Genetic Query Optimization for Large Databases: On the Use of Evolutionary Strategies for Very Large Join Queries - Couverture souple
Synopsis
As the amount of stored data grows, the relational schemas needed to organize all these data get more complex, increasing the number of relations in the database. As a consequence, it becomes necessary to write SQL queries that involve a large number of relations. Once a SQL query is introduced into the DBMS, the query optimizer must find the most efficient query execution plan to solve it. State-of-the-art query optimizers, which typically employ dynamic programming techniques, are limited in the number of joins they can handle. In these situations, optimizers either resort to heuristics or fall back to greedy algorithms. However, greedy algorithms do not consider the entire search space and thus may overlook the optimal plan, resulting in bad query performance. In this book, we present a query optimizer based on genetic programming algorithms. We compare the results yielded by our optimizer with those yielded by the UDB DB2 optimizer, as well as some of the most efficient randomized algorithms proposed in the literature. Our studies show that the larger the number of relations involved in the query, the larger the benefit obtained by this type of optimizers.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
Victor Muntés Mulero is an associate professor at the Universitat Politècnica de Catalunya. He obtained his PhD in 2007. Through his collaboration with the IBM Center for Advanced Studies in Toronto, he designed a query optimizer based on genetic algorithms. He is the author of more than 30 papers and patents related to efficient data management.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Résultats de recherche pour Genetic Query Optimization for Large Databases: On...
Image fournie par le vendeur
Genetic Query Optimization for Large Databases
Edité par
LAP LAMBERT Academic Publishing Jan 2011, 2011
ISBN 10 : 3843391750
ISBN 13 : 9783843391757
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -As the amount of stored data grows, the relational schemas needed to organize all these data get more complex, increasing the number of relations in the database. As a consequence, it becomes necessary to write SQL queries that involve a large number of relations. Once a SQL query is introduced into the DBMS, the query optimizer must find the most efficient query execution plan to solve it. State-of-the-art query optimizers, which typically employ dynamic programming techniques, are limited in the number of joins they can handle. In these situations, optimizers either resort to heuristics or fall back to greedy algorithms. However, greedy algorithms do not consider the entire search space and thus may overlook the optimal plan, resulting in bad query performance. In this book, we present a query optimizer based on genetic programming algorithms. We compare the results yielded by our optimizer with those yielded by the UDB DB2 optimizer, as well as some of the most efficient randomized algorithms proposed in the literature. Our studies show that the larger the number of relations involved in the query, the larger the benefit obtained by this type of optimizers. 236 pp. Englisch. N° de réf. du vendeur 9783843391757
Acheter neuf
EUR 79
Expédition à EUR 23
Expédition depuis Allemagne vers Etats-Unis
Expédition depuis Allemagne vers Etats-Unis
Quantité disponible : 2 disponible(s)
Image fournie par le vendeur
Genetic Query Optimization for Large Databases
Edité par
LAP LAMBERT Academic Publishing, 2011
ISBN 10 : 3843391750
ISBN 13 : 9783843391757
Neuf
Couverture souple
Vendeur : moluna, Greven, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. N° de réf. du vendeur 5468994
Acheter neuf
EUR 63,42
Expédition à EUR 48,99
Expédition depuis Allemagne vers Etats-Unis
Expédition depuis Allemagne vers Etats-Unis
Quantité disponible : Plus de 20 disponibles
Image fournie par le vendeur
Genetic Query Optimization for Large Databases | On the Use of Evolutionary Strategies for Very Large Join Queries
Edité par
LAP LAMBERT Academic Publishing, 2011
ISBN 10 : 3843391750
ISBN 13 : 9783843391757
Neuf
Taschenbuch
Vendeur : preigu, Osnabrück, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. Genetic Query Optimization for Large Databases | On the Use of Evolutionary Strategies for Very Large Join Queries | Victor Muntés-Mulero | Taschenbuch | 236 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783843391757 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 107140342
Acheter neuf
EUR 66,40
Expédition à EUR 70
Expédition depuis Allemagne vers Etats-Unis
Expédition depuis Allemagne vers Etats-Unis
Quantité disponible : 5 disponible(s)
Image fournie par le vendeur
Genetic Query Optimization for Large Databases
Edité par
LAP LAMBERT Academic Publishing Jan 2011, 2011
ISBN 10 : 3843391750
ISBN 13 : 9783843391757
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -As the amount of stored data grows, the relational schemas needed to organize all these data get more complex, increasing the number of relations in the database. As a consequence, it becomes necessary to write SQL queries that involve a large number of relations. Once a SQL query is introduced into the DBMS, the query optimizer must find the most efficient query execution plan to solve it. State-of-the-art query optimizers, which typically employ dynamic programming techniques, are limited in the number of joins they can handle. In these situations, optimizers either resort to heuristics or fall back to greedy algorithms. However, greedy algorithms do not consider the entire search space and thus may overlook the optimal plan, resulting in bad query performance. In this book, we present a query optimizer based on genetic programming algorithms. We compare the results yielded by our optimizer with those yielded by the UDB DB2 optimizer, as well as some of the most efficient randomized algorithms proposed in the literature. Our studies show that the larger the number of relations involved in the query, the larger the benefit obtained by this type of optimizers.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 236 pp. Englisch. N° de réf. du vendeur 9783843391757
Acheter neuf
EUR 79
Expédition à EUR 60
Expédition depuis Allemagne vers Etats-Unis
Expédition depuis Allemagne vers Etats-Unis
Quantité disponible : 1 disponible(s)
Image fournie par le vendeur
Genetic Query Optimization for Large Databases : On the Use of Evolutionary Strategies for Very Large Join Queries
Edité par
LAP LAMBERT Academic Publishing, 2011
ISBN 10 : 3843391750
ISBN 13 : 9783843391757
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - As the amount of stored data grows, the relational schemas needed to organize all these data get more complex, increasing the number of relations in the database. As a consequence, it becomes necessary to write SQL queries that involve a large number of relations. Once a SQL query is introduced into the DBMS, the query optimizer must find the most efficient query execution plan to solve it. State-of-the-art query optimizers, which typically employ dynamic programming techniques, are limited in the number of joins they can handle. In these situations, optimizers either resort to heuristics or fall back to greedy algorithms. However, greedy algorithms do not consider the entire search space and thus may overlook the optimal plan, resulting in bad query performance. In this book, we present a query optimizer based on genetic programming algorithms. We compare the results yielded by our optimizer with those yielded by the UDB DB2 optimizer, as well as some of the most efficient randomized algorithms proposed in the literature. Our studies show that the larger the number of relations involved in the query, the larger the benefit obtained by this type of optimizers. N° de réf. du vendeur 9783843391757
Acheter neuf
EUR 79
Expédition à EUR 61,85
Expédition depuis Allemagne vers Etats-Unis
Expédition depuis Allemagne vers Etats-Unis
Quantité disponible : 1 disponible(s)
Image d'archives
Genetic Query Optimization for Large Databases: On the Use of Evolutionary Strategies for Very Large Join Queries
Edité par
LAP LAMBERT Academic Publishing, 2011
ISBN 10 : 3843391750
ISBN 13 : 9783843391757
Ancien ou d'occasion
Paperback
Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
Évaluation du vendeur 4 sur 5 étoiles
Paperback. Etat : Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book. N° de réf. du vendeur ERICA79038433917506
Acheter D'occasion
EUR 173,88
Expédition à EUR 28,91
Expédition depuis Royaume-Uni vers Etats-Unis
Expédition depuis Royaume-Uni vers Etats-Unis
Quantité disponible : 1 disponible(s)