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Until this point in the chapter, ADO and ADO.NET have been shown to be very different technologies despite the similarities in their names and a common purpose. The core of ADO is the Recordset. To modify data through a record set it is necessary to either use a server API cursor that stays in the database or write code that sends updates back to the database once the changes are identified. Both methods have proven to be fragile because of concurrency and contention issues, and both can require a hefty chunk of code. To work with multiple Recordsets, it is necessary to create multiple connections and to juggle the Recordsets in code or pull multiple Recordsets from the database as a collection and work with them one at a time. Either method has proven to be rigid and can require a hefty chuck of often repetitive code. The primary in-memory data store of ADO.NET is the DateSet. The DataAdapter is used to connect the data source and the in-memory data store. In ADO.NET 2.0, the DataSet is more powerful than ever. The DateSet is disconnected from the database to reduce contention in the database and therefore open the door to highly scalable applications. The code required to either fill the DateSet from the database or update the database from the DateSet is minimal.

Summary

The first link value that is assigned in a part must be manually typed in. After you add the first one, you can link other dimensions to this link value by using the scroll arrows shown in Figure 9.9. You cannot edit link values. In order to change the value to which a dimension is linked, you must first unlink the value and then relink it. The Unlink function is available from the RMB menu in the same way that you assign link values. Dimensions that have a link value have the small chain symbol displayed to the left of the dimension.

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A typical traf c shaper consists of a large buffer that is served at a rate smaller than the peak rate of the stream, or of a buffer that is combined with a leaky bucket that holds the part of traf c that is non-conforming with the traf c contract; see Section 222 One may design the shaper to add delays of the same order of magnitude as the timescales of the uctuations to be smoothed Another way to implement a shaper is to collect the traf c that arrives every t time units and then transmit it during the next t time units at a constant rate This rate will differ during each period, re ecting the variable volume of data to be transmitted The above discussion explains the effects of shaping mechanisms on the effective bandwidth of the resulting traf c.

| Z1 |=3 1 <X> cenv <X> <X,Y> [X=Y] Cwait Mess Splitting 1(1)= 1(2)= 1 1(1)= 1 1(2)= 2 Sready < Z1 > 1 | Z1,0 | = 1 | Z1,1 | = 1 1 1 | Z1,2 | = 1 1 <X> cenv <X> <X,Y> [X=Y] Cwait | | Z1,0 1 Z1,2 1 |=1 | |=1 <X> cenv <X> <X,Y> [X=Y] Cwait < Z1,1 , Z1,2 1 1 Mess > Z1,1 1 |=1

Often when modeling, you are required to have a left- and a right-handed part. For this, you need to use a method other than body or feature mirroring. The Mirror Part command creates a brand new part by mirroring an existing part. The new part does not inherit all the features of the original, and so any changes must be created in the original part. If you want different versions of the two parts, you need to use Configurations, which have not been covered yet in this book.

350 (a)

When buffers in the network are large (and hence t is large), then only substantial traf c shaping can reduce the effective bandwidth of the input traf c However, for real-time traf c using small buffers, a moderate amount of traf c shaping can drastically reduce the effective bandwidths and thereby increase the multiplexing capability of the network Let us look at some data for real traf c Figure 49 shows a 1000 epoch trace from a MPEG-1 encoded video of Star Wars, each epoch being 40ms Note the different timescales of burstiness Figure 410 plots an estimate of the effective bandwidth function for this trace Observe that as either t becomes small or s becomes large, the effective bandwidth increases; this corresponds to the source becoming more dif cult to multiplex The explanation is simple.

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