數(shù)據(jù)庫管理系統(tǒng)外文翻譯-管理系統(tǒng)-展示頁
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【正文】 n response to the queries of those who aren’t programmers. In a fileoriented system, users needing special information may municate their needs to a programmers, who, when time permits, will information. The availability of a DBMS, however, offers users a much faster alternative munications patch (see figure). Special, direct, and other file processing approaches ate used to anize and structure data in single files. But a DBMS is able to integrate data elements from several files to answer specific user inquiries fir information. This means that the DBMS is able to structure and tie together the logically related data from several large files. Logical structures. Identifying these logical relationships is a job of the data administrator. A data definition language is used for this purpose. The DBMS may 大連交通大學 2021 屆本科生畢業(yè)設(shè)計 (論文 )外文文獻翻譯 2 then Employ one of the following logical structuring techniques during storage access, and retrieval operation: list structures, hierarchical (tree) structures, and work structures, relational structures. 1. List structures. In this logical approach, records are linked together by the use of pointers. A pointer is a data item in one record that identifies the storage location of another logically related record. Records in a customer master file, for example, will contain the name and address of each customer, and an account number identi fies each record in this file. During an accounting period, a customer may maintain an invoice file to reflect these transactions. A list structure could be used in this situation to show the unpaid invoices at any given time. Each in the customer file would point to the record location of the first invoice for that customer in the invoice file. This invoice record, in turn would be linked to later invoice for the customer. The last invoice in the chain would be identified by the use of a special character as a pointer. 2. Hierarchical structures. In this logical approach, data units are structured in multiple levels that graphically resemble an “upside down” tree with the root at the top and the branches formed below, there’s a superiorsubordinate relationship in a hierarchical structure. Below the singleroot data ponent are subordinate elements (or one) has only a single owner. Thus, as we see in figure, a customer owns an invoice, and the invoice has subordinate items. The branches in a tree structure are not connected. 3. Network structures. Unlike the tree approach, which dose not permit the connection of branches, the work structure permits the connection of the nodes in a multidirectional manner. Thus, each node may have several owners and may, in turn, own any number of other data units. Data, management software permits the extraction of the needed information from such a structure by beginning with any record in a file. 4. Relational structures. A relational structure is made up of many tables. The data are stored in the form of “relations” in these tables. For example, relation tables could be established to link a college course with the instructor of the course, and with the location of the in order to find the name of the instructor and the location of the English class, the course/instructor relation is searched to get the name, and the course/location relation is searched to get the class location. Many other relations are of course, possible. This is a relatively new database structuring ap
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