1. Concept
There are two forms of data dictionary
1. Put the attribute code of the main body into a separate table, instead of putting it together with the main body, only the code of the attribute is kept in the main body. Here the number of attributes is constant, while the number of attribute values can be changed.
2. Use a table to put all the attribute information with the same structure, the different values of different attributes are uniformly coded, the "type" is used to distinguish different attributes, and the list of attribute codes is kept in the main body. In this way, the number of attributes owned by the subject is variable.
The second type of data dictionary is more abstract, higher level, and more general and versatile than the first.
2. Example description
A staff table, including: name, nationality, credentials, and education.
Nationalities include: Chinese, American, Japanese
Documents include: ID card, driver's license
Educational qualifications include: PhD, master, bachelor, junior college
Three, the first form of data dictionary
The ultimate goal is the employee table, and each attribute of each employee has fixed content. For example, the nationality of an employee can only be: China, the United States, and Japan. Therefore, each attribute is designed as a table, and the ID in each attribute table can be referenced in the employee table.
1. A form of nationality
| Nationality ID |
Nationality name |
| 001 |
China |
| 002 |
United States |
| 003 |
Japan |
2. A document form
| ID |
the name of your ID |
| 001 |
ID card |
| 002 |
driver license |
3. A list of academic qualifications
| Education ID |
Education name |
| 001 |
PhD |
| 002 |
master's degree |
| 003 |
Undergraduate |
| 004 |
Junior college |
4. Staff table
| Staff ID |
Name |
Country of Citizenship |
Certificate |
Education |
| 2001 |
Zhang San |
001 |
001 |
002 |
| 2002 |
Li Si |
003 |
002 |
004 |
Advantages: Each attribute table can be dynamically modified.
Disadvantages: When querying employees, a lot of tables are required to perform a joint table query. If there are many attributes, it is not convenient to expand.
Two, the second form of data dictionary
Observing the above attributes, there is a commonality: there are only 2 fields, the first field is the identification, and the second field is the content.
So, you can put these attributes in a table:
1. Attribute table
| Logo |
classification |
content |
| 001 |
contry |
China |
| 002 |
contry |
United States |
| 003 |
contry |
Japan |
| 101 |
identify |
ID card |
| 102 |
identify |
driver license |
| 201 |
education |
PhD |
| 202 |
education |
master's degree |
| 203 |
education |
Undergraduate |
| 304 |
education |
Junior college |
2. Staff table
| Staff ID |
Name |
Country of Citizenship |
Certificate |
Education |
| 2001 |
Zhang San |
001 |
101 |
202 |
| 2002 |
Li Si |
003 |
102 |
304 |
Advantages: There is only one attribute table.
If you want to query all nationalities, just query "category"="contry" in the attribute table.
Third, the above employee table has another shortcoming, that is, the attribute field of each employee is fixed.
If: one employee may have many attributes and another employee has few attributes, there is a waste of space.
Therefore, you can split the employee table into two tables:
1. Staff table
| Staff ID |
Name |
| 2001 |
Zhang San |
| 2002 |
Li Si |
2. Attribute table
| Staff ID |
Attribute identification |
| 2001 |
001 |
| 2001 |
101 |
| 2001 |
202 |
| 2002 |
003 |
| 2002 |
102 |
| 2002 |
304 |
The employee ID is 2001 and has 3 attributes, namely: 001, 101, 202
职员ID为2002的，拥有3个属性，分别是：003，102，304
这样的话，每个职员可以拥有不同数量的属性。