Database Reference
In-Depth Information
for defining the data structures, for manipulating the data, and for maintaining the
data. Structured Query Language (SQL) has evolved as the standard to fulfill these
needs.
Implementation includes tasks required to move from an earlier data system
to the new database system. Existing data from the current system have to be con-
verted over to the new system. Furthermore, you need applications in the new envi-
ronment that will tap into the new database system. Also, you need a proper strategy
to deploy the database and distribute the data wherever they are needed.
Implementation considerations include the optimal processing of data queries.
Data retrieval involves execution of queries in the most optimal way. Our discus-
sion of implementation considerations will not be complete without an examination
of query processing.
IMPLEMENTATION LANGUAGES
You carry out the implementation of a database system through languages. You
know that language is a medium for communication and serves as a link. Just think
about programming languages. Programming languages enable user transactions
to be communicated to the computer systems. They therefore contain structures to
indicate the logic, components to denote the data requirements, and methods to
organize the flow of control.
Database implementation languages also serve to interpret and communicate
database transactions to the DBMS and to the database system. In practice, because
they support distinct functions, database implementation languages must have dis-
tinct features specially intended for the required functions. Several implementation
languages have evolved for the relational data model; however, SQL has become
the accepted standard.
Even though the name of the language implies that SQL is intended just for
queries, the language has all the components to support the various aspects of imple-
mentation. In the following sections of this chapter, you will observe the distinct
features of SQL and understand how it is a complete language for implementation
of the relational data model.
Meaning of Model Implementation
At the outset, let us describe what we mean by implementing a data model as a
database system. Consider a relational data model. The logical data model consists
of relations or tables, tuples or rows indicating individual entities, columns showing
the attributes, primary keys, and foreign keys. In the physical data model you find
these components transformed into files, blocks, records, indexes, and constraints.
So what do we mean by implementing the data model?
Implementation serves two primary purposes—storage of data and usage of data.
As you know, these are the two basic aspects of a database system. Users need
to access and use data; you need to store the data in a database for this purpose.
A data model represents the information requirements for an organization. When
you implement a data model, you make provisions to store the information content
represented by the data model and also enable the stored information to be used.
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