Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Using object-oriented materialized views to answer selection-based complex queries
Date
1999-09-01
Author
Alhajj, R
Polat, Faruk
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
249
views
0
downloads
Cite This
Presented in this paper is a model that utilizes existing materialized views to handle a wide range of complex selection-based queries, including linear recursive queries. Such queries are complex because it is almost impossible for naive users to predict the formulation of their predicate expressions. Object variables bound to objects in the result of a query are allowed to appear in the predicate of that query. Also, the predicate definition is extended to make it possible to have in the output only a subset of the objects from the actual result of a linear recursive query. We introduce an algorithm that utilizes existing materialized views in answering queries covered by the presented model. The presented model has been implemented as a part of our object-oriented database management system prototype. (C) 1999 Elsevier Science Inc. All rights reserved.
Subject Keywords
Complex queries
,
Materialized views
,
Object-oriented databases
,
Query answer
,
Query model
,
Recursive queries
URI
https://hdl.handle.net/11511/47850
Journal
INFORMATION SCIENCES
DOI
https://doi.org/10.1016/s0020-0255(99)00023-7
Collections
Department of Computer Engineering, Article
Suggestions
OpenMETU
Core
Improving the performance of Hadoop/Hive by sharing scan and computation tasks
Özal, Serkan; Toroslu, İsmail Hakkı; Doğaç, Asuman; Department of Computer Engineering (2013)
MapReduce is a popular model of executing time-consuming analytical queries as a batch of tasks on large scale data. During simultaneous execution of multiple queries, many oppor- tunities can arise for sharing scan and/or computation tasks. Executing common tasks only once can reduce the total execution time of all queries remarkably. Therefore, we propose to use Multiple Query Optimization (MQO) techniques to improve the overall performance of Hadoop Hive, an open source SQL-based distributed warehouse sy...
IMOTION Searching for Video Sequences using Multi Shot Sketch Queries
Rossetto, Luca; Giangreco, Ivan; Heller, Silvan; Tanase, Claudiu; Schuldt, Heiko; Seddati, Omar; Dupont, Stephane; Sezgin, Tevfik Metin; Altıok, Ozan; Sahillioğlu, Yusuf (null; 2016-02-10)
This paper presents the second version of the IMOTION system, a sketch-based video retrieval engine supporting multiple query paradigms. Ever since, IMOTION has supported the search for video sequences on the basis of still images, user-provided sketches, or the specification of motion via flow fields. For the second version, the functionality and the usability of the system have been improved. It now supports multiple input images (such as sketches or still frames) per query, as well as the specification o...
Integer Linear Programming Solution for the Multiple Query Optimization Problem
Dokeroglu, Tansel; Bayir, Murat Ali; Coşar, Ahmet (2014-10-28)
Multiple Query Optimization (MQO) is a technique for processing a batch of queries in such a way that shared tasks in these queries are executed only once, resulting in significant savings in the total evaluation. The first phase of MQO requires producing alternative query execution plans so that the shared tasks between queries are identified and maximized. The second phase of MQO is an optimization problem where the goal is selecting exactly one of the alternative plans for each query to minimize the tota...
Dynamic Programming with Ant Colony Optimization Metaheuristic for Optimization of Distributed Database Queries
Dokeroglu, Tansel; Coşar, Ahmet (2011-09-28)
In this paper, we introduce and evaluate a new query optimization algorithm based on Dynamic Programming (DP) and Ant Colony Optimization (ACO) metaheuristic for distributed database queries. DP algorithm is widely used for relational query optimization, however its memory, and time requirements are very large for the query optimization problem in a distributed database environment which is an NP-hard combinatorial problem. Our aim is to combine the power of DP with heuristic approaches so that we can have ...
A Cost-Aware Strategy for Query Result Caching in Web Search Engines
Altıngövde, İsmail Sengör; Ulusoy, Oezguer (2009-01-01)
Search engines and large scale IR systems need to cache query results for efficiency and scalability purposes. In this study, we propose to explicitly incorporate the query costs in the static caching policy. To this end, a query’s cost is represented by its execution time, which involves CPU time to decompress the postings and compute the query-document similarities to obtain the final top-N answers. Simulation results using a large Web crawl data and a real query log reveal that the proposed strategy impr...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
R. Alhajj and F. Polat, “Using object-oriented materialized views to answer selection-based complex queries,”
INFORMATION SCIENCES
, pp. 75–99, 1999, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/47850.
