I have a select statement which is infact a subquery within a larger select statement built up programmatically. The problem is if I elect to include this subquery it acts as a bottle neck and the whole query becomes painfully slow.
An example of the data is as follows:
Payment
.Receipt_no|.Person |.Payment_date|.Type|.Reversed|
2|John |01/02/2001 |PA | |
1|John |01/02/2001 |GX | |
3|David |15/04/2003 |PA | |
6|Mike |26/07/2002 |PA |R |
5|John |01/01/2001 |PA | |
4|Mike |13/05/2000 |GX | |
8|Mike |27/11/2004 |PA | |
7|David |05/12/2003 |PA |R |
9|David |15/04/2003 |PA | |
The subquery is as follows :
select Payment.Person,
Payment.amount
from Payment
inner join (Select min([min_Receipt].Person) 'Person',
min([min_Receipt].Receipt_no) 'Receipt_no'
from Payment [min_Receipt]
inner join (select min(Person) 'Person',
min(Payment_date) 'Payment_date'
from Payment
where Payment.reversed != 'R' and Payment.Type != 'GX'
group by Payment.Person) [min_date]
on [min_date].Person= [min_Receipt].Person and [min_date].Payment_date = [min_Receipt].Payment_date
where [min_Receipt].reversed != 'R' and [min_Receipt].Type != 'GX'
group by [min_Receipt].Person) [1stPayment]
on [1stPayment].Receipt_no = Payment.Receipt_no
This retrieves the first payment of each person by .Payment_date (ascending), .Receipt_no (ascending) where .type is not 'GX' and .Reversed is not 'R'. As Follows:
Payment
.Receipt_No|.Person|.Payment_date
5|John |01/01/2001
3|David |15/04/2003
8|Mike |27/11/2004
I am unable to move the subquery out to a temporary table as temporary tables are simply not supported within the programming language used by my application.
Edit : Incorrect statement. Temporary tables are supported and therefore this is a valid option.
Following a post on StackOverflow -
The Query was rewritten as the following.
Query 1.
select min(Payment.Person) 'Person',
min(Payment.receipt_no) 'receipt_no'
from
Payment a
where
a.type<>'GX' and (a.reversed not in ('R') or a.reversed is null)
and a.payment_date =
(select min(payment_date) from Payment i
where i.Person=a.Person and i.type <> 'GX'
and (i.reversed not in ('R') or i.reversed is null))
group by a.Person
I added this as a subquery within my much larger query, however it still ran very slowly. So I tried rewriting the query whilst trying to avoid the use of aggregate functions and came up with the following.
Query 2.
SELECT
receipt_no,
person,
payment_date,
amount
FROM
payment a
WHERE
receipt_no IN
(SELECT
top 1 i.receipt_no
FROM
payment i
WHERE
(i.reversed NOT IN ('R') OR i.reversed IS NULL)
AND i.type<>'GX'
AND i.person = a.person
ORDER BY i.payment_date DESC, i.receipt_no ASC)
Which I wouldn't necessarily think of as being more efficient. In fact if I run the two queries side by side on my larger data set Query 1. completes in a matter of milliseconds where as Query 2. takes several seconds.
However if I then add them as subqueries within a much larger query, the larger query completes in hours using Query 1. and completes in 40 seconds using Query 2.
I can only attribute this to the use of aggregate functions in one and not the other.
RANK()
or equivalent? \$\endgroup\$ – ANeves thinks SE is evil Nov 8 '12 at 14:14RANK()
is not available in SQL Server 2k. :( \$\endgroup\$ – ANeves thinks SE is evil Nov 12 '12 at 8:27