LORE : Query Optimization for Semi-Structured Data

Abstract:

The semi-structured data is becoming more pervasive and prevalent- data
that may be irregular or incomplete or unpredictable. One of the main
example of semi-structured data is XML. With the emergence of XML as a
standard for data representation and exchange on World-Wide Web, it is
more important to develop efficient query processing techniques for such
data. The query processing and cost based optimization for XML will be
presented by using LORE – a DBMS for XML based data supporting an
expressive language. All of the usual problems associated with cost-based
query optimization apply to XML-based query languages, a number of
additional problems arise, such as new kinds of indexing, more complicated
notions of database statistics, and vastly different query execution
strategies for different databases. The presentation will discuss
appropriate logical and physical query plans, database statistics, and a
cost model, and describe plan enumeration including heuristics for
reducing the large search space.