Data Abstraction

For the system to be usable, it must retrieve data efficiently. The need for efficiency has led designers to use complex data structures to represent data in the database. Since many database-system users are not computer trained, developers hide the complexity from users through several levels of abstraction, to simplify users’ interactions with the system:

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Physical level

.The lowest level of abstraction describes how the data are actually stored. The physical level describes complex low-level data structures in detail.

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Logical level

. The next-higher level of abstraction describes what data are stored in the database, and what relationships exist among those data. The logical level thus describes the entire database in terms of a small number of relatively simple structures. Although implementation of the simple structures at the logical level may involve complex physical-level structures, the user of the logical level does not need to be aware of this complexity. This is referred to asphysical data independence. Database administrators, who must decide what information to keep in the database, use the logical levelof abstraction.

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View level

. The highest level of abstraction describes only part of the entire database. Even though the logical level uses simpler structures, complexity remains because of the variety of information stored in a large database. Many users of the database system do not need all this information; instead, they need to access only a part of the database. The view level of abstraction exists to simplify their interaction with the system. The system may provide many views for the same database.

This typical file-processing system is supported by a conventional operating system. The system stores permanent records in various files, and it needs different application programs to extract records from, and add records to, the appropriate files. Before database management systems (DBMSs) were introduced, organizations usually stored information in such systems.

 

data redundancy and inconsistency 数据的冗余和不一致

difficulty in accessing data 数据访问困难

data isolation 数据孤立

integrity problem 完整性问题

atomicity problem 原子性问题

concurrent-access anomaly 并发访问异常