Parallel systems in the data warehouse Stephen Morse, David Isaac.

By: Morse, StephenContributor(s): Isaac, DavidSeries: The Data Warehousing Institute series from Prentice Hall PTR ; 3Publisher: Upper Saddle River, NJ : Prentice Hall, 1998Description: 395 p. : illISBN: 013680604XSubject(s): Data warehousing | Parallel processing (Electronic computers)Review: "Discover why parallel computing offers an ideal foundation for enterprise-scale data warehousing - and how to make the right strategic and tactical decisions about these critical technologies."--BK JACKET. "What are the right questions to ask? What aren't the vendors telling you? How do benchmarks relate to real-world results? Parallel Systems in the Data Warehouse evaluates all three major parallel hardware architectures, comparing scalability, performance and sustainable I/O bandwidth: symmetric multiprocessors (SMP), distributed memory (DM) or "massively parallel" machines, and distributed shared memory (DSM) systems ("non-uniform memory access" machines)."--BK JACKET. "Consistently high throughput is critical to the success of data warehousing - and traditional techniques like normalization and indexing aren't enough anymore. Learn smarter table partitioning strategies, star schema and other powerful techniques to fully exploit the inherent scalability and high I/O bandwidth of parallel hardware."--BK JACKET.
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"Discover why parallel computing offers an ideal foundation for enterprise-scale data warehousing - and how to make the right strategic and tactical decisions about these critical technologies."--BK JACKET. "What are the right questions to ask? What aren't the vendors telling you? How do benchmarks relate to real-world results? Parallel Systems in the Data Warehouse evaluates all three major parallel hardware architectures, comparing scalability, performance and sustainable I/O bandwidth: symmetric multiprocessors (SMP), distributed memory (DM) or "massively parallel" machines, and distributed shared memory (DSM) systems ("non-uniform memory access" machines)."--BK JACKET. "Consistently high throughput is critical to the success of data warehousing - and traditional techniques like normalization and indexing aren't enough anymore. Learn smarter table partitioning strategies, star schema and other powerful techniques to fully exploit the inherent scalability and high I/O bandwidth of parallel hardware."--BK JACKET.

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