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2025-02-03 11:34本頁面
【正文】 store the data themselves in the database. Forth. Mobility and Personal Databases Largescale mercial databases have traditionally been stored in central puting facilities. In the case of distributed database applications, there has usually been strong central database and work administration. Two technology trends have bined to create applications in which this assumption of central control and administration is not entirely correct: increasingly widespread use of personal puters, and, more important, of laptop or “notebook” puters. development of a relatively lowcost wireless digital munication infrastructure, base on wireless localarea works, cellular digital packet works, and other technologies. Wireless puting creates a situation where machines no longer have fixed locations and work addresses. This plicates query processing, since it bees difficult to determine the optimal location at which to materialize the result of a query. In some cases, the location of the user is a parameter of the query. A example is a traveler’s information system that provides data on hotels, roadside services, and the like to motorists. Queries about services that are ahead on the current route must be processed based on knowledge of the user’s location, direction of motion, and speed. Energy (battery power) is a scarce resource for mobile puters. This limitation influences many aspects of system design. Among the more interesting consequences of the need for energy efficiency is the use of scheduled data broadcasts to reduce the need for mobile system to transmit queries. Increasingly amounts of data may reside on machines administered by users, rather than by database administrators. Furthermore, these machines may, at times, be disconnected from the work. Summary Decisionsupport systems are gaining importance, as panies realize the value of the online data collected by their online transactionprocessing systems. Proposed extensions to SQL, such as the cube operation, help to support generation of summary data. Data mining seeks
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