Hello,
I've a table ORD(ordid, custid, total)
customer's orders where
custid is customer's ID and total is payment
I need to select those customers where every payment is greater
than average.
I tried:

but it gives me the customers which also has payment less than average.
how can i fix that it gives me only those who are greater?

Your query seems fine to me. I would suspect a problem in your DBMS.

Move/copy the sub-query to the where-clause.

select custid
from ord , (select avg(total) from ord) dv
where total > (select avg(total) from ord)

and then remove the subquery from the FROM clause

Semantically, this is not necessary. The subquery constructs a table with 1 row and 1 column, and that is joined to each row in the ORD table. Isn't that so? Therefore, I still claim that the query is valid and the DBMS executing the query screws up, i.e. has a bug.

Select-list expressions (e.g. the subquery discussed) can not be used in the where clause.

Here's Celko's standard reply:
"Here is how a SELECT works in Standard SQL ... at least in theory. Real
products will optimize things when they can.

a) Start in the FROM clause and build a working table from all of the
joins, unions, intersections, and whatever other table constructors are
there. The table expression> AS <correlation name> option allows you
give a name to this working table which you then have to use for the
rest of the containing query.

b) Go to the WHERE clause and remove rows that do not pass criteria;
that is, that do not test to TRUE (reject UNKNOWN and FALSE). The WHERE
clause is applied to the working set in the FROM clause.

c) Go to the optional GROUP BY clause, make groups and reduce each
group to a single row, replacing the original working table with the new
grouped table. The rows of a grouped table must be group
characteristics: (1) a grouping column (2) a statistic about the group
(i.e. aggregate functions) (3) a function or (4) an expression made up
those three items.

d) Go to the optional HAVING clause and apply it against the grouped
working table; if there was no GROUP BY clause, treat the entire table
as one group.

e) Go to the SELECT clause and construct the expressions in the list.
This means that the scalar subqueries, function calls and expressions in
the SELECT are done after all the other clauses are done. The “AS”
operator can also give names to expressions in the SELECT list. These
new names come into existence all at once, but after the WHERE clause,
GROUP BY clause and HAVING clause has been executed; you cannot use them
in the SELECT list or the WHERE clause for that reason.

If there is a SELECT DISTINCT, then redundant duplicate rows are
removed. For purposes of defining a duplicate row, NULLs are treated as
matching (just like in the GROUP BY).

f) Nested query expressions follow the usual scoping rules you would
expect from a block structured language like C, Pascal, Algol, etc.
Namely, the innermost queries can reference columns and tables in the
queries in which they are contained.

--CELKO-- "

As you can see, the result set rows are already defined when the select-list expressions are processed.

Thanks for your replies, i've fixed the query to:
now everyone who has values below average are removed and those who has
values above average only are shown.

@JarHL: I don't see how you could possibly interpret the explanations you cited as an argument against subselects in a WHERE clause or SELECT list.

A scalar subselect is an expression. Based on that, you can use subselects in both, a WHERE clause and the SELECT list. Even more so, there are predicates like EXISTS, IN, =ANY, =ALL, etc. that operate on whole sets, i.e. subselects.

that's true, eh

you made it worse

the fact that it might actually be returning what you think it should be returning is just as mysterious as why your first query wasn't returning what you think it should be returning

So it comes down to either throw away your DBMS or to get it fixed.

why ? the result of first query was incorrect.
let's say the table has those tuples:
ORD(ordid,custid,total)

(100,1,50)
(101,2,56)
(102,3,48)
(103,3,52)

the average is 51.5
the first query will return custid 1,2 and 3 (first, second and last row)
but this is not correct because custid 3 has also an order which is less than
average. but the problem was to select only those customers whose EVERY order is above average.
so the second query will return the correct result, custid 1 and 2.

oh, that's pretty cool, i understand

now that you've explained what you were doing

wow! that's cool haven't learnt that yet
why count(*) ? i don't quite understand the logic of having count(*)...