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dencies, except for the special case of declaring superkeys by using the primary key or unique constraints It is possible, although a little complicated, to write assertions that enforce a functional dependency (see Exercise 715); unfortunately, testing the assertions would be very expensive in most database systems Thus even if we had a dependency-preserving decomposition, if we use standard SQL we would not be able to ef ciently test a functional dependency whose left-hand side is not a key Although testing functional dependencies may involve a join if the decomposition is not dependency preserving, we can reduce the cost by using materialized views, which many database systems support Given a BCNF decomposition that is not dependency preserving, we consider each dependency in a minimum cover Fc that is not preserved in the decomposition For each such dependency , we de ne a materialized view that computes a join of all relations in the decomposition, and projects the result on The functional dependency can be easily tested on the materialized view, by means of a constraint unique ( ) On the negative side, there is a space and time overhead due to the materialized view, but on the positive side, the application programmer need not worry about writing code to keep redundant data consistent on updates; it is the job of the database system to maintain the materialized view, that is, keep up up to date when the database is updated (Later in the book, in Section 145, we outline how a database system can perform materialized view maintenance ef ciently) Thus, in case we are not able to get a dependency-preserving BCNF decomposition, it is generally preferable to opt for BCNF, and use techniques such as materialized views to reduce the cost of checking functional dependencies

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The McGraw Hill Companies, 2001

Fig 14-4 A comparison of of e 05t (solid line) and e 3t (dashed line)

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last, the account may contain either $450 or $400, rather than the correct value of $350 To guard against this possibility, the system must maintain some form of supervision But supervision is dif cult to provide because data may be accessed by many different application programs that have not been coordinated previously Security problems Not every user of the database system should be able to access all the data For example, in a banking system, payroll personnel need to see only that part of the database that has information about the various bank employees They do not need access to information about customer accounts But, since application programs are added to the system in an ad hoc manner, enforcing such security constraints is dif cult These dif culties, among others, prompted the development of database systems In what follows, we shall see the concepts and algorithms that enable database systems to solve the problems with le-processing systems In most of this book, we use a bank enterprise as a running example of a typical data-processing application found in a corporation

CHAPTER 11:

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A database system is a collection of interrelated les and a set of programs that allow users to access and modify these les A major purpose of a database system is to provide users with an abstract view of the data That is, the system hides certain details of how the data are stored and maintained

For the system to be usable, it must retrieve data ef ciently The need for ef ciency has led designers to use complex data structures to represent data in the database Since many database-systems users are not computer trained, developers hide the complexity from users through several levels of abstraction, to simplify users interactions with the system: Physical level The lowest level of abstraction describes how the data are actually stored The physical level describes complex low-level data structures in detail Logical level The next-higher level of abstraction describes what data are stored in the database, and what relationships exist among those data The logical level thus describes the entire database in terms of a small number of relatively simple structures Although implementation of the simple structures at the logical level may involve complex physical-level structures, the user of the logical level does not need to be aware of this complexity Database administrators, who must decide what information to keep in the database, use the logical level of abstraction

The McGraw Hill Companies, 2001

If the pole is real and a > 0, the circuit is impulse response stable If the pole is small, then the function will decay slowly with time On the other hand, if the pole is large, h(t) decays rapidly This is illustrated in Fig 14-4, where we show a plot of e 05t (solid line) and e 3t (dashed line) The poles of these two functions are s = 1/2 and s = 3, respectively In the latter case, the pole has a larger magnitude and so the transfer function decays faster Now let s begin to consider more complicated cases The next complication we might imagine with poles are multiple poles of the type s = a, that is H (s) = 1 (s + a)n (144)

Just above the right side of the list of captured and imported files is a button that enables you to rename, delete, or modify the scene detection options for your video files Clicking this button is the same as right-clicking one of the video files (that is, both actions display exactly the same pop-up menu) I m sure that you can understand the first two options rename and delete without any extra help But the third item Scene detect options might need a bit of explanation When you click this item, the Options dialog box shown here appears:

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