If a primary key value is updated, three options exist for handling foreign key values:

• Restricted UPDATE. The modification of the primary key column(s) is not allowed if foreign key values exist.

• Neutralizing UPDATE. All foreign key values equal to the primary key value(s) being modified are set to null. Of course, neutralizing UPDATE requires that nulls be permitted on the foreign key column(s).

• Cascading UPDATE. All foreign key columns with a value equal to the primary key value(s) being modified are modified as well.

DELETE Rule

Similar to the primary key perspective of the update rule, three options exist when deleting a row from a parent table:

• Restricted DELETE. The deletion of the primary key row is not allowed if a foreign key value exists.

• Neutralizing DELETE. All foreign key values equal to the primary key value of the row being deleted are set to null.

• Cascading DELETE. All foreign key rows with a value equal to the primary key of the row about to be deleted are deleted as well.