《数据库系统概念》第一章Review Terms术语解释

Review Terms

• Database system(DBS): A collection of interrelated data and a set of programs to access those data.
• Database-system applications: A database application is a computer program whose primary purpose is entering and retrieving information from a computerized database.
• File-processing systems: In computing, a file system or file-processing system controls how data is stored and retrieved.
• Data inconsistency: Data inconsistency is a condition that occurs between files when similar data is kept in different formats in two different files, or when matching of data must be done between files.
• Consistency constrains: Consistency in database systems refers to the requirement that any given database transaction must change affected data only in allowed ways. Any data written to the database must be valid according to all defined rules, including constraints, cascades, triggers, and any combination thereof.
• Data abstraction: Data abstraction enforces a clear separation between the abstract properties of a data type and the concrete details of its implementation.
• Instance: Table instance (or database instance), a concept in database design, refer to a row--also called a tupl--represents a single, implicitly structured data item in a table.
• Schema: The schema of a table is an example of metadata.
• Physical schema: physical schema is a term used in data management to describe how data is to be represented and stored (files, indices) in secondary storage using a particular database management system (DBMS).
• Logical schema: logical schema is a data model of a specific problem domain expressed independently of a particular database management product or storage technology (physical data model) but in terms of data structures such as relational tables and columns, object-oriented classes, or XML tags.
• Physical data independence: The ability to change the physical schema without changing the logical schema is called physical data independence.
• Data models: A database model is a type of data model that determines the logical structure of a database and fundamentally determines in which manner data can be stored, organized, and manipulated.
  • Entity-relationship model: An entity-relationship model (ER model for short) describes interrelated things of interest in a specific domain of knowledge. A basic ER model is composed of entity types (which classify the things of interest) and specifies relationships that can exist between instances of those entity types.
  • Relational data model: The relational model (RM) for database management is an approach to managing data using a structure and language consistent with first-order predicate logic, first described in 1969 by Edgar F. Codd, where all data is represented in terms of tuples, grouped into relations. A database organized in terms of the relational model is a relational database.
  • Object-based data model: An object database is a database management system in which information is represented in the form of objects as used in object-oriented programming. Object databases are different from relational databases which are table-oriented. Object-relational databases are a hybrid of both approaches.
  • Semi-structured data model: Semi-structured data model is a form of structured data that does not conform with the formal structure of data models associated with relational databases or other forms of data tables, but nonetheless contains tags or other markers to separate semantic elements and enforce hierarchies of records and fields within the data.
• Database languages: Database languages are special-purpose languages, which allow one or more of the following tasks, sometimes distinguished as sublanguage.
  • Data-definition language: defines data types such as creating, altering, or dropping and the relationships among them
  • Data-manipulation language: performs tasks such as inserting, updating, or deleting data occurrences
  • Query language: allows searching for information and computing derived information.
• Metadata: Metadata is "data that provides information about other data".
• Application program: Application programs are programs that are used to interact with the database in this fashion.
• Normalization: Database normalization is the process of restructuring a relational database in accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity.
• Data dictionary: A data dictionary, or metadata repository, as defined in the IBM Dictionary of Computing, is a "centralized repository of information about data such as meaning, relationships to other data, origin, usage, and format".
• Storage manager: The storage manager is the component of a database system that provides the interface between the low-level data stored in the database and the application programs and queries submitted to the system. The storage manager is responsible for the interaction with the file manager.
• Query processor: The query processor components include: DDL interpreter, which interprets DDL statements and records the definitions in the data dictionary; DML compiler, which translates DML statements in a query language into an evaluation plan consisting of low-level instructions that the query evaluation engine understands and also performs query optimization; Query evaluation engine, which executes low-level instructions generated by the DML compiler.
• Transactions: A transaction symbolizes a unit of work performed within a database management system (or similar system) against a database, and treated in a coherent and reliable way independent of other transactions. A transaction generally represents any change in a database.
  • Atomicity: An atomic transaction is an indivisible and irreducible series of database operations such that either all occur, or nothing occurs.
  • Failure recovery: Failure recovery, that is, detect system failures and restore the database to the state that existed prior to the occurrence of the failure.
  • Concurrency control: Concurrency control is to ensure the consistency of the database when several transactions update the database concurrently.
• Two- and three-tier database architecture: In software engineering, multitier architecture (often referred to as n-tier architecture) or multilayered architecture is a client–server architecture in which presentation, application processing, and data management functions are physically separated. The most widespread use of multitier architecture is the three-tier architecture.
• Data mining: Data mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.
• Database administrator(DBA): Database administrators (DBAs) use specialized software to store and organize data. The role may include capacity planning, installation, configuration, database design, migration, performance monitoring, security, troubleshooting, as well as backup and data recovery.