5 Implementing Data Integrity Rules

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5.1 What is a data integrity rule?

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5.2 Why data integrity rules should always be implemented in the database

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5.3 Specifying business rules

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5.4 Categories of business rules

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5.5 Implicit Data Integrity Rules of table definitions

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5.5.1 Data type, length, precision, scale and semantics

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5.5.1.1 NUMBER (and its subtypes)

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5.5.1.2 DATE, TIMESTAMP and TIMESTAMP WITH TIME ZONE

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5.5.1.3 VARCHAR2, CHAR, NVARCHAR2, NCHAR

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5.5.1.4 Spatial types

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5.5.1.5 RAW and LONG RAW

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5.5.1.6 CLOB, BLOB and BFILE

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5.5.1.7 XMLTYPE and JSONTYPE

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5.5.1.8 BOOLEAN

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5.5.1.9 User-defined data types

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5.5.2 Collation

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5.5.3 Optionality

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5.5.4 Auto-increment property

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5.5.5 Default Value

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5.6 Implementing Data Integrity using constraints

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5.6.1 VALIDATE/NOVALIDATE

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5.6.2 DEFERRABLE constraints

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5.6.3 Collation

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5.6.4 The purpose of check constraints

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5.6.5 Advantages of check constraints over other implementations of attribute and tuple rules

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5.6.6 Disadvantages of check constraints

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5.6.7 Examples of check constraints

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5.6.7.1 Constraint example 1 Testing dates

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5.6.7.2 Constraint example 2 The exclusive arc relation

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5.6.7.3 Constraint example 3 Testing on limit values

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5.6.7.4 Constraint example 4 Validating JSON

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5.6.7.5 Constraint example 5 Checking domain values

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5.6.7.6 Constraint example 6 Conditional optionality

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5.6.8 Summary of using database constraints

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5.7 Implementing Data Integrity Rules using database triggers

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5.7.1 Examples of implementing data integrity rules in database triggers

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5.7.1.1 Trigger example 1 Conditional optionality

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5.7.1.2 Trigger example 2 Restricted foreign keys

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5.7.1.3 Trigger example 3 Conditional updatability

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5.7.1.4 Trigger example 4 Domain checks against a table

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5.7.1.5 Trigger example 5 Preventing overlapping value ranges and gaps between ranges

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5.7.2 Summary using database triggers

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5.8 Implementing business rules and functionality using APIs

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5.8.1 An API for creating an Order

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6 Which language do we speak? Communicating with the database