Abstract: Distributed database is a collection of logically related databases that cooperate in a transparent manner. Query processing uses a communication network for transmitting data between sites. It refers to one of the challenges in the database world. The development of sophisticated query optimization technology is the reason for the commercial success of database systems, which complexity and cost increase with increasing number of relations in the query. Mariposa, query trading and query trading with processing task-trading strategies developed for autonomous distributed database systems, but they cause high optimization cost because of involvement of all nodes in generating an optimal plan. In this paper, we proposed a modification on the autonomous strategy K-QTPT that make the seller’s nodes with the lowest cost have gradually high priorities to reduce the optimization time. We implement our proposed strategy and present the results and analysis based on those results.
Abstract: Currently, database management systems have various tools such as backup and maintenance, and also provide statistical information such as resource usage and security. In terms of query performance, this paper covers query optimization, views, indexed tables, pre-computation materialized view, query performance analysis in which query plan alternatives can be created and the least costly one selected to optimize a query. Indexes and views can be created for related table columns. The literature review of this study showed that, in the course of time, despite the growing capabilities of the database management system, only database administrators are aware of the need for dealing with archival and transactional data types differently. These data may be constantly changing data used in everyday life, and also may be from the completed questionnaire whose data input was completed. For both types of data, the database uses its capabilities; but as shown in the findings section, instead of repeating similar heavy calculations which are carrying out same results with the same query over a survey results, using materialized view results can be in a more simple way. In this study, this performance difference was observed quantitatively considering the cost of the query.
Abstract: The emergence of the Semantic Web technology
increases day by day due to the rapid growth of multiple web pages.
Many standard formats are available to store the semantic web data.
The most popular format is the Resource Description Framework
(RDF). Querying large RDF graphs becomes a tedious procedure
with a vast increase in the amount of data. The problem of query
optimization becomes an issue in querying large RDF graphs.
Choosing the best query plan reduces the amount of query execution
time. To address this problem, nature inspired algorithms can be used
as an alternative to the traditional query optimization techniques. In
this research, the optimal query plan is generated by the proposed
SAPSO algorithm which is a hybrid of Simulated Annealing (SA)
and Particle Swarm Optimization (PSO) algorithms. The proposed
SAPSO algorithm has the ability to find the local optimistic result
and it avoids the problem of local minimum. Experiments were
performed on different datasets by changing the number of predicates
and the amount of data. The proposed algorithm gives improved
results compared to existing algorithms in terms of query execution
time.
Abstract: Appeared toward 1986, the object-oriented databases
management systems had not known successes knew five years after
their birth. One of the major difficulties is the query optimization.
We propose in this paper a new approach that permits to enrich
techniques of query optimization existing in the object-oriented
databases. Seen success that knew the query optimization in the
relational model, our approach inspires itself of these optimization
techniques and enriched it so that they can support the new concepts
introduced by the object databases.
Abstract: Due to new distributed database applications such as
huge deductive database systems, the search complexity is constantly
increasing and we need better algorithms to speedup traditional
relational database queries. An optimal dynamic programming
method for such high dimensional queries has the big disadvantage of
its exponential order and thus we are interested in semi-optimal but
faster approaches. In this work we present a multi-agent based
mechanism to meet this demand and also compare the result with
some commonly used query optimization algorithms.
Abstract: Semantic query optimization consists in restricting the
search space in order to reduce the set of objects of interest for a
query. This paper presents an indexing method based on UB-trees
and a static analysis of the constraints associated to the views of the
database and to any constraint expressed on attributes. The result of
the static analysis is a partitioning of the object space into disjoint
blocks. Through Space Filling Curve (SFC) techniques, each
fragment (block) of the partition is assigned a unique identifier,
enabling the efficient indexing of fragments by UB-trees. The search
space corresponding to a range query is restricted to a subset of the
blocks of the partition. This approach has been developed in the
context of a KB-DBMS but it can be applied to any relational
system.
Abstract: Fast retrieval of data has been a need of user in any
database application. This paper introduces a buffer based query
optimization technique in which queries are assigned weights
according to their number of execution in a query bank. These
queries and their optimized executed plans are loaded into the buffer
at the start of the database application. For every query the system
searches for a match in the buffer and executes the plan without
creating new plans.
Abstract: Over the past few years, XML (eXtensible Mark-up
Language) has emerged as the standard for information
representation and data exchange over the Internet. This paper
provides a kick-start for new researches venturing in XML databases
field. We survey the storage representation for XML document,
review the XML query processing and optimization techniques with
respect to the particular storage instance. Various optimization
technologies have been developed to solve the query retrieval and
updating problems. Towards the later year, most researchers
proposed hybrid optimization techniques. Hybrid system opens the
possibility of covering each technology-s weakness by its strengths.
This paper reviews the advantages and limitations of optimization
techniques.