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This solution can perform well even when you have multiple page requests that usually move forward that is, page 1 is requested, then page 2, then page 3, and so on, as long as a small number of pages is requested and you have an index to support the requests When the rst page of rows is requested, the relevant data/index pages are physically scanned and loaded into cache (if they re not there already) When the second page of rows is requested, the data pages for the rst request already reside in cache, and only the data pages for the second page of rows need to be physically scanned This requires mostly logical reads (reads from cache), and physical reads are needed only for the requested page Logical reads are much faster than physical reads, but keep in mind that they also have a cost that accumulates.

To add to the confusion, there are various conventions for expressing date and time values The value 02/12/10 means different things to different people When this string must be converted to a date and time type, SQL Server will convert it based on the language settings of the session The session s language is determined by the login s default language, but it can be overwritten by using the SET LANGUAGE session option You can also control how date and time literals comprising digits and separators are interpreted by using the SET DATEFORMAT option, specifying a combination of the characters d, m, and y For example, mdy means month, day, year (By the way, SET LANGUAGE implicitly sets DATEFORMAT to match the language s convention for date formatting .

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Multipage Access Another solution for paging typically performs better overall than the previous solution when you have multiple page requests that do not move forward, if the result set is not very large First, materialize all pages in a table along with row numbers and create a clustered index on the row number column:.

This query is incorrect for the same reason as the previous one, but it is clear that we have to complete aggregate binding for the entire query just to realize this. The MAX(T1.c2) in the inner query must be evaluated in the outer query much as it was in the query SELECT c1, MAX(c2) FROM dbo.T1; just shown, and therefore, the use of the nonaggregated column c1 in the SELECT list is illegal and the query is incorrect.

SELECT ROW_NUMBER() OVER(ORDER BY qty, empid) AS rownum, empid, mgrid, qty INTO #SalesRN FROM dbo.Sales; CREATE UNIQUE CLUSTERED INDEX idx_rn ON #SalesRN(rownum);

) So you have tools to control the way some date and time literals will be interpreted, but you realize that by issuing one of the aforementioned SET options, you re changing the behavior of the whole session What if other code that will end up running in your session is supposed to be dependent on the login s default language This consideration is especially important with international applications Whenever possible, I write code that is independent of any settings or switches in the system Each of the date and time types supports several forms of language-neutral character.

Now you can satisfy any page request with a query like the following:

string literals . This means that when you convert the literal character string to the target date and time type, SQL Server interprets the value the same way regardless of the effective language or DATEFORMAT setting . Table 10-2 provides the language-neutral forms supported by each of the date and time types . I strongly recommend sticking to those to avoid ambiguity .

One of the most important and complex components involved in processing your queries is the query optimizer The optimizer's job is to produce an efficient execution plan for each query in a batch or a stored procedure The plan lists the steps SQL Server has to carry out to execute your query, and it includes such information as which index or indexes to use when accessing data from each table in the query The plan also includes the strategy for processing each join operation, each aggregation, each sort, and each partitioned table access The plan shows an intent to perform operations on parallel threadsthat is, where the row streams are partitioned, repartitioned, and then merged into a single stream SQL Server's query optimizer is a cost-based optimizer, which means that it tries to come up with the cheapest execution plan for each SQL statement.

DECLARE @pagesize AS INT, @pagenum AS INT; SET @pagesize = 5; SET @pagenum = 2; SELECT rownum, empid, mgrid, qty FROM #SalesRN WHERE rownum BETWEEN @pagesize * (@pagenum-1) + 1 AND @pagesize * @pagenum ORDER BY rownum;

TABLe 10-2

The execution plan for this query is shown in Figure 6-10 (abbreviated by removing the operators that calculate boundaries up to the Merge Interval operator to focus on the actual data access).

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