在mysql中加入两个表并获取记录

Question

I have two tables " contacts " and " users ". Users table storing data with "," separated. Need to distinct data in " Contacts " column from " Contacts " table. And need to join with " Users " table, and get the records.

Contacts Table
--------------------------
id |    user_Id      | contats
--------------------------
1  |   2147483647    | 90123456789,90123456789,90123456789,90123456789
2  |   2147483647    | 90123456789,90123456789,90123456789,90123456789
3  |   919444894154  | 90123456789,90123456789,90123456789,90123456789

Users Table
-----------------------------
id | username | email                  | phone
-----------------------------
1  | bhavan   | bhavanram93@gmail.com  | 90123456789
2  | bhavan   | bhavanram93@gmail.com  | 90123456789
3  | prince   | prince@gmail.com       | 1234567980
4  | bhavan   | bhavanram93@gmail.com  | 90123456789
5  | hello    | hello@gmail.com        | 1234567890
6  | bhavan   | bhavanram93@gmail.com  | 90123456789

Answer 1

Your table Contacts shouldn't be constructed this way.

Since you want 1 Users table containing all the data about a user, and 1 Contacts table containing links between different users, you'd rather do this kind of table structure :

Contacts table

id | user_id | contact_id
-------------------------
1  | 1       | 2
2  | 1       | 3
3  | 2       | 3

That'll allow you to do something like :

SELECT *
FROM Users
JOIN Contacts ON (Users.id = Contacts.contact_id)
WHERE Contacts.user_id = 1

Which will return all the data of the contacts of the user 1.

Your current structure is a huge ongoing mess, it's the opposite of being flexible.

Answer 2

You should restructure your db to a normalized format as Steve suggest.

But if you cant:

SELECT *
FROM Users
JOIN Contacts 
  ON CONCAT(',', Contacts.contacts, ',') like
     CONCAT('%,', Users.phone, ',%')
WHERE Contacts.user_id = 1

the idea is you convert your contacts to

,    <numbers>    ,
,90123456789,90123456789,90123456789,90123456789,

and try to match with

 %,90123456789,%

Note this approach cant use any index so will have bad performance with many rows. if you are in the order of 1k-10k rows may be ok. More than that you need consider restructure your db.