Take a look at this query.
SELECT *
FROM
(
SELECT customer_id, ‘MTD’ AS record_type, COUNT(*), SUM(…), AVG(…)
FROM payment_table
WHERE YEAR(payment_dt) = YEAR(GETDATE())
and MONTH(payment_dt) = MONTH(GETDATE())
GROUP BY customer_id) MTD_payments
UNION ALL
(
SELECT customer_id, ‘YTD’ AS record_type, COUNT(*), SUM(…), AVG(…)
FROM payment_table
WHERE
WHERE YEAR(payment_dt) = YEAR(GETDATE())
GROUP BY customer_id) YTD_payments
UNION ALL
(
SELECT customer_id, ‘LTD’ AS record_type, COUNT(*), SUM(…), AVG(…)
FROM payment_table) LTD_payments
) payments_report
ORDER BY customer_id, record_typeCan you see the problem?
A person had this query, it would run for over 24 hours. Wow, that is pretty bad, I don't think I had ever written something that ran over an hour, and the ones I did were mostly defragmentation and update statistics jobs.
The problem is that the following piece of code
where year(payment_dt) = year(getDate())
and month(payment_dt) = month(getDate())
is not sargable. First what does it mean to be sargable? A query is said to be sargable if the DBMS engine can take advantage of an index to speed up the execution of the query (using index seeks, not covering indexes). The term is derived from a contraction of Search ARGument Able.
This query is not sargable because there is a function on the column, whenever you use a function on the column you will not get an index seek but an index scan. The difference between an index seek and an index scan can be explained like this: when searching for something in a book, you go to the index in the back find the page number and go to the page, that is an index seek. When looking for something in a book you go from page one until the last page, read all the words on all the ages and get what you need, that was an index scan. Do you see how much more expensive in terms of performance that was?
Let's get back to the query, what can we do to make this piece of code use an index seek?
where year(payment_dt) = year(getDate())
and month(payment_dt) = month(getDate())
You would change it to this:
where payment_dt >= dateadd(mm, datediff(mm, 0, getdate())+0, 0)
and payment_dt < dateadd(mm, datediff(mm, 0, getdate())+1, 0)
You can see the complete question on the MSDN forum site here:
http://forums.microsoft.com/msdn/ShowPost.aspx?PostID=3746751&SiteID=1The Person said that his query went from over 24 hours to 36 seconds. Wow!! That is very significant. hardware cannot help you out if you have bad queries like that.
The same exact day I answered a very similar question, take a look here:
http://forums.microsoft.com/msdn/ShowPost.aspx?PostID=3752248&SiteID=1The person had this
AND DATEDIFF(d, '08/10/2008', DateCreated) >= 0
AND DATEDIFF(d, DateCreated, '08/15/2008') >= 0
I told him to change it to this
AND DateCreated >= '08/10/2008'
and DateCreated <= '08/15/2008'
And that solved that query. If you are interested in some more performance, I have written some Query Optimization items on the LessThanDot Wiki. Below are some direct links
Case Sensitive Search
No Functions on Left Side of Operator
Query Optimizations With Dates
Optimization: Set Nocount On
No Math In Where Clause
Don't Use (select *), but List Columns
If you are interested in some blogposts about dates, take a look at these two which I wrote earlier
How Are Dates Stored In SQL Server?Do You Know How Between Works With Dates?Labels: database, Dates, Indexing, Performance Tuning, rdbms, SQL, T-SQL, temporal data
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