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Nonclustered indexes created on a clustered table are architected differently than on a heap. The only difference is that the row locator in a nonclustered index created on a clustered table is a value called a clustering key, as opposed to being an RID. The clustering key consists of the values of the clustered index keys from the pointed row and the uniqui er (if present). The idea is to point to a row logically as opposed to physically. This architecture was designed mainly for OLTP systems, where clustered indexes often suffer from many page splits upon data insertions and updates. If nonclustered indexes pointed to RIDs of rows, all pointers to the data rows that moved would have to be changed to re ect their new RIDs and that s true for all relevant pointers in all nonclustered indexes. Instead, SQL Server maintains logical pointers that don t change when data rows move. Figure 4-18 illustrates what the PK_Orders nonclustered index might look like; the index is de ned with the orderid as the key column, and the Orders table has a clustered index de ned with the orderdate as the key column. A seek operation looking for a particular key in the nonclustered index (some orderid value) will end up reaching the relevant leaf row and have access to the row locator. The row locator in this case is the clustering key of the pointed row. To actually grab the pointed row, a lookup operation will need to perform a whole seek within the clustered index based on the acquired clustering key. This type of lookup is known as a key lookup, as opposed to a RID lookup. I will demonstrate this access method later in the chapter. The cost of each lookup operation here (in terms of the number of page reads) is as high as the number of levels in the clustered index (3 in our case). That s compared to a single page read for a RID lookup when the table is a heap. Of course, with range queries that use a nonclustered index and a series of lookups, the ratio between the number of logical reads in a heap case and a clustered table case will be close to 1:L, where L is the number of levels in the clustered index. Before you worry too much about this point and remove all clustered indexes from your
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The DateTime type also offers a Parse method:
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Now, after you construct a formatter, construct an instance of Ver1ToVer2SerializationBinder and set the formatter s Binder read/write property to refer to the binder object . After setting the Binder property, you can now call the formatter s Deserialize method . During deserialization, the formatter sees that a binder has been set . As each object is about to be deserialized, the formatter calls the binder s BindToType method, passing it the assembly name and type that the formatter wants to deserialize . At this point, BindToType decides what type should actually be constructed and returns this type . Note The SerializationBinder class also makes it possible to change the assembly/type
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Domain Controllers
public static class Monitor { public static Boolean Wait(Object obj); public static Boolean Wait(Object obj, Int32 millisecondsTimeout); public static void Pulse(Object obj); public static void PulseAll(Object obj); }
Identity
Open two connections and call them connection 1 and connection 2 . From connection 1, issue the following code, which updates col2 to Version 2 within a transaction and retrieves the modified column values, keeping the transaction open:
computer2 192.168.10.2
regarding the import. You can then save these text files for reference or to examine any errors that occurred during import.
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