I'm designing a database with the following attribute dependencies: Approach 1: A <- B <- C <-D Approach 2: A <- B, {A,B} < C, {A,B,C} <- D;
Please I need your help on which approach is better. Thanks
EDIT
Sample tables for approach 1
Country_info ------------- , state info, city_info, village_info
id | country_id | name
TABLE PAIRS
id | state_id | country_id
id | division_id | state_id
id | village_id | division_id
Now, I have the id of a village and I want to know the name of the country in which it belongs. I will have to look for the division, state before arriving at the country.
With the second approach, the village table will have the division_id, state_id and the country_id.
Thanks!
如果村庄是经常使用的“主要”对象(并且也经常使用它与其他表的关系),那么通过使用第二种方法,您将减少代码行数并提高性能(例如,按国家对村庄进行过滤) 。
KISS.
Table 1: A business/person/etc has an address and a City.
Table 2: The City also includes the Viliage, State, Province, Country_code, Postal_code, whatever.
Normalizing each layer is overkill.
If you have half a dozen tables, imagine the number of JOINs
needed to get all the parts of the address!
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