This article provides 10 tips for improving the performance of SQL Server applications. Some of the tips include using EXISTS instead of COUNT(*) when checking for existence, being careful when using WHERE IN and WHERE NOT IN clauses, randomizing result sets with NEWID(), and increasing the default packet size for transferring large data fields.

1. Speed Up SQL Server Apps -- Visual Studio Magazine
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Developers love database programming tips, tricks, and workarounds—especially those that slash development time or Combinations with
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boost application performance. Here's a collection of such nuggets for developing SQL Server applications. the BigInteger
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1) Replace COUNT(*) With EXISTS When Checking for Existence
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Developers often use the value from the COUNT(*) function when enforcing business rules in Transact-SQL code.
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However, try the EXIST clause instead if you're using the COUNT(*) value only to evaluate whether you have at least one
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News row that meets certain conditions. For example, consider this code from the Northwind database: Templates
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IF (SELECT COUNT(*) FROM Orders
WHERE ShipVia = 3) > 0
PRINT 'You cannot delete this shipper'
The execution plan shows that SQL Server has to read all 255 rows in the Orders table before evaluating the IF
expression. You can achieve the same result more efficiently with EXISTS because the IF condition evaluates to true as
soon as SQL Server finds the first occurrence of 3 in the ShipVia column:
IF EXISTS (SELECT * FROM Orders
WHERE ShipVia = 3)
PRINT 'You cannot delete this shipper'
The difference in total execution time isn't much in a sample database such as Northwind, but use this efficient query
against an Orders table with millions of rows and you'll see a major speed improvement.
2) Be Careful When Using WHERE IN and WHERE NOT IN
SQL Server doesn't always choose an optimal execution plan when you have a substantial list of values in the WHERE IN
clause. Using WHERE IN and WHERE NOT IN clauses in T-SQL code can produce an execution plan involving one or
more nested loops. This increases the number of comparisons SQL Server must perform exponentially. Use the WHERE
IN clause only if you have a short list of values you need to evaluate:
USE Northwind
--This query takes 9 ms to execute
SELECT *
FROM Customers
http://visualstudiomagazine.com/articles/2004/07/01/speed-up-sql-server-apps.aspx[08/29/2012 4:29:12 PM]

2. Speed Up SQL Server Apps -- Visual Studio Magazine
WHERE CustomerID NOT IN
(SELECT CustomerID FROM Orders) FREE WHITEPAPERS
Replace the WHERE IN clause with OUTER JOIN if you're using a subquery to generate a potentially large list. Doing so Five Tips for Delivering
can improve performance significantly: Working Software with
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USE Northwind
--This query takes 3 ms to execute 5 Ways Today’s Backup
SELECT c.* and Restore
FROM Customers c Technologies Can Put
LEFT OUTER JOIN Orders o
ON o.CustomerID = c.CustomerID Your Business on the
WHERE o.CustomerID IS NULL Fast Track
In this case, the second query uses LEFT OUTER JOIN, producing an execution plan that lets it run about three times Microsoft Uses
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faster than the first query.
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The LEFT OUTER JOIN selects all rows from the Customer table—whether or not a customer placed any orders—and Software to Eliminate
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joins them with the Orders table. Then the WHERE clause filters out the rows where the columns from the Orders table
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have NULL values. Either way, you get a list of customers who placed no orders, but the second way gives SQL Server a
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lot less work to do. I rewrote a query recently using this technique, and the execution time went from 50 seconds to about Features DBAs Should
500 ms. Know About
3) Randomize Resultset Orders With NewID() > MORE TECHLIBRARY
You occasionally might need to randomize the order of the resultset retrieved from SQL Server. This is often the case in
database searches where certain products or services would gain unfair advantage against others based simply on their
name. I've seen a few clever (and not so clever) solutions for randomizing resultsets, but the solution is actually simple.
You can use the NewID() function in Transact-SQL to generate a GUID for each row, then order the results by the
generated GUID:
SELECT * FROM Products
ORDER BY NEWID()
SQL Server returns products in a different order every time you run the query. You also can use this technique to return a
random row from a table:
SELECT TOP 1 * FROM Products
ORDER BY NEWID()
However, be careful when using this technique with large tables. You're only asking for one random row, but the execution
plan shows that SQL Server gives you that random row only after reading each row in the table, generating a GUID for
each row, then sorting all the rows. Consequently, SQL Server needs several seconds to give you a random row from a
table with a few million rows. So don't use the "SELECT TOP 1?" technique on huge tables. Instead, restrict the random
selection to a subset of the large table. Select a random range, then use "SELECT TOP 1?" within that range.
4) Increase Default Packet Size for Large Data Fields
SQL Server client applications communicate with instances of SQL Server through Net-Libraries. Client Net-Libraries and
Server Net-Libraries communicate over the network by exchanging network packets. The size of network packets depends
on the data access API you're using. The default packet size is 4,096 bytes in ADO and 8,192 bytes in ADO.NET.
These sizes work well in most scenarios, but sometimes you can improve data exchange velocity greatly by increasing
packet size—especially if you're sending or receiving large amounts of XML data, or if you're storing images in SQL Server.
The client and server libraries must exchange and process fewer packets when you increase packet size. Maximum packet
size is 32,767 bytes. You can increase packet size in ADO or ADO.NET simply by including the Packet Size property in the
connection string:
"?;Packet Size=32767;?"
The speed gained in data upload and download depends on the size of your data fields and on your network topology. One
of my applications stores XML data in SQL Server, with each XML field about 500K in size. My benchmarks show that the
application exchanged XML data with SQL Server about twice as fast after increasing the packet size to 32,767 bytes.
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