9780071829427-0071829423-Microsoft SQL Server 2014 Query Tuning & Optimization

Microsoft SQL Server 2014 Query Tuning & Optimization

ISBN-13: 9780071829427
ISBN-10: 0071829423
Edition: 1
Author: Benjamin Nevarez
Publication date: 2014
Publisher: McGraw Hill
Format: Paperback 416 pages
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Book details

ISBN-13: 9780071829427
ISBN-10: 0071829423
Edition: 1
Author: Benjamin Nevarez
Publication date: 2014
Publisher: McGraw Hill
Format: Paperback 416 pages

Summary

Microsoft SQL Server 2014 Query Tuning & Optimization (ISBN-13: 9780071829427 and ISBN-10: 0071829423), written by authors Benjamin Nevarez, was published by McGraw Hill in 2014. With an overall rating of 4.4 stars, it's a notable title among other SQL (Databases & Big Data, Programming Languages) books. You can easily purchase or rent Microsoft SQL Server 2014 Query Tuning & Optimization (Paperback) from BooksRun, along with many other new and used SQL books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $1.15.

Description

Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.Optimize Microsoft SQL Server 2014 queries and applications

Microsoft SQL Server 2014 Query Tuning & Optimization is filled with ready-to-use techniques for creating high-performance queries and applications. The book describes the inner workings of the query processor so you can write better queries and provide the query processor with the quality information it needs to produce efficient execution plans. You’ll also get tips for troubleshooting underperforming queries. In-Memory OLTP (Hekaton), a key new feature of SQL Server 2014, is fully covered in this practical guide.

  • Understand how the query optimizer works
  • Troubleshoot queries using extended events, SQL trace, dynamic management views (DMVs), the data collector, and other tools
  • Work with query operators for data access, joins, aggregations, parallelism, and updates
  • Speed up queries and dramatically improve application performance by creating the right indexes
  • Understand statistics and how to detect and fix cardinality estimation errors
  • Maximize OLTP query performance using In-Memory OLTP (Hekaton) features, including memory-optimized tables and natively compiled stored procedures
  • Monitor and promote plan caching and reuse to improve application performance
  • Improve the performance of data warehouse queries using columnstore indexes
  • Handle query processor limitations with hints and other methods
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