Reputation: 2672
To get the list of distinct values from table1 and column1 is as easy as doing this:
SELECT distinct(column1)
FROM table1
However, I inherited (unfortunately) a database where column1 contains values separated by a comma
column1
--------
row 1: name1,name2
row 2: name2,name3
row 3: name4,name1,name3
I need to get the list of distinct values from column1, so it looks like this:
column1
--------
name1
name2
name3
name4
Any ideas?
Upvotes: 0
Views: 1531
Reputation: 222482
A generic method uses a recursive query (available in MySQL 8.0 only):
with recursive
data as (select concat(column1, ',') rest from mytable),
words as (
select substring(rest, 1, locate(',', rest) - 1) word, substring(rest, locate(',', rest) + 1) rest
from data
union all
select substring(rest, 1, locate(',', rest) - 1) word, substring(rest, locate(',', rest) + 1) rest
from words
where locate(',', rest) > 0
)
select distinct word from words order by word
Sample data:
| column1 | | :---------------- | | name1,name2 | | name2,name3 | | name4,name1,name3 |
Results:
| word | | :---- | | name1 | | name2 | | name3 | | name4 |
Upvotes: 3
Reputation: 1269823
You have to split them apart. If you have at most three names in the column, then one method is:
select substring_index(column1, ',', 1) as name
from t
union -- on purpose to remove duplicates
select substring_index(substring_index(column1, ',', 2), ',', -1) as name
from t
where name like '%,%'
union -- on purpose to remove duplicates
select substring_index(substring_index(column1, ',', 3), ',', -1) as name
from t
where name like '%,%,%';
Upvotes: 1
Reputation: 366
You can't. Your database does not adhere to the the first principle in designing normalized databases :- Atomicity. It says to store one and only one attribute in a column and yet you have so many. You need to retrieve the entire columns value, split and de-dupe them from your application. SQL cannot do this for you.
What you really need to do here is to have a seperate NAMES table and apply DISTINCT on name column after filtering relevant rows.
Upvotes: 0