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MCITP SQL Server 2005 Database Developer All-in-One Exam Guide
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Creating an Indexed VIEW
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As we learned in 2, VIEWs don t actually hold data, but instead are virtual tables that can help us focus the data from existing tables We can use them to provide vertical partitioning (hide columns) and provide a layer of security since permissions to underlying tables don t need to be granted when granting access to the VIEW If we want to optimize a VIEW, we can create an index on the VIEW This is referred to as creating an indexed VIEW Indexes on VIEWs are created as unique clustered indexes An indexed VIEW gets the best performance gains in two situations:
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The data in the VIEW is frequently read but rarely updated If the data in the index is frequently changed, then the overhead of index maintenance takes away from the performance gains The VIEW is used to produce aggregations of data (such as SUM, AVG, and so on) Since the index materializes the VIEW, the indexed VIEW can be searched instead of having to search the base table(s) to produce the aggregations The size of the indexed VIEW would typically be significantly smaller than the base table(s) EXAM TIP Indexed VIEWs provide the best performance gains when used to produce aggregations on a large amount of data, and on data that is frequently read but not frequently updated
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Indexed VIEWs are a little picky While we covered this in more detail in 2, remember that several prerequisites must be met when creating indexed VIEWs These include the following:
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Tables must be referenced by two-part names (for instance, schematablename) in the VIEW definition Included functions must also be referenced with a two-part name The VIEW must be created using the WITH SCHEMABINDING option Included functions must also use the WITH SCHEMABINDING option The VIEW can only reference tables, not other VIEWs All base tables referenced by the VIEW must be in the same database as the VIEW and have the same owner as the VIEW The VIEW must be deterministic Several SET options must be configured according to specific rules
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EXAM TIP Some of the basic rules for creating indexes on VIEWs are that: 1) They must be created with the SCHEMABINDING option 2) Objects must be referenced with a two-part name (for example, schematable) 3) The VIEW must be deterministic (it cannot contain any nondeterministic functions) 4) All base tables referenced by the VIEW must be in the same database as the VIEW and have the same owner as the VIEW
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7: Optimizing Databases
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My statistics class in college was one of the most challenging classes I had mostly because they seemed to talk in a different language I was able to squeak by, but statistics is not my forte The good news is that all of the heavy lifting needed for statistics is done by the database engine We don t have to be statistical experts, but instead just need to know how SQL Server is using statistics and how they are maintained SQL Server uses statistics to determine how useful an index is when it s creating a query plan Before we explore that further, let s look at statistics in general Statistics is an area of mathematics concerned with masses of data It examines a sample of the whole population in order to interpret or predict information on the whole population Imagine it snows in your city Once the snowstorm is over, the weather forecaster says you ve received 18 inches of snow I doubt that the weather forecaster went all over the city with a ruler measuring how thick the snowfall was at five million different places within the city Instead, he might have five or ten measuring tools scattered throughout the city and by looking at those measurements, he can fairly accurately say what happened throughout the entire city In this example, the whole population is the amount of snow that fell on every inch of the city A portion of the whole population (the sample) is the measurements by the five or ten measuring tools scattered throughout the city Similarly, the query analyzer within SQL Server uses statistics to determine how dense or how selective an index is for any given query Instead of looking at all five million rows of an index, the query analyzer can look at the statistics (maybe 300 rows) of the index and make decisions on the usefulness of the index
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