SQL Delete low counts - sql

Question

I have a table with this data:
Id Qty
-- ---
A 1
A 2
A 3
B 112
B 125
B 109
But I'm supposed to only have the max values for each id. Max value for A is 3 and for B is 125. How can I isolate (and delete) the other values?
The final table should look like this :
Id Qty
-- ---
A 3
B 125
Running MySQL 4.1

Answer 1

Oh wait. Got a simpler solution :
I'll select all the max values(group by id), export the data, flush the table, reimport only the max values.
CREATE TABLE tabletemp LIKE table;
INSERT INTO tabletemp SELECT id,MAX(qty) FROM table GROUP BY id;
DROP TABLE table;
RENAME TABLE tabletemp TO table;
Thanks to all !

Answer 2

Try this in SQL Server:
delete from tbl o
left outer join
(Select max(qty) anz , id
from tbl i
group by i.id) k on o.id = k.id and k.anz = o.qty
where k.id is null
Revision 2 for MySQL... Can anyone check this one?:
delete from tbl o
where concat(id,qty) not in
(select concat(id,anz) from (Select max(qty) anz , id
from tbl i
group by i.id))
Explanation:
Since I was supposed to not use joins (See comments about MySQL Support on joins and delete/update/insert), I moved the subquery into a IN(a,b,c) clause.
Inside an In clause I can use a subquery, but that query is only allowed to return one field. So in order to filter all elements that are not the maximum, i need to concat both fields into a single one, so i can return it inside the in clause. So basically my query inside the IN returns the biggest ID+QTY only. To compare it with the main table i also need to make a concat on the outside, so the data for both fields match.
Basically the In clause contains:
("A3","B125")
Disclaimer: The above query is "evil!" since it uses a function (concat) on fields to compare against. This will cause any index on those fields to become almost useless. You should never formulate a query that way that is run on a regular basis. I only wanted to try to bend it so it works on mysql.
Example of this "bad construct":
(Get all o from the last 2 weeks)
select ... from orders where orderday + 14 > now()
You should allways do:
select ... from orders where orderday > now() - 14
The difference is subtle: Version 2 only has to do the math once, and is able to use the index, and version 1 has to do the math for every single row in the orders table., and you can forget about the index usage...

Answer 3

I'd try this:
delete from T
where exists (
select * from T as T2
where T2.Id = T.Id
and T2.Qty > T.Qty
);
For those who might have similar question in the future, this might be supported some day (it is now in SQL Server 2005 and later)
It won't require a join, and it has advantages over the use of a temporary table if the table has dependencies
with Tranked(Id,Qty,rk) as (
select
Id, Qty,
rank() over (
partition by Id
order by Qty desc
)
from T
)
delete from Tranked
where rk > 1;

Answer 4

You'll have to go via another table (among other things that makes a single delete statement here quite impossible in mysql is you can't delete from a table and use the same table in a subquery).
BEGIN;
create temporary table tmp_del select id,max(qty) as qty from the_tbl;
delete the_tbl from the_tbl,tmp_del where
the_tbl.id=tmp_del.id and the_tbl.qty=tmp_del.qty;
drop table tmp_del;
END;

Answer 5

MySQL 4.0 and later supports a simple multi-table syntax for DELETE:
DELETE t1 FROM MyTable t1 JOIN MyTable t2 ON t1.id = t2.id AND t1.qty < t2.qty;
This produces a join of each row with a given id to all other rows with the same id, and deletes only the row with the lesser qty in each pairing. After this is all done, the row with the greatest qty per group of id is left not deleted.
If you only have one row with a given id, it still works because a single row is naturally the one with the greatest value.
FWIW, I just tried my solution using MySQL 5.0.75 on a Macbook Pro 2.40GHz. I inserted 1 million rows of synthetic data, with different numbers of rows per "group":
2 rows per id completes in 26.78 sec.
5 rows per id completes in 43.18 sec.
10 rows per id completes in 1 min 3.77 sec.
100 rows per id completes in 6 min 46.60 sec.
1000 rows per id didn't complete before I terminated it.