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Relational calculus does not involve the mathematical complexity of relational algebra; it focuses only on what the database is being queried for, rather than how to conduct the query. In other words, it is a declarative language. You focus on the results you expect and the conditions to be satisfied in the process, and you ignore the sequencing of the relational algebra concepts. Relational calculus is based on a part of mathematical logic called propositional calculus or, more precisely, first-order predicate calculus. Relational calculus involves the use of operators such as AND and OR to manipulate relations in logical expressions.
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Relational calculus is far easier to use than relational algebra, but it still is based on the principles of logic and it is not easy for most people to use. You thus need an easy-to-use implementation of relational calculus. Structured Query Language (SQL) is one such implementation, and it has become hugely popular as the predominant language for the relational database model. SQL is considered a relationally complete language, in the sense that it can express any query that is supported by relational calculus. Structured English Query Language (SEQUEL), the precursor of SQL, was developed by IBM to use Codd s relational database model. Oracle introduced the first commercially available implementation of SQL in 1979 (when Oracle was known as Relational Software), and SQL has since become the standard language for RDBMSs, although not all implementations adhere completely to the official standards. Oracle has its own implementation of SQL, which is very close to the American National Standards Institute (ANSI) standard (visit http://www.ansi.org/ for more information). SQL is an English-like language that enables you to manipulate data in a database. Using SQL, you can derive any relation that can be derived using relational calculus. You can formulate queries in easy-to-format structures, which are then processed by sophisticated database servers into complex forms to get the queried data. Its intuitive appeal, ease of use, and tremendous power and sophistication have made SQL the language of choice when working with any relational database. You can divide SQL statements into two major categories: data definition language (DDL) and data manipulation language (DML). DDL statements are used to build and alter database structures, such as tables, and to define and construct database schemas. DML statements are used to manipulate data in the database tables; with DML statements, you can delete, update, and insert tuples that are part of a relation. The Appendix provides a quick introduction to the Oracle Database 11g SQL language as well as to PL/SQL, Oracle s procedural extension to standard SQL that provides the power of traditional programming languages along with SQL s ease of use.
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C HA PTE R 2 RELATIONA L DATABA SE M ODELING A ND DATABA SE DES IGN
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Relational Database Life Cycle
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The essential steps of a typical relational database life cycle are as follows: 1. Requirements gathering and analysis 2. Logical database design 3. Physical database design 4. Production implementation I will examine each of these stages in detail in the rest of this chapter. You could, of course, forget about using any methodology, and just design your database any way you want, create the structures, load the data, and be in business. However, improper database design has serious long-term performance implications, and you risk ending up with an inadequate database or simply with one that is wrong for your company s information and analysis needs. One thing to bear in mind is that databases tend to grow, and the better the database, the bigger it tends to get as more and more users rely on it. In addition, it won t take long for your application developers to begin to expand upon the core data, especially with today s requirements to make as much data as possible available on the Web.
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