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However, the rst intermediate level is also used in fragmentation analysis and to drive read-ahead during large range scans of the index To understand these structures, we start with de ning the leaf level in generic terms (meaning that these basic concepts apply to both clustered and nonclustered indexes) The leaf level of an index contains something (we discuss the speci cs when we get into the topic of physical index structures later in the chapter) for every row of the table in indexed order In this discussion, we are focusing on traditional indexes and those created without lters, which refers to a new SQL Server 2008 feature called ltered indexes Non-leaf levels exist to help navigate to a row at the leaf level but the architecture is rather straightforward.

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5. Add the following code to the BackgroundCurrentWorker_DoWork event handler:

Each non-leaf level stores something for every page of the level below and levels are added until the index builds up to a root of one page Each higher non-leaf level in the index (that is, farther away from the leaf level) is smaller than the one below it because each row at a level contains only the minimum key value that can be on each page of the level below, plus a pointer to that page Although it sounds like this could result in a lot of levels (that is, a tall tree), the limitation on the size of the key (which has a maximum of 900 bytes or 16 columns whichever comes rst) in SQL Server helps to keep index trees relatively small..

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In fact, in the example that we show coming up which has an index with fairly wide rows and a key de nition that is at the maximum size the tree size of this example index (at the time the index is created) is only eight levels deep To see this tree (and the computations used to determine its size), we use an example where the leaf level of the index contains 1,000,000 rows We put quotes around rows because these are not necessarily data rows these are just leaf-level rows of any index Later in the chapter when we discuss the physical structures of each speci c index you will see exactly what leaf-level rows are and how they are structured.

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However, for this example, we re focused on an abstract index where we re concerned only about the leaf and non-leaf levels as well as how they re structured within the con nes of SQL Server pages (8-KB pages) In this example, our leaf-level rows are 4,000 bytes, which means we can store only two rows per page For a table with 1,000,000 rows, the leaf level of our index would have 500,000 pages Relatively speaking, this is a fairly wide row structure; however, we are not wasting a lot of space on the page If our leaf-level page had two 3,000-byte rows we d still only t two rows per page, but then we d have 2,000 bytes of wasted space (This would be an example of internal fragmentation, which is discussed in the section entitled Fragmentation, later in this chapter.

) Now, why are these just rows and not speci cally data rows The reason is that this leaf level could be the leaf level for a clustered index (therefore data rows) or these leaf-level rows could be rows in a nonclustered index that uses INCLUDE (which was added in SQL Server 2005) to add non-key columns to the leaf level of the index When INCLUDE is used, leaf-level pages can contain wider rows (wider than the 900-byte or 16-column key maximum) Again, although this doesn t currently sound interesting, we explain later in this chapter why this can be bene cial In this example, the leaf level of this index would be 4 GB in size (500,000 8-KB pages) at the time it s created This structure, depending on its de nition could become larger and possibly very fragmented if a lot of new data is added.

Right up front, the focus of the strategy is not the competition The goal of a company is not to beat the competition, but to enhance the customer and make a good profit So the first focus of an XML implementation strategy is the customer the customer s requirements, needs, wants, and desires

private void BackgroundCurrentWorker_DoWork(object sender, DoWorkEventArgs e) { // This method will execute in the background thread created // by the BackgroundWorker component string desiredLocationCode = e.Argument.ToString(); MSNWeatherData myMSNWeather = new MSNWeatherData(); e.Result = myMSNWeather.GetWeatherReport(desiredLocationCode); }

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