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Database optimization is a compelling part of the database developer s job role. The difference in performance between a well-optimized database and a non-optimized database can be enormous. Working with optimization demands a keen eye for details and an interest in understanding how the database engine works. The more you learn about what Microsoft SQL Server actually needs to do to complete a task, the greater your chance will be to successfully optimize the database. In a sense, you must try to become SQL Server. The task of optimizing a database can be broken down into subtasks, including: optimizing queries and database routines, creating appropriate indexes, and normalizing and de-normalizing the database. (Database normalization is beyond the scope of this training kit.)
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Exam objectives in this chapter:
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Evaluate query performance.
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Analyze query plans. Modify queries to improve performance. Test queries for improved performance.
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Detect locking problems. Modify queries to optimize client and server performance. Rewrite subqueries to joins. Design queries that have search arguments (SARGs). Convert single-row statements into set-based queries. Design an index strategy. Analyze index use across an application. Add, remove, or redesign indexes. Optimize index-to-table-size ratio.
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Optimize indexing strategies.
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Optimizing SQL Server 2005 Performance
Optimize data storage.
Choose column data types to reduce storage requirements across the enterprise. Design appropriate use of varchar across the enterprise. Denormalize entities to minimize page reads per query. Optimize table width.
Before You Begin
To complete the lessons in this chapter, you must have:
A thorough understanding of Transact-SQL, including inner joins, outer joins, apply, and subqueries. A good understanding of the indexes in SQL Server databases. SQL Server 2005 and the AdventureWorks sample database installed.
Lesson 1: Optimizing and Tuning Queries
Lesson 1: Optimizing and Tuning Queries
Estimated lesson time: 60 minutes
Optimizing and tuning queries is an important task for a database developer. Throughout this lesson, we will discuss several options for optimizing queries.
Evaluating Query Performance
One of the most important aspects when measuring performance is what to actually measure, that is, what metric to use. In SQL Server, there are three main metrics to consider: query cost, page reads, and query execution time. Exam Tip
In the exam, always consider the performance metric against which your solution to a specific problem is measured.
Query Cost
The query cost is typically the best metric to use when comparing query performance. It is an internal metric used in SQL Server that takes into account both CPU and input/output (IO) resources used by the query. The lower the query cost, the better the query performance. You can find it in the graphical execution plan of the query by moving the mouse pointer over the last (the leftmost) operation in the query and examining the value Estimated subtree cost. The query cost is not affected by things such as locking or resource contention. The cost is typically a good metric, but when certain items are used in a query, such as scalar user-defined functions and CLR routines, the cost for these items is not calculated, which renders the query cost lower than the accurate assessment. This is why it is called estimated query cost. The problem with query cost is discussed in greater detail later in this lesson.
Page Reads
Page reads represents the number of 8-kilobyte data pages accessed by the SQL Server storage engine while executing a query. You can retrieve this metric by executing SET STATISTICS IO ON. This will cause each query execution to output something similar to the following in the Messages tab of the query window:
Table 'Customer'. Scan count 2, logical reads 136, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. Table 'SalesOrderHeader'. Scan count 121, logical reads 822, physical reads 5, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.
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Optimizing SQL Server 2005 Performance
The total page reads of this output is 136 + 822, which is the sum of the values labeled logical reads. Logical reads are the number of pages read from memory. The logical reads represent the total number of data pages read from any index on the SalesOrderHeader table. The other items tell you how many of the logical reads were read from the hard drive (physical and readahead reads), the number of passes through an index or heap it took to respond to the query (scan count), and how many of the page reads were used to retrieve Large OBject (LOB) data (data stored outside of the row for the data types VARCHAR(max), NVARCHAR(max), VARBINARY(max), TEXT, NTEXT, IMAGE, and XML). The metric page reads do not take into account the amount CPU resources used when executing the query. This is why page reads are typically not as accurate a metric as the query cost. This metric also has the same problem with scalar used-defined functions and CLR routines as the query cost, which is that page reads caused by these routines are not included in the output of STATISTICS IO.
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