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Expert Performance Indexing in SQL Server 2019, Jason Strate


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Цена: 4890.00р.
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Автор: Jason Strate
Название:  Expert Performance Indexing in SQL Server 2019
ISBN: 9781484254639
Издательство: Springer
Классификация:


ISBN-10: 1484254635
Обложка/Формат: Soft cover
Страницы: 615
Вес: 1.20 кг.
Дата издания: 2019
Язык: English
Издание: 3rd ed.
Иллюстрации: 247 illustrations, black and white; xxiii, 615 p. 247 illus.
Размер: 254 x 178 x 33
Читательская аудитория: Professional & vocational
Основная тема: Computer Science
Подзаголовок: Toward Faster Results and Lower Maintenance
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Германии
Описание:
Take a deep dive into perhaps the single most important facet of good performance: indexes, and how to best use them. Recent updates to SQL Server have made it possible to create indexes in situations that in the past would have prevented their use.
Other improvements covered in this book include new dynamic management views, the ability to pause and resume index maintenance, and the ability to more easily recover from failures during index creation and maintenance operations. This new edition also brings new content around the indexing of columnstore and in-memory tables, showing how these new types of tables and the queries that execute against them can also benefit from good indexing practices.
The book begins with explanations of the types of indexes and how they are stored in databases. Moving deeper into the topic, and further into the book, you will look at the statistics that are accumulated both by indexes and on indexes. You will better understand what indexes are doing in the database and what can be done to mitigate and improve their effect on performance. You will get a look at the Index Advisor now available in Azure SQL Database, and learn how to review and maintain the health of your indexes. The final chapters present a guided tour through a number of scenarios showing approaches you can take to investigate, mitigate, and improve the performance of your database.
What You Will Learn
Properly index row store, columnstore, and in-memory tablesReview statistics to understand indexing choices made by the optimizerApply indexing strategies such as covering indexes, included columns, and index intersectionsRecognize and remove unnecessary indexesDesign effective indexes for full-text, spatial, and XML data typesManage the big picture: Encompass all indexes in a database, and all database instances on a server
Who This Book Is For
Database administrators and developers who are ready to lift the performance of their database environment by thoughtfully building indexes to speed up queries that matter the most and make a difference to the business

Дополнительное описание: 1. Index Fundamentals.- 2. Index Storage Fundamentals.- 3. Index Metadata and Statistics.- 4. XML Indexes.- 5. Spatial Indexing.- 6. Indexing Memory-Optimized Tables.- 7. Full-Text Indexing.- 8. Indexing Myths and Best Practices.- 9. Index Maintenance.- 1



Query Store for SQL Server 2019

Автор: Tracy Boggiano; Grant Fritchey
Название: Query Store for SQL Server 2019
ISBN: 1484250036 ISBN-13(EAN): 9781484250037
Издательство: Springer
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Цена: 3912.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Apply the new Query Store feature to identify and fix poorly performing queries in SQL Server.

Query Store is an important and recent feature in SQL Server that provides insight into the details of query execution and how that execution has changed over time. Query Store helps to identify queries that aren’t performing well, or that have regressed in their performance. Query Store provides detailed information such as wait stats that you need to resolve root causes, and it allows you to force the use of a known good execution plan. With SQL Server 2017 and later you can automate the correction of regressions in performance.
Query Store for SQL Server 2019 helps you protect your database’s performance during upgrades of applications or version of SQL Server. The book provides fundamental information on how Query Store works and best practices for implementation and use. You will learn to run and interpret built-in reports, configure automatic plan correction, and troubleshoot queries using Query Store when needed. Query Store for SQL Server 2019 helps you master Query Store and bring value to your organization through consistent query execution times and automate correction of regressions.
What You'll Learn
Apply best practices in implementing Query Store on production serversDetect and correct regressions in query performanceLower the risk of performance degradation following an upgradeUse tools and techniques to get the most from Query StoreAutomate regression correction and other uses of Query Store
Who This Book Is For
SQL Server developers and administrators responsible for query performance on SQL Server. Anyone responsible for identifying poorly performing queries will be able to use Query Store to find these queries and resolve the underlying issues.
SQL Server 2019 Revealed: Including Big Data Clusters and Machine Learning

Автор: Ward Bob
Название: SQL Server 2019 Revealed: Including Big Data Clusters and Machine Learning
ISBN: 148425418X ISBN-13(EAN): 9781484254189
Издательство: Springer
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Цена: 7685.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Intermediate-Advanced user level

Refactoring Legacy T-SQL for Improved Performance: Modern Practices for SQL Server Applications

Автор: Bohm Lisa
Название: Refactoring Legacy T-SQL for Improved Performance: Modern Practices for SQL Server Applications
ISBN: 1484255801 ISBN-13(EAN): 9781484255803
Издательство: Springer
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Цена: 7685.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Intermediate-Advanced user level

Expert T-SQL Window Functions in SQL Server 2019

Автор: Kathi Kellenberger; Clayton Groom; Ed Pollack
Название: Expert T-SQL Window Functions in SQL Server 2019
ISBN: 1484251962 ISBN-13(EAN): 9781484251966
Издательство: Springer
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Цена: 4191.00 р.
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Описание:

Become an expert who can use window functions to solve T-SQL query problems. Replace slow cursors and self-joins with queries that are easy to write and perform better. This new edition provides expanded examples, including a chapter from the world of sports, and covers the latest performance enhancements through SQL Server 2019.
Window functions are useful in analytics and business intelligence reporting. They came into full blossom with SQL Server 2012, yet they are not as well known and used as often as they ought to be. This group of functions is one of the most notable developments in SQL, and this book shows how every developer and DBA can benefit from their expressive power in solving day-to-day business problems. Once you begin using window functions, such as ROW_NUMBER and LAG, you will discover many ways to use them. You will approach SQL Server queries in a different way, thinking about sets of data instead of individual rows. Your queries will run faster, be easier to write, and easier to deconstruct, maintain, and enhance in the future.
Just knowing and using these functions is not enough. You also need to understand how to tune the queries. Expert T-SQL Window Functions in SQL Server clearly explains how to get the best performance. The book also covers the rare cases when older techniques are the best bet.
What You Will Learn
Solve complex query problems without cumbersome self-joins that run slowly and are difficult to readCreate sliding windows in a result set for computing such as running totals and moving averagesReturn aggregate and detail data simultaneously from the same SELECT statementCompute lag and lead and other values that access data from multiple rows in a result setUnderstand the OVER clause syntax and how to control the windowAvoid framing errors that can lead to unexpected results
Who This Book Is For
Anyone who writes T-SQL queries, including database administrators, developers, business analysts, and data scientists. Before reading this book, you should understand how to join tables, write WHERE clauses, and build aggregate queries.

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