Everything has a life cycle, of course, the database system is no exception!
Database design and ER model This chapter is mainly based on the life cycle of the database system, the design phase of which to explain.
Let's take a look at the life cycle of the database system:
, the life cycle of database system is divided into five stages: planning, requirement analysis, design, realization, operation and maintenance . The design phase includes three aspects of concept, logic, and physics .
The following two sections are focused on conceptual design and logical Design in the design phase, as well as transformation from conceptual design to logical design .
I. Conceptual design (ER model)
The first chapter is about the four models of data abstraction: The conceptual data model, the logical data model, the external data model, and the internal data model, so in this chapter, we mention the concept and logic of the two words, certainly not unfamiliar.
In the first chapter, the concept model is modeled from the point of view of user demand. And our ER model is widely adopted conceptual model design method. Since it's a design approach, we'll explore how to use it.
1. Elements contained in the ER modelin the top map we see that the elements of the ER model are two: entities and relationships. But let's not forget that it also has entities and relationships that both contain attribute elements.
(1)
entity: entity: object;entity set: class;entity type: The definition of the object.
(2)
Contact: Contact: the relationship between entities;Contact Set: A collection of contacts of the same type;Contact Type: definition of contact. (3)
attribute classification:
Simple and composite properties: divided by whether the parent attribute can be decomposed into sub-attributes, there is a dependency between the decomposed sub-attributes. Can be decomposed into composite properties, non-decomposed as simple attributes.
Single-valued and multivalued attributes: depending on how many values are taken, you can take a multi-valued attribute as a multivalued attribute and take a single value as a single-valued attribute.
store attributes and derived properties: store partitioning as necessary. There is no need to store the property as a derived property, and it is necessary to store it for storage.
properties allowed to be null: when there are null values in the database, there are a number of situations that can be difficult to handle and to analyze all the cases.
2. Er model operation and design(1) ER model operation: including merging, splitting, adding and deleting, and other operations. (2) The design of ER model follows a principle: first local, then global, then optimized.
Ii. Logical design (relational model)the logical model is based on the view of database implementation, modeling data. The relational model is a data model that uses key codes to represent the relationships between entities.
1. Terminology: attributes, relationship patterns, tuples, relationships, attribute values. The entire two-dimensional table is a relational pattern, the attribute is a field in a two-dimensional table, the attribute value is a field value, and a tuple represents a record, and a relationship represents a collection of multiple records.
2. Follow the integrity rules (1) Entity: The primary key attribute cannot be a null value. (2) Reference: Do not allow references to entities that do not exist. (3) User defined: Set integrity rules for specific constraints.
Iii. Conceptual Design--Logic design
1. AlgorithmThe conversion of entity type and contact type to relational mode is described respectively. All the same, attributes, attributes, identifiers, etc. become keys.
2. Design Steps(1) Export initial relationship set: Global ER Model--Relationship mode(2) Normalization: Reducing exceptions in relational mode(3) mode evaluation: Check the function and performance to meet the user's requirements(4) mode correction: revise according to the evaluation result(5) Design sub-pattern: Design local Logical Structure
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Principle of "self-taught" database system (II.)--Detailed (database design and ER model)
