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With cursors it s different in the sense that you actually force order in the data, and therefore contradict the model SQL Server 2008 lacks full support for window functions and window specifications compared to the ANSI SQL standard It supports the window partition (PARTITION BY) and order (ORDER BY) clauses with four ranking functions (ROW_NUMBER, RANK, DENSE_RANK, and NTILE) These functions are handled by SQL Server s engine very efficiently compared to alternative solutions using cursors As for the OVER clause for aggregate functions, SQL Server 2008 supports only a window partition clause, but not the window order and frame (ROWS, RANGE) clauses The lack of support for window order and frame clauses is the main obstacle to efficient set-based queries for running aggregates and similar calculations For such calculations, cursor-based solutions are currently more efficient I ll demonstrate this.

in the section Running Aggregations later in this chapter . The SEARCH clause for recursive common table expressions (CTEs) has not been implemented in SQL Server 2008 . Matching problems are another kind of problem in which cursor solutions are faster than set-based solutions I ll also demonstrate this use of cursors . With matching problems, I haven t found set-based solutions that perform nearly as well as cursor solutions . Of course, from time to time you should revisit problems for which cursor solutions perform better then set-based ones . You might come up with a new set-based approach, and you might be able to benefit from enhancements in SQL Server .

Replication is the dedication of additional hardware and software to a given activity in order to provide more processing capability.

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In this chapter s introduction, I talked about the benefits that set-based solutions have over cursor-based ones I mentioned both logical and performance benefits For the most part, efficiently written set-based solutions will outperform cursor-based solutions for two reasons First, you empower the optimizer to do what it s so good at generating multiple valid execution plans and choosing the most efficient one When you apply a cursor-based solution, you re basically forcing the optimizer to go with a rigid plan that doesn t leave much room for optimization at least not as much room as with set-based solutions Second, the processing of each cursor row involves overhead that is not applicable when processing set-based code You can run some simple tests to witness and measure this overhead for example, by comparing the costs of scanning a table by using a simple query and by using a cursor .

If you express the cost of scanning n rows with a query as n, you can express the cost of scanning the same number of rows with a cursor as n + n o, where o represents the overhead, or extra cost, associated with the processing of a single cursor row You can eliminate the actual disk I/O cost by running the code twice (The first run will load the data to cache ) To eliminate the time it takes to generate the output, you should run your code with the Discard results after execution option in SQL Server Management Studio (SSMS) is turned on The difference in performance between the set-based code and the cursor code will then be the cursor s overhead I will now demonstrate how to compare scanning the same amount of data with set-based code versus with a cursor .

Run the following code to generate a table called T1, with a million rows, each containing slightly more than 200 bytes:.

Combining replication and load balancing is sometimes referred to as server clustering. Setting up proxies and caching data can be even better than replicating functionality and balancing loads.

SET NOCOUNT ON; USE tempdb; IF OBJECT_ID('dbo.T1', 'U') IS NOT NULL DROP TABLE dbo.T1; GO SELECT n AS keycol, CAST('a' AS CHAR(200)) AS filler INTO dbo.T1 FROM dbo.Nums WHERE n <= 1000000; CREATE UNIQUE CLUSTERED INDEX idx_keycol ON dbo.T1(keycol);

With the exception of cable or DSL connections, which typically do not require a user name and password, you need to use the New Connection Wizard to set up your connection. Before going through the wizard, make sure that you have the following information available from your service provider: Specific IP address or the address of the DHCP server DNS address and domain name

You can find the code to create and populate the Nums table in 2, User-Defined Functions . Turn on the Discard results after execution option in SSMS (under Query | Query Options | Results | Grid Or Text) . Now run the following code to issue a checkpoint to ensure that all dirty pages are flushed from cache to disk, and then clear the cache:

CHECKPOINT; DBCC DROPCLEANBUFFERS;

Run the following set-based code twice the first run measures performance against a cold cache, and the second measures it against a warm cache:

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