Query Optimization Scheme using Query Classification in Hybrid Spatial DBMS
نویسندگان
چکیده
منابع مشابه
Relational Databases Query Optimization using Hybrid Evolutionary Algorithm
Optimizing the database queries is one of hard research problems. Exhaustive search techniques like dynamic programming is suitable for queries with a few relations, but by increasing the number of relations in query, much use of memory and processing is needed, and the use of these methods is not suitable, so we have to use random and evolutionary methods. The use of evolutionary methods, beca...
متن کاملQuery Optimization in a Heterogeneous DBMS
We propose a query optimization strategy for heterogeneous DBMSs that extends the traditional optimizer strategy widely used in commercial DBMSs to allow execution of queries over both known (i.e., proprietary) DBMSs and foreign vendor DBMSs that conform to some standard such as providing the usual relational database statistics. We assume that participating DBMSs are autonomous and may not be ...
متن کاملrelational databases query optimization using hybrid evolutionary algorithm
optimizing the database queries is one of hard research problems. exhaustive search techniques like dynamic programming is suitable for queries with a few relations, but by increasing the number of relations in query, much use of memory and processing is needed, and the use of these methods is not suitable, so we have to use random and evolutionary methods. the use of evolutionary methods, beca...
متن کاملMultiple-Site Distributed Spatial Query Optimization Using Spatial Semijoins
In this paper, we present our strategy for distributed spatial query optimization that involves multiple sites. Previous work in the area of distributed spatial query processing and optimization focuses only on strategies for performing spatial joins and spatial semijoins, and distributed spatial queries that only involve two sites. We propose a strategy for optimizing a distributed spatial que...
متن کاملQuery classification using Wikipedia
Identifying the intended topic that underlies a user’s query can benefit a large range of applications, from search engines to question-answering systems. However, query classification remains a difficult challenge due to the variety of queries a user can ask, the wide range of topics users can ask about, and the limited amount of information that can be mined from the query. In this paper, we ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Journal of the Korea Contents Association
سال: 2008
ISSN: 1598-4877
DOI: 10.5392/jkca.2008.8.1.290