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外文原文

Management Center of MySQL

Authors: Lauderdale, John Tsang, Danny H. K. Baciu, George

Issue Date: 2006

Citation: Proceedings of IEEE Visual '96, Melbourne, Australia, February 2006, p. 447-458

Database (sometimes spelled database) is also called an electronic database, referring to any collections of data, or information, that is specially organized for rapid search and retrieval by a computer. Databases are structured to facilitate the storage, retrieval, modification and deletion of data in conjunction with various data-processing operations. Database can be stored on magnetic disk or tape, optical disk, or some other secondary storage device.

A database consists of a file or a set of files. The information in the these files may be broken down into records, each of which consists of one or more fields are the basic units of data storage, and each field typically contains information pertaining to one aspect or attribute of the entity described by the database. Using keywords and various sorting commands, users can rapidly search, rearrange, group, and select the fields in many records to retrieve or create reports on particular aggregates of data.

Database records and files must be organized to allow retrieval of the information. Early system were arranged sequentially (i.e., alphabetically, numerically, or chronologically); the development of direct-access storage devices made possible random access to data via indexes. Queries are the main way users retrieve database information. Typically the user provides a string of characters, and the computer searches the database for a corresponding sequence and provides the source materials in which those characters appear. A user can request, for example, all records in which the content of the field for a person’s last name is the word Smith.

In flat databases, records are organized according to a simple list of entities; many simple databases for personal computers are flat in structure. The records in hierarchical databases are organized in a treelike structure, with each level of records branching off into a set of smaller categories. Unlike hierarchical databases, which provide single links between sets of records at different levels, network databases create multiple linkages between sets by placing links, or pointers, to one set of records in another; the speed and versatility of network databases have led to their wide use in business. Relational databases are used where

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associations among files or records cannot be expressed by links; a simple flat list becomes one table, or “relation”, and multiple relations can be mathematically associated to yield desired information. Object-oriented databases store and manipulate more complex data structures, called “objects”, which are organized into hierarchical classes that may inherit properties from classes higher in the chain; this database structure is the most flexible and adaptable.

The information in many databases consists of natural-language texts of documents; Small databases can be used by individuals at home. These and larger databases have become increasingly important in business life. Typical commercial applications include airline reservations, production management, medical records in hospitals, and legal records of insurance companies. The largest databases are usually maintained by governmental agencies, business organizations, and universities. These databases may contain texts of such materials as catalogs of various kinds. Reference databases contain bibliographies or indexes that serve as guides to the location of information in books, periodicals, and other published literature. Thousands of these publicly accessible databases now exist, covering topics ranging from law, medicine, and engineering to news and current events, games, classified advertisements, and instructional courses. Professionals such as scientists, doctors, lawyers, financial analysts, stockbrokers, and researchers of all types increasingly rely on these databases for quick, selective access to large volumes of information. DBMS Structuring Techniques

Sequential, direct, and other file processing approaches are used to organize and structure data in single files. But a DBMS is able to integrate data elements from several files to answer specific user inquiries for information. That is, 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 then employ one of the following logical structuring techniques during storage, access, and retrieval operations.

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 each record in this file is identified by an account number. During an accounting period, a customer may buy a number of items on different days. Thus, the company 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 record in the

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customer in the invoice file includes a field, it pointed to the location of the first invoice record in invoice file, this invoice record, in turn, would be linked to next invoices for the customer. The last invoice in the chain would be identified by the use of a special character as a pointer.

Hierarchical (tree) 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 superior-subordinate relationship in a hierarchical (tree) structure. Below the single-root data component are subordinate elements or nodes, in turn, each element or branch in this structure below the root has only a single owner. Thus, a customer owns an invoice, and the invoice has subordinate items. The branches in a tree structure are not connected.

Network Structures. Unlike the tree approach, which does not permit the connection of branches, the network 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.

Relational structures. A relational structure is made up of many tables. The data are stored in the form of “relations” in these tables. This is a relatively new database structuring approach that’s expected to be widely implemented in the future.

Physical Structures. People visualize or structure data in logical ways for their own purposes. Thus, records R1 and R2 may always be logically linked and processed in sequence in one particular application. However, in a computer system it’s quite possible that these records that are logically contiguous in one application are not physically stored together. Rather, the physical structure of the records in media and hardware may depend not only on the I/O and storage devices and storage techniques used, but also on the different logical relationships that users may assign to the data found in R1 and R2. For example, R1 and R2 may be records of credit customers who have shipments send to the same block in the same city every 2 weeks. From the shipping department manager’s perspective, then, R1 and R2 are sequential entries on a geographically organized shipping report. But in the A/R application, the customers represented by R1 and R2 may be identified, and their accounts may be processed, according to their account numbers which are widely separated. In short, then, the physical location of the stored records in many computer-based information systems is invisible to users.

Database Management Features of MySQL

MySQL includes many features that make the database easier to manage. We’ve divided

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