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easier way to maintain summary data Designers also used triggers extensively for replicating databases; they used triggers on insert/delete/update of each relation to record the changes in relations called change or delta relations A separate process copied over the changes to the replica (copy) of the database, and the system executed the changes on the replica Modern database systems, however, provide built-in facilities for database replication, making triggers unnecessary for replication in most cases In fact, many trigger applications, including our example overdraft trigger, can be substituted by encapsulation features being introduced in SQL:1999 Encapsulation can be used to ensure that updates to the balance attribute of account are done only through a special procedure That procedure would in turn check for negative balance, and carry out the actions of the overdraft trigger Encapsulations can replace the reorder trigger in a similar manner Triggers should be written with great care, since a trigger error detected at run time causes the failure of the insert/delete/update statement that set off the trigger Furthermore, the action of one trigger can set off another trigger In the worst case, this could even lead to an in nite chain of triggering For example, suppose an insert trigger on a relation has an action that causes another (new) insert on the same relation The insert action then triggers yet another insert action, and so on ad in nitum Database systems typically limit the length of such chains of triggers (for example to 16 or 32), and consider longer chains of triggering an error Triggers are occasionally called rules, or active rules, but should not be confused with Datalog rules (see Section 52), which are really view de nitions

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In this example, the e0/1 interface is activated, and two VLANs are associated with the physical interface in the system area A context, called CTX1, is created that includes these two interfaces (with mapped names), and the configuration file for the context is located in the appliance flash memory

The McGraw Hill Companies, 2001

Use the show context command to verify your context configuration in the system area:

.

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Sorting of data plays an important role in database systems for two reasons First, SQL queries can specify that the output be sorted Second, and equally important for query processing, several of the relational operations, such as joins, can be implemented ef ciently if the input relations are rst sorted Thus, we discuss sorting here before discussing the join operation in Section 135 We can sort a relation by building an index on the sort key, and then using that index to read the relation in sorted order However, such a process orders the relation only logically, through an index, rather than physically Hence, the reading of tuples in the sorted order may lead to a disk access for each record, which can be very expensive, since the number of records can be much larger than the number of blocks For this reason, it may be desirable to order the records physically The problem of sorting has been studied extensively, both for relations that t entirely in main memory, and for relations that are bigger than memory In the rst case, standard sorting techniques such as quick-sort can be used Here, we discuss how to handle the second case Sorting of relations that do not t in memory is called external sorting The most commonly used technique for external sorting is the external sort merge algorithm We describe the external sort merge algorithm next Let M denote the number of page frames in the main-memory buffer (the number of disk blocks whose contents can be buffered in main memory) 1 In the rst stage, a number of sorted runs are created; each run is sorted, but contains only some of the records of the relation i = 0; repeat read M blocks of the relation, or the rest of the relation, whichever is smaller; sort the in-memory part of the relation; write the sorted data to run le Ri ; i = i + 1; until the end of the relation 2 In the second stage, the runs are merged Suppose, for now, that the total number of runs, N, is less than M, so that we can allocate one page frame to each run and have space left to hold one page of output The merge stage operates as follows: read one block of each of the N les Ri into a buffer page in memory; repeat choose the rst tuple (in sort order) among all buffer pages; write the tuple to the output, and delete it from the buffer page; if the buffer page of any run Ri is empty and not end-of- le(Ri ) then read the next block of Ri into the buffer page; until all buffer pages are empty.

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ciscoasa# show context [name | detail | count]

The McGraw Hill Companies, 2001

Here s an example of the use of this command:

Discrete: Discrete performance/payment periods stand alone for measurement and payment purpose For example, a sales compensation plan that pays monthly discrete treats each month as a standalone measurement and payment period No previous or future month s performance will affect the payout for an individual month Use less than annual discrete measurement periods when sales cycles are short and sales personnel have no flexibility or selfserving motivation to move orders from one period to another

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ciscoasa# show context Context Name Interfaces *admin Ethernet0/0 Ethernet0/1 CTX1 Ethernet0/2 Ethernet0/3 Total active Security Contexts: 2 URL disk0:/admincfg disk0:/CTX1cfg

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An * beside a context name indicates that the context is the administrative context In the preceding example, this is the admin context

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