Efficient Algorithm for Multi Query Optimization
TL;DR: A multi query shareability algorithm which can efficiently detect the common sub-expressions among the multiple queries and share the output among the queries was proposed and algorithm for optimal order of those queries was also proposed.
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Abstract: Multi Query Optimization is an important process in database and it becomes the commonplace due to the frequent usage of decision support systems in almost all the multinational enterprises. The multiple queries from different users that have been addressed to one schema often have a lot of common sub-expressions and it is the function of the multi query optimization algorithms such as Basic Volcano, Volcano RU and Volcano SH algorithms to optimize such multiple queries together and executes the common operation once and share the output among the queries. In this work, a multi query shareability algorithm which can efficiently detect the common sub-expressions among the multiple queries and share the output among those queries was proposed and algorithm for optimal order of those queries was also proposed. The Algorithm has a time complexity of O(n 2 + 9n +6) while the most recent basic algorithm thus Volcano RU Algorithm has O(2n 2 +20n +12), both the algorithms have O(n 2 ) time complexity which is quadratic in nature. However, the Proposed Algorithm is more efficient and better than Volcano RU algorithm even if n approach to infinity.
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Citations
An Improved C4.5 Algorithm Using L’ Hospital Rule for Large Dataset
TL;DR: In this paper, the improved C4.5 algorithm has the best running time of O(n) compared to the traditional C4.5 algorithm which has O( n(log 2 n)2 ).
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An Improved C4.5 Algorithm using Principle of Equivalent of Infinitesimal and Arithmetic Mean Best Selection Attribute for Large Dataset
L. J. Muhammad,Muhammed Besiru Jibrin,B. Z. Yahaya,I.A. Mohammed Besiru Jibrin,Abdulkadir Ahmad,Jamila Musa Amshi +5 more
- 29 Oct 2020
TL;DR: In this article, the authors proposed a new C4.5 data mining algorithm with a lesser time complexity for large dataset compared with traditional C.45 algorithm, but however for smaller dataset traditional C 4.5 algorithm has less time complexity, the new algorithm was improved using Principle of Equivalent of Infinitesimal and Arithmetic Mean Best Selection Attribute.
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Multi Query Optimization Algorithm Using Semantic and Heuristic Approaches
TL;DR: The result of experiment showed that, Proposed Algorithm gave the best plans compared Volcano RU Algorithm, across all three queries and was best for all queries in terms of execution time and CPU time.
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References
Using common subexpressions to optimize multiple queries
J. Park,Arie Segev +1 more
- 01 Feb 1988
TL;DR: A dynamic programming algorithm is presented for the selection of individual access plans such that the resulting global access plan is of minimum processing cost.
Analysis of common subexpression exploitation models in multiple-query processing
J.R. Alsabbagh,Vijay V. Raghavan +1 more
- 14 Feb 1994
TL;DR: This paper compares, empirically and analytically, the performance of the various query execution models that are implied by different approaches to query rewriting.
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Query Optimization (in Relational Databases).
Thomas Neumann
- 01 Jan 2018
TL;DR: This dissertation proposes how to efficiently establish the extent of inter-query shareability and exploit it so as to compute common sub-expressions once and share the output among the queries and proposes the optimal order of optimization so that the sharing is done in a more cost saving and time conserving manner.
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On Multi Query Optimization Algorithms Problem
TL;DR: The basic multi query optimization algorithms including Basic Volcano, Volcano-SH and Volcano RU are studied, their strengths and weaknesses are identified, and strategies for developing new improved multi query optimize algorithm are recommended so as to reduce weaknesses and integrate strengths of the differentbasic multi query algorithms into one efficient algorithm.
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