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The Query Optimizer uses scalar values within the query text to help estimate the cardinality for each operator in the query. This ultimately helps choose the lowest-cost plan, as cardinality is a major input into the costing functions. Parameterized queries can make this process more dif cult because parameters can change from one execution to the next. Given that SQL Server automatically parameterizes queries as well, this design choice affects more queries than one would expect. When estimating cardinality for parameterized queries, the Query Optimizer usually uses a less accurate estimate of the average number of distinct values in the column or it sniffs the parameter value from the context (usually only on recompile, unfortunately).

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8

This sniffed value is used for cardinality estimation and plan selection, but it is not used to simplify the query or otherwise depend on the speci c parameter value So, parameter snif ng can help pick a plan that is good for a speci c case Because most data sets have nonuniform column distributions, the value sniffed can affect the run time of the query plan If a value representing the common distribution is picked, this might work very well in the average case and less optimally in the outlier case (a value with substantially more instances than the average case) If the outlier is used to sniff the value, then the plan picked might perform noticeably worse than it would have if the average case value had been sniffed.

8. Using the IntelliSense automatic using statement feature, click the red and yellow underline on StreamWriter, and add the following using directive to the top of the code file:

This can be a problem due to the plan caching policy in SQL Server a parameterized query is kept in the cache even though the values change from execution to execution When a recompile happens, only the information from that speci c context is used to recompile The OPTIMIZE FOR hint allows the query author to specify the actual values to use during compilation This can be used to tell the Query Optimizer, This is a common value that I expect to see at run time, and this can provide more plan predictability on parameterized queries This hint works for both the initial compilation and for recompiles While specifying a common value is usually the best approach, test out this hint to make sure that it gives the desired behavior.

In Listing 8-17, the OPTIMIZE FOR hint is used to force the query plan to account for an average value in the optimization of the query (Note: I am only demonstrating that the plans change, not that these two plans perform differently This technique can be used on arbitrarily complex queries to hint plans) Note that when the value of 23 is used to compile the query (as shown in Figure 8-79), a different index is picked than when it is not (shown in Figure 8-78) because 23 is a very common value and it is not as selective as the predicate on col2 Parameter values can cause index changes, join order changes, and other more complex changes to your query plan testing forced parameters is highly recommended..

5

In this chapter, we ll start with a basic introduction to tables and continue into some very detailed examinations of their internal structures Simply put, a table is a collection of data about a speci c entity (a person, place, or thing) that has a discrete number of named attributes (for example, quantity or type) Tables are at the heart of Microsoft SQL Server and the relational model in general In SQL Server, a table is often referred to as a base table to emphasize where data is stored Calling it a base table also distinguishes it from a view a virtual table that s an internal query referencing one or more base tables or other views Attributes of a table s data (such as color, size, quantity, order date, and supplier s name) take the form of named columns in the table.

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using System.IO;