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
Multiple query optimization with depth first branch and bound and dynamic query ordering
Date
1993-09-01
Author
Coşar, Ahmet
Lım, Ee Peng
Srıvastava, Jaıdeep
Metadata
Show full item record
Item Usage Stats
174
views
0
downloads
Cite This
In certain database applications such as deductive databases, batch query processing, and recursive query processing etc., a single query can be transformed into a set of closely related database queries. Great benefits can be obtained by executing a group of related queries all together in a single unified multi-plan instead of executing each query separately. In order to achieve this, Multiple Query Optimization (MQO) identifies common task(s) (e.g. common subexpressions, joins, etc.) among a set of query plans and creates a single unified plan (multiplan) which can be executed to obtain the required outputs for all queries at once. In this paper, a new heuristic function (fc), dynamic query ordering heuristics, and Depth-First Branch-and-Bound (DFBB) are defined and experimentally evaluated, and compared with existing methods which use A* and static query ordering. Our experiments show that all three of fc, DFBB, and dynamic query ordering help to improve the performance of our MQO algorithm.
Subject Keywords
Algorithms
,
Data processing
,
Error analysis
,
Function evaluation
,
Graph theory
,
Heuristic methods
URI
http://dl.acm.org/citation.cfm?id=170181
https://hdl.handle.net/11511/82430
Conference Name
Multiple query optimization with depth first branch and bound and dynamic query ordering, CIKM-1993, Amerika Birleşik Devletleri, 1 - 02 Eylül 1993
Collections
Graduate School of Natural and Applied Sciences, Conference / Seminar
Suggestions
OpenMETU
Core
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...
Distributed database design with integer linear programming and evolutionary hybrid algorithms
Tosun, Umut; Coşar, Ahmet; Department of Computer Engineering (2013)
The communication costs of remote access and retrieval of table fragments required in the execution of distributed database queries, are the major factors determining the quality of a distributed database design. Data allocation algorithms try to minimize these costs by dividing database tables into horizontal fragments, then assigning each fragment at or near the database sites they are needed more frequently. In this thesis, we propose efficient optimization algorithms for centralized and distributed data...
Data mining for rule discovery in relatonal databases
Toprak, Serkan; Alpaslan, Ferda Nur; Department of Computer Engineering (2004)
Data is mostly stored in relational databases today. However, most data mining algorithms are not capable of working on data stored in relational databases directly. Instead they require a preprocessing step for transforming relational data into algorithm specified form. Moreover, several data mining algorithms provide solutions for single relations only. Therefore, valuable hidden knowledge involving multiple relations remains undiscovered. In this thesis, an implementation is developed for discovering mul...
Uncertainty in a nested relational database model
Yazıcı, Adnan; Buckles, BP; Petry, FE (1999-07-01)
Some database models have already been developed to deal with complex values but they have constrains that data stored is precise and queries are crisp. However, as many researchers have pointed out, there is a need to present, manipulate, and query complex and uncertain data of various non-traditional database applications such as oceanography, multimedia, meteorology, office automation systems, engineering designs, expert database systems and geographic information systems. In this paper, we present a log...
Handling complex and uncertain information in the ExIFO and NF2 data models
Yazıcı, Adnan; Petry, FE (1999-12-01)
Trends in databases leading to complex objects present opportunities for representing imprecision and uncertainty that were difficult to integrate cohesively in simpler database models. In fact, one can begin at the conceptual level with a model that allows uncertainty assumptions and then transform those assumptions into a logical model having the necessary semantic foundations upon which to base a meaningful query language. Here we provide such a constructive approach beginning with the ExIFO model for ex...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
A. Coşar, E. P. Lım, and J. Srıvastava, “Multiple query optimization with depth first branch and bound and dynamic query ordering,” presented at the Multiple query optimization with depth first branch and bound and dynamic query ordering, CIKM-1993, Amerika Birleşik Devletleri, 1 - 02 Eylül 1993, Washington, DC, USA, 1993, Accessed: 00, 2021. [Online]. Available: http://dl.acm.org/citation.cfm?id=170181.