High performance mysql

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  • High Performance MySQL Baron Schwartz, Peter Zaitsev, and Vadim Tkachenko Beijing • Cambridge • Farnham • Köln • Sebastopol • Tokyo All rights reserved. Printed in the United States of America. Published by O’Reilly Media, Inc., 1005 Gravenstein Highway North, Sebastopol, CA 95472. O’Reilly books may be purchased for educational, business, or sales promotional use. Online editions are also available for most titles

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  • We had several goals in mind for this book. Many of them were derived from think-ing about that mythical perfect MySQL book that none of us had read but that we kept looking for on bookstore shelves. Others came from a lot of experience helping other users put MySQL to work in their environments.

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  • High-Performance Parallel Database Processing and Grid Databases- P2: Parallel databases are database systems that are implemented on parallel computing platforms. Therefore, high-performance query processing focuses on query processing, including database queries and transactions, that makes use of parallelism techniques applied to an underlying parallel computing platform in order to achieve high performance.

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  • High-Performance Parallel Database Processing and Grid Databases- P1: Parallel databases are database systems that are implemented on parallel computing platforms. Therefore, high-performance query processing focuses on query processing, including database queries and transactions, that makes use of parallelism techniques applied to an underlying parallel computing platform in order to achieve high performance.

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  • High-Performance Parallel Database Processing and Grid Databases- P4: Parallel databases are database systems that are implemented on parallel computing platforms. Therefore, high-performance query processing focuses on query processing, including database queries and transactions, that makes use of parallelism techniques applied to an underlying parallel computing platform in order to achieve high performance.

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  • High-Performance Parallel Database Processing and Grid Databases- P8: Parallel databases are database systems that are implemented on parallel computing platforms. Therefore, high-performance query processing focuses on query processing, including database queries and transactions, that makes use of parallelism techniques applied to an underlying parallel computing platform in order to achieve high performance.

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  • High-Performance Parallel Database Processing and Grid Databases- P3: Parallel databases are database systems that are implemented on parallel computing platforms. Therefore, high-performance query processing focuses on query processing, including database queries and transactions, that makes use of parallelism techniques applied to an underlying parallel computing platform in order to achieve high performance.

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  • High-Performance Parallel Database Processing and Grid Databases- P6: Parallel databases are database systems that are implemented on parallel computing platforms. Therefore, high-performance query processing focuses on query processing, including database queries and transactions, that makes use of parallelism techniques applied to an underlying parallel computing platform in order to achieve high performance.

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  • High-Performance Parallel Database Processing and Grid Databases- P12: Parallel databases are database systems that are implemented on parallel computing platforms. Therefore, high-performance query processing focuses on query processing, including database queries and transactions, that makes use of parallelism techniques applied to an underlying parallel computing platform in order to achieve high performance.

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  • High-Performance Parallel Database Processing and Grid Databases- P13: Parallel databases are database systems that are implemented on parallel computing platforms. Therefore, high-performance query processing focuses on query processing, including database queries and transactions, that makes use of parallelism techniques applied to an underlying parallel computing platform in order to achieve high performance.

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  • High-Performance Parallel Database Processing and Grid Databases- P5: Parallel databases are database systems that are implemented on parallel computing platforms. Therefore, high-performance query processing focuses on query processing, including database queries and transactions, that makes use of parallelism techniques applied to an underlying parallel computing platform in order to achieve high performance.

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  • High-Performance Parallel Database Processing and Grid Databases- P7: Parallel databases are database systems that are implemented on parallel computing platforms. Therefore, high-performance query processing focuses on query processing, including database queries and transactions, that makes use of parallelism techniques applied to an underlying parallel computing platform in order to achieve high performance.

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  • High-Performance Parallel Database Processing and Grid Databases- P10: Parallel databases are database systems that are implemented on parallel computing platforms. Therefore, high-performance query processing focuses on query processing, including database queries and transactions, that makes use of parallelism techniques applied to an underlying parallel computing platform in order to achieve high performance.

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  • High-Performance Parallel Database Processing and Grid Databases- P9: Parallel databases are database systems that are implemented on parallel computing platforms. Therefore, high-performance query processing focuses on query processing, including database queries and transactions, that makes use of parallelism techniques applied to an underlying parallel computing platform in order to achieve high performance.

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  • High-Performance Parallel Database Processing and Grid Databases- P11: Parallel databases are database systems that are implemented on parallel computing platforms. Therefore, high-performance query processing focuses on query processing, including database queries and transactions, that makes use of parallelism techniques applied to an underlying parallel computing platform in order to achieve high performance.

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  • Finally, we refine the accuracy of the computed per- formance model through experimental sampling. We use statistical interpolation between computed and ex- perimental sample points in order to re-approximate the per-application performance models, thus dynamically refining the model. We experimentally show that, by us- ing this method, convergence towards near-optimal con- figurations can be achieved in mere minutes, while an exhaustive exploration of the multi-dimensional search space, representing all possible partitioning configura- tions, would take weeks, or even months.

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