Database Reference
In-Depth Information
Chapter 7
View Selection and
Materialization
Zohra Bellahsene
LIRMM-CNRS/Université Montpellier 2, France
ABSTRACT
There are many motivations for investigating the view selection problem. At first, materialized views are
increasingly being supported by commercial database systems and are used to speed up query response
time. Therefore, the problem of choosing an appropriate set of views to materialize in the database is
crucial in order to improve query processing cost. Another application of the view selection issue is select-
ing views to materialize in data warehousing systems to answer decision support queries. The problem
addressed in this paper is similar to that of deciding which views to materialize in data warehousing.
However, most existing view selection methods are static. Moreover, none of these methods have con-
sidered the problem of de-materializing the already materialized views. Yet it is a very important issue
since the size of storage space is usually restricted. This chapter deals with the problem of dynamic view
selection and with the pending issue of removing materialized views in order to replace less beneficial
views with more beneficial ones. We propose a view selection method for deciding which views to ma-
terialize according to statistic metadata. More precisely, we have designed and implemented our view
selection method, including a polynomial algorithm, to decide which views to materialize.
INTRODUCTION
in advance and stored in a repository. Then, user
queries are addressed directly to the data warehouse
system and processed without needing to access
the data sources. At an abstract level, a data ware-
house can be seen as a set of materialized views.
Furthermore, new applications of the problem of
view selection arise namely in data placement in
Nowadays, materialized views are increasingly be-
ing supported by a variety of commercial DBMS
to speed up query response time. This technique is
also very useful in data warehousing for optimizing
OLAP queries. In such systems, data are extracted
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