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Genetic Query Optimization for Large Databases - Victor Muntés-Mulero
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Victor Muntés-Mulero:
Genetic Query Optimization for Large Databases - neues Buch

2011, ISBN: 9783843391757

ID: 814698117

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. On the Use of Evolutionary Strategies for Very Large Join Queries Buch (fremdspr.) Taschenbuch 11.01.2011 Bücher>Fremdsprachige Bücher>Englische Bücher, LAP LAMBERT Academic Publishing, .201

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Genetic Query Optimization for Large Databases - Victor Muntés-Mulero
Vergriffenes Buch, derzeit bei uns nicht verfügbar.
(*)
Victor Muntés-Mulero:
Genetic Query Optimization for Large Databases - neues Buch

ISBN: 9783843391757

ID: 836676265

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. On the Use of Evolutionary Strategies for Very Large Join Queries Buch (fremdspr.) Bücher>Fremdsprachige Bücher>Englische Bücher, LAP LAMBERT Academic Publishing

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Genetic Query Optimization for Large Databases
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Genetic Query Optimization for Large Databases - neues Buch

ISBN: 9783843391757

ID: 17CHIKFIFHC

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. Bücher / Naturwissenschaften, Medizin, Informatik & Technik / Informatik & EDV

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Genetic Query Optimization for Large Databases On the Use of Evolutionary Strategies  for Very Large Join Queries - Muntés-Mulero, Victor
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Muntés-Mulero, Victor:
Genetic Query Optimization for Large Databases On the Use of Evolutionary Strategies for Very Large Join Queries - neues Buch

2011, ISBN: 3843391750

ID: A12653891

Kartoniert / Broschiert, mit Schutzumschlag neu, [PU:LAP Lambert Acad. Publ.]

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Genetic Query Optimization for Large Databases
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Genetic Query Optimization for Large Databases

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.

Detailangaben zum Buch - Genetic Query Optimization for Large Databases


EAN (ISBN-13): 9783843391757
ISBN (ISBN-10): 3843391750
Gebundene Ausgabe
Taschenbuch
Erscheinungsjahr: 2011
Herausgeber: LAP Lambert Acad. Publ.

Buch in der Datenbank seit 23.11.2007 05:54:30
Buch zuletzt gefunden am 06.02.2019 09:34:17
ISBN/EAN: 9783843391757

ISBN - alternative Schreibweisen:
3-8433-9175-0, 978-3-8433-9175-7


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