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About 9,411 papers for “Query optimization”
Saeed K. Rahimi, Frank S. Haug · 2010
This chapter contains sections titled: Sample Database Relational Algebra Computing Relational Algebra Operators Query Processing in Centralized Systems Query Processing in Distributed Systems Summary Glossary References Exercises
Cited by 1
2004
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Nicolas Bruno · 2014
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Minjie Chen, Mantao Xu, Pasi Fränti · 2005
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Yuning Chen, Jin-kao Hao, Yuning Chen et al. · 2005
Abstract The quadratic multiple knapsack problem (QMKP) consists in as-signing objects with both individual and pairwise profits to a set of limited knapsacks in order to maximize the total profit. QMKP is a NP-hard com-binatorial optimization problem with a number of applications. In this pa-per, we present an iterated responsive threshold search (IRTS) approach for solving the QMKP. Based on a combined use of three neighborhoods, the algorithm alternates between a threshold-based exploration phase where so-lution transitions are allowed among those satisfying a responsive threshold and a descent-based improvement phase where only improving solutions are accepted. A dedicated perturbation strategy is utilized to ensure a global di-versification of the search procedure. Extensive experiments performed on a set of 60 benchmark instances in the literature show that the proposed ap-proach competes very favorably with the current state-of-the-art methods for the QMKP. In particular, it discovers 41 improved lower bounds and attains all the best known results for the remaining instances. The key components of IRTS are analyzed to shed light on their impact on the performance of the algorithm.
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2008
Large-scale distributed environments, where each node is completely autonomous and offers services to its peers through external communication, pose significant challenges to query processing and optimization. Autonomy is the main source of the problem, as it results in lack of knowledge about any particular node with respect to the information it can produce and its characteristics, e.g., cost of production or quality of produced results. Inter-node competition is another source of the problem, as it results in potentially inconsistent behavior of the nodes at different times. In this paper, inspired by e-commerce technology, we recognize queries (and query answers) as commodities and model query optimization as a trading negotiation process. Query parts (and their answers) are traded between nodes until deals are struck with some nodes for all of them. We identify the key parameters of this framework and suggest several potential alternatives for each one. In comparison to trading negotiations for e-commerce, query optimization faces unique new challenges that stem primarily from the complex structure of queries. We address these challenges through a particular instantiation of our framework focusing on the negotiation strategy, the contents of the negotiation messages, the evaluation metrics of the queries, and the optimization algorithm run on a “buying ” node. Finally, we conclude with some experiments that demonstrate the scalability and performance characteristics of our approach compared to those of traditional query optimization. 1
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Timos Sellis · ACM SIGMOD Record · 1986
In some recently proposed extensions to relational database systems as well as in deductive databases, a database system is presented with a collection of queries to process instead of just one. It is an interesting problem then, to come up with algorithms that process these queries together instead of one query at a time. We examine the problem of multiple (global) query optimization in this paper. A hierarchy of algorithms that can be used for global query optimization is exhibited and analyzed. These algorithms range from an arbitrary serial execution without any sharing of common results among the queries to an exhaustive search of all possible ways to process all queries.
Cited by 71Open access
University Research Chair · Encyclopedia of Database Systems · 2009
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Hans Zeller, Goetz Graefe · Encyclopedia of Database Systems · 2018
Cited by 1
Cem Evrendilek, Asuman Dogac, Sena Nural et al. · OpenMETU (Middle East Technical University) · 1997
. A multidatabase system (MDBS) allows the users to simultaneously access heterogeneous, and autonomous databases using an integrated schema and a single global query language. The query optimization problem in MDBSs is quite different from the query optimization problem in distributed homogeneous databases due to schema heterogeneity and autonomy of local database systems. In this work, we consider the optimization of query distribution in case of data replication and the optimization of intersite joins, that is, the join of the results returned by the local sites in response to the global subqueries. The algorithms presented for the optimization of intersite joins try to maximize the parallelism in execution and take the federated nature of the problem into account. It has also been shown through a comparative performance study that the proposed intersite join optimization algorithms are efficient. The approach presented can easily be generalized to any operation required for intersi...
Cited by 0Open access
한욱신, 곽우성, 이진수 et al. · Open Access System for Information Sharing (Pohang University of Science and Technology) · 2018
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CHEN DING · National University of Singapore · 2009
Ph.D
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Yannis Manolopoulos, Αλέξανδρος Νανόπουλος, Apostolos N. Papadopoulos et al. · Advanced information and knowledge processing · 2006
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SpringerReference · 2011
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Choenni, Sunil, Kersten, Martin, Akker, Johan et al. · SpringerReference · 2011
Cited by 4Open access
Benabderrezak, Youcef · 2025
Cited by 0Open access
Min-rong Chen, Yong-zai Lu, Qi Luo · 1992
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Timos Sellis · 1986
In some recently proposed extensions to relational database systems as well as in deductive databases, a database system is presented with a collection of queries to process instead of just one. It is an interesting problem then, to come up with algorithms that process these queries together instead of one query at a time. We examine the problem of multiple (global) query optimization in this paper. A hierarchy of algorithms that can be used for global query optimization is exhibited and analyzed. These algorithms range from an arbitrary serial execution without any sharing of common results among the queries to an exhaustive search of all possible ways to process all queries.
Cited by 36
Stocker, Markus, Kannengießer, Annika, , Ilyas et al. · Open Research Knowledge Graph (ORKG) · 2022
Compares the performance of various algorithms evaluated using the LUBM benchmark.
Cited by 0Open access
Henrietta Dombrovskaya, Boris Novikov, Anna Bailliekova · Apress eBooks · 2024
This book helps you write efficient queries and also optimize existing queries to perform fast and deliver results on time.
Cited by 1Open access