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Edité par Anchor Academic Publishing Dez 2014, 2014
ISBN 10 : 3954893363ISBN 13 : 9783954893362
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -For a DBMS that provides support for a declarative query language like SQL, the query optimizer is a crucial piece of software. The declarative nature of a query allows it to be translated into many equivalent evaluation plans. The process of choosing a suitable plan from all alternatives is known as query optimization. The basis of this choice are a cost model and statistics over the data. Essential for the costs of a plan is the execution order of join operations in its operator tree, since the runtime of plans with different join orders can vary by several orders of magnitude. An exhaustive search for an optimal solution over all possible operator trees is computationally infeasible. To decrease complexity, the search space must be restricted. Therefore, a well-accepted heuristic is applied: All possible bushy join trees are considered, while cross products are excluded from the search.There are two efficient approaches to identify the best plan: bottom-up and top- down join enumeration. But only the top-down approach allows for branch-and-bound pruning, which can improve compile time by several orders of magnitude, while still preserving optimality.Hence, this book focuses on the top-down join enumeration. In the first part, we present two efficient graph-partitioning algorithms suitable for top-down join enumer- ation. However, as we will see, there are two severe limitations: The proposed algo- rithms can handle only (1) simple (binary) join predicates and (2) inner joins. There- fore, the second part adopts one of the proposed partitioning strategies to overcome those limitations. Furthermore, we propose a more generic partitioning framework that enables every graph-partitioning algorithm to handle join predicates involving more than two relations, and outer joins as well as other non-inner joins. As we will see, our framework is more efficient than the adopted graph-partitioning algorithm. The third part of this book discusses the two branch-and-bound pruning strategies that can be found in the literature. We present seven advancements to the combined strategy that improve pruning (1) in terms of effectiveness, (2) in terms of robustness and (3), most importantly, avoid the worst-case behavior otherwise observed.Different experiments evaluate the performance improvements of our proposed methods. We use the TPC-H, TPC-DS and SQLite test suite benchmarks to evalu- ate our joined contributions. As we show, the average compile time improvement in those settings is 100% when compared with the state of the art in bottom-up join enu- meration. Our synthetic workloads show even higher improvement factors. 204 pp. Englisch.
Edité par GRIN Verlag Jun 2014, 2014
ISBN 10 : 3656663424ISBN 13 : 9783656663423
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Doctoral Thesis / Dissertation from the year 2014 in the subject Computer Science - Applied, grade: summa cum laude, University of Mannheim (School of Business Informatics and Mathematics), course: Databases, language: English, abstract: For a DBMS that provides support for a declarative query language like SQL, the query optimizer is a crucial piece of software. The declarative nature of a query allows it to be translated into many equivalent evaluation plans. The process of choosing a suitable plan from all alternatives is known as query optimization. The basis of this choice are a cost model and statistics over the data. Essential for the costs of a plan is the execution order of join operations in its operator tree, since the runtime of plans with different join orders can vary by several orders of magnitude. An exhaustive search for an optimal solution over all possible operator trees is computationally infeasible. To decrease complexity, the search space must be restricted. Therefore, a well-accepted heuristic is applied: All possible bushy join trees are considered, while cross products are excluded from the search.There are two efficient approaches to identify the best plan: bottom-up and top-down join enumeration. But only the top-down approach allows for branch-and-bound pruning, which can improve compile time by several orders of magnitude, while still preserving optimality.Hence, this thesis focuses on the top-down join enumeration. In the first part, we present two efficient graph-partitioning algorithms suitable for top-down join enumeration. However, as we will see, there are two severe limitations: The proposed algorithms can handle only (1) simple (binary) join predicates and (2) inner joins. Therefore, the second part adopts one of the proposed partitioning strategies to overcome those limitations. Furthermore, we propose a more generic partitioning framework that enables every graph-partitioning algorithm to handle join predicates involving more than two relations, and outer joins as well as other non-inner joins. As we will see, our framework is more efficient than the adopted graph-partitioning algorithm. The third part of this thesis discusses the two branch-and-bound pruning strategies that can be found in the literature. We present seven advancements to the combined strategy that improve pruning (1) in terms of effectiveness, (2) in terms of robustness and (3), most importantly, avoid the worst-case behavior otherwise observed.Different experiments evaluate the performance improvements of our proposed methods. We use the TPC-H, TPC-DS and SQLite test suite benchmarks to evaluate our joined contributions. 208 pp. Englisch.
Edité par Anchor Academic Publishing, 2014
ISBN 10 : 3954893363ISBN 13 : 9783954893362
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - For a DBMS that provides support for a declarative query language like SQL, the query optimizer is a crucial piece of software. The declarative nature of a query allows it to be translated into many equivalent evaluation plans. The process of choosing a suitable plan from all alternatives is known as query optimization. The basis of this choice are a cost model and statistics over the data. Essential for the costs of a plan is the execution order of join operations in its operator tree, since the runtime of plans with different join orders can vary by several orders of magnitude. An exhaustive search for an optimal solution over all possible operator trees is computationally infeasible. To decrease complexity, the search space must be restricted. Therefore, a well-accepted heuristic is applied: All possible bushy join trees are considered, while cross products are excluded from the search.There are two efficient approaches to identify the best plan: bottom-up and top- down join enumeration. But only the top-down approach allows for branch-and-bound pruning, which can improve compile time by several orders of magnitude, while still preserving optimality.Hence, this book focuses on the top-down join enumeration. In the first part, we present two efficient graph-partitioning algorithms suitable for top-down join enumer- ation. However, as we will see, there are two severe limitations: The proposed algo- rithms can handle only (1) simple (binary) join predicates and (2) inner joins. There- fore, the second part adopts one of the proposed partitioning strategies to overcome those limitations. Furthermore, we propose a more generic partitioning framework that enables every graph-partitioning algorithm to handle join predicates involving more than two relations, and outer joins as well as other non-inner joins. As we will see, our framework is more efficient than the adopted graph-partitioning algorithm. The third part of this book discusses the two branch-and-bound pruning strategies that can be found in the literature. We present seven advancements to the combined strategy that improve pruning (1) in terms of effectiveness, (2) in terms of robustness and (3), most importantly, avoid the worst-case behavior otherwise observed.Different experiments evaluate the performance improvements of our proposed methods. We use the TPC-H, TPC-DS and SQLite test suite benchmarks to evalu- ate our joined contributions. As we show, the average compile time improvement in those settings is 100% when compared with the state of the art in bottom-up join enu- meration. Our synthetic workloads show even higher improvement factors.
Edité par GRIN Verlag, 2014
ISBN 10 : 3656663424ISBN 13 : 9783656663423
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Doctoral Thesis / Dissertation from the year 2014 in the subject Computer Science - Applied, grade: summa cum laude, University of Mannheim (School of Business Informatics and Mathematics), course: Databases, language: English, abstract: For a DBMS that provides support for a declarative query language like SQL, the query optimizer is a crucial piece of software. The declarative nature of a query allows it to be translated into many equivalent evaluation plans. The process of choosing a suitable plan from all alternatives is known as query optimization. The basis of this choice are a cost model and statistics over the data. Essential for the costs of a plan is the execution order of join operations in its operator tree, since the runtime of plans with different join orders can vary by several orders of magnitude. An exhaustive search for an optimal solution over all possible operator trees is computationally infeasible. To decrease complexity, the search space must be restricted. Therefore, a well-accepted heuristic is applied: All possible bushy join trees are considered, while cross products are excluded from the search.There are two efficient approaches to identify the best plan: bottom-up and top-down join enumeration. But only the top-down approach allows for branch-and-bound pruning, which can improve compile time by several orders of magnitude, while still preserving optimality.Hence, this thesis focuses on the top-down join enumeration. In the first part, we present two efficient graph-partitioning algorithms suitable for top-down join enumeration. However, as we will see, there are two severe limitations: The proposed algorithms can handle only (1) simple (binary) join predicates and (2) inner joins. Therefore, the second part adopts one of the proposed partitioning strategies to overcome those limitations. Furthermore, we propose a more generic partitioning framework that enables every graph-partitioning algorithm to handle join predicates involving more than two relations, and outer joins as well as other non-inner joins. As we will see, our framework is more efficient than the adopted graph-partitioning algorithm. The third part of this thesis discusses the two branch-and-bound pruning strategies that can be found in the literature. We present seven advancements to the combined strategy that improve pruning (1) in terms of effectiveness, (2) in terms of robustness and (3), most importantly, avoid the worst-case behavior otherwise observed.Different experiments evaluate the performance improvements of our proposed methods. We use the TPC-H, TPC-DS and SQLite test suite benchmarks to evaluate our joined contributions.
Edité par Anchor Academic Publishing, 2014
ISBN 10 : 3954893363ISBN 13 : 9783954893362
Vendeur : moluna, Greven, Allemagne
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. For a DBMS that provides support for a declarative query language like SQL, the query optimizer is a crucial piece of software. The declarative nature of a query allows it to be translated into many equivalent evaluation plans. The process of choosing a sui.
Edité par Grin Verlag, 2014
ISBN 10 : 3656663424ISBN 13 : 9783656663423
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
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Etat : New.
Edité par Anchor Academic Publishing, 2014
ISBN 10 : 3954893363ISBN 13 : 9783954893362
Vendeur : PBShop.store US, Wood Dale, IL, Etats-Unis
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PAP. Etat : New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Edité par Anchor Academic Publishing, 2014
ISBN 10 : 3954893363ISBN 13 : 9783954893362
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
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Etat : New.
Edité par Anchor Academic Publishing, 2014
ISBN 10 : 3954893363ISBN 13 : 9783954893362
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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Etat : New. PRINT ON DEMAND Book; New; Fast Shipping from the UK. No. book.
Edité par Anchor Academic Publishing 2015-01-12, 2015
ISBN 10 : 3954893363ISBN 13 : 9783954893362
Vendeur : Chiron Media, Wallingford, Royaume-Uni
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Paperback. Etat : New.
Edité par Anchor Academic Publishing, 2014
ISBN 10 : 3954893363ISBN 13 : 9783954893362
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
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PAP. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.