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-- Add a the ring buffer target and configure it -- to retain 1000 events ALTER EVENT SESSION TrackDF ON SERVER ADD TARGET package0.ring_buffer ( SET occurrence_number = 1000 ); GO -- Start the session and begin event collection ALTER EVENT SESSION TrackDF ON SERVER STATE = start GO -- Use a deprecated feature SELECT DATABASEPROPERTY('master','IsTruncLog') AS IsTruncLog; -- View the collected events SELECT CAST(xet.target_data as xml) FROM sys.dm_xe_session_targets xet JOIN sys.dm_xe_sessions xe ON (xe.address = xet.event_session_address) WHERE xe.name = 'TrackDF' GO -- Stop the event session and remove it from the server ALTER EVENT SESSION TrackDF ON SERVER STATE = STOP; GO DROP EVENT SESSION TrackDF ON SERVER GO

Having greater control of their destiny has been a goal of teachers for many years In the late 1990s, recommendations to that effect by national panels and commissions held new promise of implementation

which is now called Runge's function He took equidistantlyspaceddata points from this function over the interval t-l, ll He then used interpolatingpolynomials of increasing order and found that ashe took more points,the polynomialsandthe original curve differed greatly as the order was increased considerably Further,the situationdeteriorated Duplicate Runge'sresult by using the polyf it and polyval functionsto fit fourth- and tenthorder polynomials to 5 and 1l equally spacedpoints generated with Eq (152$ Create

>> x >> Y = linspace(-I,L,5); I/(I+25*x^2);

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<RingBufferTarget eventsPerSec="0" processingTime="0" totalEventsProcessed="1" eventCount="1" droppedCount="0" memoryUsed="424"> <event name="deprecation_final_support" package="sqlserver" id="207" version="1" timestamp="2008-10-30T08:54:31.689Z"> <data name="feature"> <type name="unicode_string" package="package0" /> <value>DATABASEPROPERTY</value> <text /> </data> <data name="message"> <type name="unicode_string" package="package0" /> <value>DATABASEPROPERTY will be removed in the next version of SQL Server. Avoid using this feature in new development work, and plan to modify applications that currently use it.</value> <text />

Next, a more finally spacedvector of rx valuescan be computedso that we cancreate a snooth plot of the results: >> xx = linspace(-1,1); Recall that l inspace automaticallycreates100 points if the desirednumberof points is not specifiedThe po ly f r t function can be usedto generate coefficients thefounhof the order polynomial, and the polval function can be usedto generate polynomial the interpolation at the finely spaced valuesof xx:

Summary

= po11'f it >> 14 = polyval >> p (x,y , 4) ; (p, xx) ;

Finally we can generate valuesfor Runge'sfunction itself and plot them alongwiththe polynomial fit and the sampleddata: >> yr - Ii (1+25*xx"2);

releases of the product. Pick any of the methods mentioned in this chapter and make sure that your applications will have a greater longevity.

>> plot (x,y,' o',xx,y4,xx,yt:,' --' )

As in Fig 1512, polynomialdoesa poorjob of followingRunge'stunction the Continuingwith the analysis tenth-order polynomial can be generated plotted the and with

Cristian Lefter is a SQL Server MVP and a former SQL Server developer, currently working as a consultant at Micro Training, a consulting and training company. Cristian is a writer, blogger, SQL expert, and frequent reviewer for Manning, Apress, Wiley, and other publishers, as well as for ASPToday, Simple-Talk, Microsoft E-Learning, Asentus, Content Master, GrandMasters, and more. He s based in Bucharest, Romania. You can reach him at his blog at http:/ /sqlserver.ro/blogs/ cristians_blog/default.aspx, or his email address at CristianLefter@hotmail.com.

linspace( 1,1,11); I / (I+25*x ^2) ;

and astronomically sized datasets, but it can also scale down to support incredibly small and resource-constrained scenarios. Many workforces are increasingly becoming mobile and working outside the fixed confines of an office environment. This presents a challenge to system architects, as they need to consider how to make their company data accessible to field workers while coping with issues such as the high costs and slow speeds (and potential unavailability) of network connectivity. In building a traditional three-tier distributed application, you may have used SQL Server 2008 to store your data on a large centralized server and had clients retrieve data over the network on an as-needed basis. When building mobile applications for devices such as laptops, Tablet PCs, and PDAs, you re more likely to place a local data store on each client. This is required to store data so that the application can continue to function while offline. It may also be desirable to locally cache large fairly static datasets (such as customer or product lists) to avoid repeatedly transferring data over expensive or slow networks. SQL Server Compact Edition is the smallest member of the SQL Server family and is optimized to be an embedded database for single-user applications running on the Tablet PC, Windows Mobile PDA, and desktop platforms. It s designed to fit in your pocket with a disk footprint of less than 4 MB.

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