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In a cluster, data rows are lined up the way we want them for a range search, an ORDER BY or a GROUP BY Not only is this good for selections, it also reduces the number of "hot spots" a potential problem that we'll discuss in 15, "Locks" Clustering speeds up queries even if rows aren't 100% in order Provided that there is any ordering, queries will be faster on average provided that the cluster key (column1 in our earlier example) is important The DBMS can use a clustered index to find out what the row order should be (an index is a handy structure for the purpose because indexes are ordered) You just have to tell the DBMS that you want a clustered index and that you want column1 to be the cluster key There can, of course, be only one clustered index per table because the data rows can only be sorted in one order In contrast, when a table has only a nonclustered index, pages and data rows are not stored in an order based on the index key, but rather in a heap like the pile of papers on an untidy person's desk Usually a new row is just dumped wherever it can fit in the file that's why it's called a heap The difference between a weak-clustered index and a strong-clustered index is the fierceness with which the DBMS maintains cluster-key order Most DBMSs have weak-clustered indexes, and they only guarantee to make a good-faith attempt to maintain order Two of the Big Eight Microsoft and Sybase have strong-clustered indexes, and they maintain order forcibly, even when this requires a lot of reorganizing of both index keys and data rows (Oracle has both weak-clustered indexes and indexorganized tables; index-organized tables are in fact strong-clustered indexes, but Oracle doesn't call them that) Because their effect is major, we will examine strong-clustered indexes more closely Strong-clustered indexes The concept is simple: The leaf level of a strong-clustered index doesn't contain mere index keys Instead, the leaf level contains the data rows themselves Figure 9-8 and Figure 9-9 illustrate this by showing a conventional "data heap and separate" structure (Figure 9-8) and a radical "clustered index with integrated data" structure (Figure 9-9) containing the same data Figure 9-8 A heap-and-index structure. asp.net qr code reader QR Code Scanner in ASP.Net - CodeProject
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