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Know more about what affects query performance. Know how to measure query performance. Know how to write more efficient queries.
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Evaluating Query Performance
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One of the most important aspects of tuning queries is measuring performance. When measuring performance, you need to know 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.
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Query Cost
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The query cost is typically (but not always, as you will soon see) a good 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 (I/O) resources used by the query. The lower the query cost, theoretically, the better the query performance is. The query cost is not affected by issues such as resource contention or waiting for locks. The query cost is typically a good performance measurement, but when certain items are used in a query, such as scalar user-defined functions (UDFs) and Common Language Runtime (CLR) routines, the cost for these items is not calculated, which renders the query cost lower than a truly accurate assessment. This is why it is called estimated query cost.
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Page Reads
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Page reads represents the number of 8-kilobyte (KB) 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 causes each query execution to output something similar to the following in the Messages tab of the query window:
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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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Lesson 1: Tuning Queries
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 read-ahead 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. LOB data is stored outside the row for the data types varchar(max), nvarchar(max), varbinary(max), text, ntext, image, and XML. The page reads metric does not take into account the amount of CPU resources used when executing the query. This is why page reads are typically not as appropriate a performance measurement as the query cost. This metric also has the same problem with scalar UDFs 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.
Query Execution Time
The execution time of the query is the most volatile metric. It is affected by blocking (locks), as well as resource contention on the server. That said, it is particularly important to always include the query execution time metric in performance comparisons because it can help you spot problems missed by the other performance metrics (page reads and query cost). If you execute SET STATISTICS TIME ON, SQL Server returns the execution time in milliseconds for each query execution.
Examining the Theoretical Query Execution Order
It is vital to have a basic understanding of the theoretical execution order of a SELECT statement when working with query tuning. This helps you understand what SQL Server actually needs to do to produce the query results. The theoretical execution order is referred to as theoretical because the optimizer might change the actual execution order to optimize performance. An alternative execution order is used only if the query results would be the same were the theoretical execution order to be used. The execution order needs to be split into two branches because it differs if the UNION clause is included in the query or not. A simplified version of the first branch, without UNION, is described in Table 6-1, showing the order in which clauses are processed.
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