SQL SELECT DISTINCT and GROUP BY problem

I need to return only 1 row per specific database entry. For e.g. if I have:

ID col1 col2
1    1    A
2    1    B
3    1    C
4    2    D
5    3    E
6    4    F
7    4    G

in MySQL I can run a query

SELECT DISTINCT col1, col2 FROM table GROUP BY col1

and I will get ->

ID col1 col2
1    1    A
4    2    D
5    3    E
6    4    F

which is what I want, but if I run the same query in SQL Server I get an error..

So, basically I need to return only ONE (or FIRST) "col1" AND its "col2" from each row in the table..

What would be the correct syntax for SQL Server?

Thank y开发者_开发知识库ou for your time!

Andrej

EDIT:

the complete query that works in mysql is ->

SELECT DISTINCT list_order, category_name, category_id
FROM  `jos_vm_category` 
WHERE  `category_publish` =  'Y'
GROUP BY list_order

so, FOR EACH "list_order" number i want to return the category_name and category_id from that row, and ignore every other row with the same "list_order" number

---

Another approach is to use the ROW_NUMBER() function in T-SQL, which allows you to "partition" your data by something - like your col1 here - and get incremental numbers for each of those data partitions. If you want only the first entry for each "partition", just query it this way (using a Common Table Expression - CTE):

;WITH Distincts AS
(
    SELECT ID, col1, col2,
        ROW_NUMBER() OVER (PARTITION BY col1 ORDER BY ID) AS 'RowNo'
    FROM dbo.Table
)
SELECT
    ID, col1, col2
FROM
    Distincts
WHERE
    RowNo = 1

This gives me the output you're looking for.

---

You can get all rows corresponding to the first instance of a value in col1 as follows

SELECT col1, col2
FROM table t1
where not exists 
      (select 1 
         from table t2
        where t2.col1 = t1.col1 and
              t2.id < t1.id)

EDIT: posting a comparison of the queries

EDIT2: Posting the comparison of actual query execution plan, with about 2000 rows of data randomly generated, and with a id being a identity column with a unique index. A second index on id and col1.

Turns out Marc's query is faster after all, at least with this data!