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customer-name Adams Hayes Figure 316 Result of customer -name ( borrower loan-number = loanloan-number ( branch-name = Perryridge (borrower loan))) this Given a relational-algebra expression E, the expression x (E) returns the result of expression E under the name x A relation r by itself is considered a (trivial) relational-algebra expression Thus, we can also apply the rename operation to a relation r to get the same relation under a new name A second form of the rename operation is as follows Assume that a relationalalgebra expression E has arity n Then, the expression x(A1 ,A2 ,,An ) (E) returns the result of expression E under the name x, and with the attributes renamed to A1 , A2 , , An To illustrate renaming a relation, we consider the query Find the largest account balance in the bank Our strategy is to (1) compute rst a temporary relation consisting of those balances that are not the largest and (2) take the set difference between the relation balance (account) and the temporary relation just computed, to obtain the result Step 1: To compute the temporary relation, we need to compare the values of all account balances We do this comparison by computing the Cartesian product account account and forming a selection to compare the value of any two balances appearing in one tuple First, we need to devise a mechanism to distinguish between the two balance attributes We shall use the rename operation to rename one reference to the account relation; thus we can reference the relation twice without ambiguity

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balance 500 400 700 750 350 Figure 317 Result of the subexpression accountbalance ( accountbalance < dbalance (account d (account)))

reach the desired ending point, then drag the red scissors slider all the way to the left until it won t move further

The McGraw Hill Companies, 2001

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Given an electric circuit we can calculate its response to a unit impulse input (t) This type of excitation serves to characterize the circuit itself and can be used to determine the response of the circuit to any general type of excitation As a result the response of the circuit to the unit impulse is sometimes called the natural response or unit impulse response We denote the output by h(t) This is shown schematically in Fig 13-4 We call the Laplace transform of the natural response the network function H (s) Once the network function for a given circuit is known, we can calculate the response of the circuit to any input by using the convolution theorem Let e(t) represent an arbitrary excitation of the circuit Then the response is found by using convolution r (t) =

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after a crash, these data must be restored Therefore, it is necessary to log not only changes to the database, but also changes to internal system data pertaining to longduration transactions Logging of updates is made more complex when certain types of data items exist in the database A data item may be a CAD design, text of a document, or another form of composite design Such data items are physically large Thus, storing both the old and new values of the data item in a log record is undesirable There are two approaches to reducing the overhead of ensuring the recoverability of large data items: Operation logging Only the operation performed on the data item and the data-item name are stored in the log Operation logging is also called logical logging For each operation, an inverse operation must exist We perform undo using the inverse operation, and redo using the operation itself Recovery through operation logging is more dif cult, since redo and undo are not idempotent Further, using logical logging for an operation that updates multiple pages is greatly complicated by the fact that some, but not all, of the updated pages may have been written to the disk, so it is hard to apply either the redo or the undo of the operation on the disk image during recovery Using physical redo logging and logical undo logging, as described in Section 179, provides the concurrency bene ts of logical logging while avoiding the above pitfalls Logging and shadow paging Logging is used for modi cations to small data items, but large data items are made recoverable via a shadow-page technique (see Section 175) When we use shadowing, only those pages that are actually modi ed need to be stored in duplicate Regardless of the technique used, the complexities introduced by long-duration transactions and large data items complicate the recovery process Thus, it is desirable to allow certain noncritical data to be exempt from logging, and to rely instead on of ine backups and human intervention.

Recall from Section 198 that a multidatabase system creates the illusion of logical database integration, in a heterogeneous database system where the local database systems may employ different logical data models and data-de nition and datamanipulation languages, and may differ in their concurrency-control and transaction-management mechanisms A multidatabase system supports two types of transactions: 1 Local transactions These transactions are executed by each local database system outside of the multidatabase system s control 2 Global transactions These transactions are executed under the multidatabase system s control

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