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Compact Disk A compact disk (often spelled disc in hi-fi applications), also called a CD, is a plastic disk with a diameter of 472 in (120 cm), on which data can be recorded in digital form Any kind of data can be digitized: sound, images, and computer programs and files This data can also be stored on other digital media of sufficient capacity, such as a computer hard drive or a backup tape drive Digital sound, recorded on the surface of a CD, is practically devoid of the hiss and crackle that bedevil recordings on analog media This is because the information on the disk is binary: a bit (binary digit) is either 1 (high) or 0 (low) The distinction between these two states is more clear-cut than the subtle fluctuations of an analog signal When a CD is prepared, the sound is first subjected to analog-to-digital (A/D) conversion This changes the continuously variable audio waves into logic bits These bits are then burned (literally) into the surface of the disk in the form of microscopic pits The pits are arranged in a spiral track that would, if unwound, measure several kilometers in length Digital signal processing (DSP) minimizes the noise introduced by environmental factors such as microscopic particles on the disk or random electronic impulses in circuit hardware A scrambling process smears recordings throughout the disk, rather than burning the pits in a direct linear sequence This further improves the signal-to-noise (S/N) ratio Compact-disk players recover the sound from a disk without any hardware physically touching the surface A laser beam scans the disk The beam is scattered by the pits and is reflected from the unpitted plastic The result is a digitally modulated beam that is picked up by a sensor and converted into electrical currents These currents proceed to a descrambling circuit, a digital-to-analog (D/A) converter, a DSP circuit, and audio amplifiers Speakers or headphones convert the audio currents into sound waves With a CD player, the track location processes are entirely electronic, and they can all be done quickly Tracks are assigned numbers that you select by pressing buttons It is impossible to damage.

For such comparisons, it s convenient to use two copies of the same database the original database exactly as it exists in production and the modified one with a covering index.

Just as it s a good idea to boost your immune system with sleep, sunlight, and vitamins and to vaccinate yourself (or preferably your children) against standard diseases, so should you try to make your scripts resistant to errors This section shows you three ways of doing so:

Back up your AdventureWorks database, create a new database named AdventureWorks_Copy, and restore the backup of AdventureWorks against AdventureWorks_Copy. You can either do it all via SSMS or you can run the script in listing 1, changing the folder from C:\Temp if necessary.

the CD, no matter how much you skip around among the songs You can move instantly to any desired point within an individual track You can program the system to play only those tracks you want, ignoring the others

RESTORE DATABASE AdventureWorks_Copy FROM DISK=N'C:\Temp\AdventureWorksFullBackup.bak' WITH REPLACE, MOVE 'AdventureWorks_Data' TO 'C:\Temp\AdventureWorks_Copy_Data.mdf', MOVE 'AdventureWorks_Log' TO 'C:\Temp\AdventureWorks_Copy_Log.mdf'

Making sure an item exists before you try to use it Referring to an application by its formal name rather than its common name Breaking up a script into subroutines

Highlight the following query in Management Studio:

These methods of resisting errors are a solid start, not a panacea Even if you use them religiously, you may run into unexpected errors, just as swine flu or avian flu may turn up and brush aside all your health precautions

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SELECT [DueDate],SUM([OrderQty]) AS SumQty FROM [AdventureWorks].[Production].[WorkOrder] GROUP BY [DueDate] SELECT [DueDate],SUM([OrderQty]) AS SumQty FROM [AdventureWorks_Copy].[Production].[WorkOrder] GROUP BY [DueDate]

Press Ctrl-L to see the execution plans. Note that the optimizer expects the covered query to run several times faster, because the covered query is expected to perform several times fewer reads. Is the optimizer correct in its estimate Compare real execution costs and see for yourself. Run the following commands: