Titlebook: Analytics Optimization with Columnstore Indexes in Microsoft SQL Server; Optimizing OLAP Work Edward Pollack Book 2022 Edward Pollack 2022

Inveterate

Introduction to Analytic Data in a Transactional Database,sts and data scientists find more ways to crunch it. There is a great convenience to having analytic data in close proximity to its underlying transactional sources. Utility is also gained by choosing a location for analytic data that can withstand the test of time, thus avoiding the need for costly

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Columnstore Compression,t significant driver in both performance and resource consumption. Understanding how SQL Server implements compression in columnstore indexes and how different algorithms are used to shrink the size of this data allows for optimal architecture and implementation of analytic data storage in SQL Serve

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Bulk Loading Data, to be inserted directly into a columnstore index. This not only bypasses the delta store, but results in a transaction size that reflects the compression of the target data, greatly reducing the amount of data written to the transaction log when this process is utilized.

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Analytics Optimization with Columnstore Indexes in Microsoft SQL ServerOptimizing OLAP Work

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Analytics Optimization with Columnstore Indexes in Microsoft SQL Server978-1-4842-8048-5

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Book 2022nitive guidelines. You will learn when columnstore indexes shouldbe used, and the performance gains that you can expect. You will also become familiar with best practices around architecture, implementation, and maintenance. Finally, you will know the limitations and common pitfalls to be aware of a

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