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Appendix B
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If a page is already in memory when the read-ahead request is posted, the contiguous read is still needed and is faster than breaking up read requests into multiple physical requests. SQL Server considers the read to be unusable for the page in question, but many of the pages around it might be usable. However, if a write operation is in progress when the read is posted, the subsystem has to determine which image of the read to return. Some implementations return the current version of the page before the write is complete; others make the read wait until the write completes; and yet others return a combination, showing partially new data and partially old data. The key is that SQL Server will discard the read as unusable but the subsystem needs to maintain the proper image for subsequent read operations. The inprogress write, when completed, must be the next read image returned to the server running SQL Server.
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Read-ahead vs. parallel query plans
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Do not confuse read-ahead with parallel query plans. Read-ahead occurs independently of the parallel query plan selection. The parallel plan might drive I/O harder because multiple workers are driving the load, but read-ahead occurs for serial and parallel plans. To ensure that parallel workers do not work on the same data sets, SQL Server implements the parallel page supplier to help segment the data requests.
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Having a good understanding of the internal workings and architecture of the SQL Server 2005 database storage engine helps database developers to develop applications that can overcome the weaknesses of the storage engine as well as take advantage of its strengths.
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SQL Server 2005 Query Engine
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Simply put, the SQL Server 2005 query engine, sometimes known as the relational engine, is responsible for efficiently answering requests from users and providing output. The query engine is made up of the following components, as shown in Figure B-12:
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Query Engine
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Figure B-12
The SQL Server 2005 query engine components
SQL Server 2005 Architecture and Internals
The Query Optimizer is responsible for constructing an efficient plan of attack to answer queries. Procedure Cache Manager The Procedure Cache Manager is responsible for managing the storage and retrieval of query execution plans that the optimizer has constructed. Statistics Manager The Statistics Manager is responsible for maintaining statistical information on indexes to ensure that the most up-to-date information is used when constructing a query plan. Each of these components works together to construct the most efficient plan, or set of instructions, to provide to the storage engine for data retrieval and storage. One of the most prevalent design goals for the SQL Server 2005 query engine was to make it invisible to the user. The hope was that developers would never need to know about the internal workings of the query engine, and it would just do its job without interaction. In previous versions of SQL Server, developers of large-scale applications spent a fair amount of time trying to fool the query engine into generating more efficient query plans. This practice led to a number of query hints and options being embedded in T-SQL code that helped instruct the query engine. Unfortunately, due to the improvements in the SQL Server 2005 query engine, this practice can lead to less-efficient queries, and as the applications are upgraded to SQL Server 2005, many developers are finding that their applications are running more slowly. Developers need to understand exactly how the query engine processes data in SQL Server 2005 to make the best choices for creating efficient queries within their applications.
Query Optimizer
Query Engine Processing
The most basic query type is the SELECT query. SELECT simply instructs the database engine to retrieve certain data based on the criteria specified in the FROM and WHERE clauses. A SELECT statement is nonprocedural, in that it does not state the exact steps that the query engine should use to retrieve the requested data. This means that the query engine must analyze the statement to determine the most efficient way to extract the requested data. This is referred to as query optimization. The component that does this is called the query optimizer. The input to the optimizer consists of the query, the database schema (table and index definitions), and the database statistics. The output of the optimizer is a query plan. A SELECT statement only defines the following:
The format of the result set. This is specified mostly in the select list. However, other clauses, such as ORDER BY and GROUP BY, also affect the final form of the result set. The tables that contain the data. This is specified in the FROM clause.
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