data independant rules

Codd's 12 rules are a set of 12 rules proposed by Edgar F. Codd, a pioneer of the relational model for databases, designed to define what is required from a database management system in order for it to be considered relational, i.e., an RDBMS. [1][2]

Codd produced these rules as part of a personal campaign to prevent his vision of the relational database being diluted, as database vendors scrambled in the early 1980s to repackage existing products with a relational veneer. Rule 12 was particularly designed to counter such a positioning. In fact, the rules are so strict that all popular so-called "relational" DBMSs fail on many of the criteria.[citation needed]

[edit] The rules

Rule 000: The system must qualify as relational, as a database, and as a management system.

For a system to qualify as a relational database management system (RDBMS), that system must use its relational facilities (exclusively) to manage the database.

Rule 1: The information rule:

All information in the database is to be represented in one and only one way, namely by values in column positions within rows of tables.

Rule 2: The guaranteed access rule:

All data must be accessible with no ambiguity. This rule is essentially a restatement of the fundamental requirement for primary keys. It says that every individual scalar value in the database must be logically addressable by specifying the name of the containing table, the name of the containing column and the primary key value of the containing row.

Rule 3: Systematic treatment of null values:

The DBMS must allow each field to remain null (or empty). Specifically, it must support a representation of "missing information and inapplicable information" that is systematic, distinct from all regular values (for example, "distinct from zero or any other number," in the case of numeric values), and independent of data type. It is also implied that such representations must be manipulated by the DBMS in a systematic way.

Rule 4: Active online catalog based on the relational model:

The system must support an online, inline, relational catalog that is accessible to authorized users by means of their regular query language. That is, users must be able to access the database's structure (catalog) using the same query language that they use to access the database's data.

Rule 5: The comprehensive data sublanguage rule:

The system must support at least one relational language that

(a) Has a linear syntax
(b) Can be used both interactively and within application programs,
(c) Supports data definition operations (including view definitions), data manipulation operations (update as well as retrieval), security and integrity constraints, and transaction management operations (begin, commit, and rollback).

Rule 6: The view updating rule:

All views that are theoretically updatable must be updatable by the system.

Rule 7: High-level insert, update, and delete:

The system must support set-at-a-time insert, update, and delete operators. This means that data can be retrieved from a relational database in sets constructed of data from multiple rows and/or multiple tables. This rule states that insert, update, and delete operations should be supported for any retrievable set rather than just for a single row in a single table.

Rule 8: Physical data independence:

Changes to the physical level (how the data is stored, whether in arrays or linked lists etc.) must not require a change to an application based on the structure.

Rule 9: Logical data independence:

Changes to the logical level (tables, columns, rows, and so on) must not require a change to an application based on the structure. Logical data independence is more difficult to achieve than physical data independence.

Rule 10: Integrity independence:

Integrity constraints must be specified separately from application programs and stored in the catalog. It must be possible to change such constraints as and when appropriate without unnecessarily affecting existing applications.

Rule 11: Distribution independence:

The distribution of portions of the database to various locations should be invisible to users of the database. Existing applications should continue to operate successfully :

(a) when a distributed version of the DBMS is first introduced; and
(b) when existing distributed data are redistributed around the system.

Rule 12: The nonsubversion rule:

If the system provides a low-level (record-at-a-time) interface, then that interface cannot be used to subvert the system, for example, bypassing a relational security or integrity constraint.

Data independence is the type of data transparency that matters for a centralized DBMS. It refers to the immunity of user applications to make changes in the definition and organization of data, and vice-versa.

Physical data independence deals with hiding the details of the storage structure from user applications. The application should not be involved with these issues, since there is no difference in the operation carried out against the data.

The data independence and operation independence together gives the feature of Data Abstraction.

There are two levels of data independence.

[edit] First level

The logical structure of the data is known as the schema definition. In general, if a user application operates on a subset of the attributes of a relation, it should not be affected later when new attributes are added to the same relation.

[edit] Second level

The physical structure of the data is referred to as physical data description. Physical data independence deals with hiding the details of the storage structure from user applications. The application should not be involved with these issues since, conceptually, there is no difference in the operations carried out against the data.

We may also look upon the two data independence :

1.Logical Data Independence : The ability to change the logical schema without changing the physical schema is called Logical Data Independence.

Example -Addition or removal of new entities, attributes, or relationships to the conceptual schema should be possible without having to change existing external schemas or having to rewrite existing application programs.


2.Physical Data Independence : The ability to change the physical schema without changing the logical schema is called Physical Data Independence.

Example : A change to the internal schema, such as using different file organisation or storage structures, storage devices, or indexing strategy, should be possible without having to change the conceptual or external schemas