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Expert T-SQL window functions in SQL...

Kellenberger, Kathi.

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Expert T-SQL window functions in SQL Server 2019 = the hidden secret to fast analytic and reporting queries /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Expert T-SQL window functions in SQL Server 2019/ by Kathi Kellenberger, Clayton Groom, Ed Pollack.
Reminder of title:	the hidden secret to fast analytic and reporting queries /
Author:	Kellenberger, Kathi.
other author:	Groom, Clayton.
Published:	Berkeley, CA :Apress : : 2019.,
Description:	xviii, 213 p. :ill., digital ;24 cm.
[NT 15003449]:	1. Looking through the Window -- 2. Discovering Ranking Functions -- 3. Summarizing with Window Aggregates -- 4. Calculating Running and Moving Aggregates -- 5. Adding Frames to the Window -- 6. Taking a Peek at Another Row -- 7. Understanding Statistical Functions -- 8. Tuning for Better Performance -- 9. Hitting a Home Run with Gaps, Islands, and Streaks -- 10. Time Range Calculations -- 11. Time Trend Calculations.
Contained By:	Springer eBooks
Subject:	SQL (Computer program language) -
Online resource:	https://doi.org/10.1007/978-1-4842-5197-3
ISBN:	9781484251973

Expert T-SQL window functions in SQL Server 2019 = the hidden secret to fast analytic and reporting queries /
Kellenberger, Kathi.

Expert T-SQL window functions in SQL Server 2019the hidden secret to fast analytic and reporting queries /[electronic resource] :by Kathi Kellenberger, Clayton Groom, Ed Pollack. - 2nd ed. - Berkeley, CA :Apress :2019. - xviii, 213 p. :ill., digital ;24 cm.

1. Looking through the Window -- 2. Discovering Ranking Functions -- 3. Summarizing with Window Aggregates -- 4. Calculating Running and Moving Aggregates -- 5. Adding Frames to the Window -- 6. Taking a Peek at Another Row -- 7. Understanding Statistical Functions -- 8. Tuning for Better Performance -- 9. Hitting a Home Run with Gaps, Islands, and Streaks -- 10. Time Range Calculations -- 11. Time Trend Calculations.

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. You will: Solve complex query problems without cumbersome self-joins that run slowly and are difficult to read Create sliding windows in a result set for computing such as running totals and moving averages Return aggregate and detail data simultaneously from the same SELECT statement Compute lag and lead and other values that access data from multiple rows in a result set Understand the OVER clause syntax and how to control the window Avoid framing errors that can lead to unexpected results.

ISBN: 9781484251973

Standard No.: 10.1007/978-1-4842-5197-3doiSubjects--Uniform Titles:

SQL server.
Subjects--Topical Terms:

606987
SQL (Computer program language)

LC Class. No.: QA76.73.S67 / K455 2019

Dewey Class. No.: 005.756

Expert T-SQL window functions in SQL Server 2019 = the hidden secret to fast analytic and reporting queries /
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505 0 $a 1. Looking through the Window -- 2. Discovering Ranking Functions -- 3. Summarizing with Window Aggregates -- 4. Calculating Running and Moving Aggregates -- 5. Adding Frames to the Window -- 6. Taking a Peek at Another Row -- 7. Understanding Statistical Functions -- 8. Tuning for Better Performance -- 9. Hitting a Home Run with Gaps, Islands, and Streaks -- 10. Time Range Calculations -- 11. Time Trend Calculations.
520 $a 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. You will: Solve complex query problems without cumbersome self-joins that run slowly and are difficult to read Create sliding windows in a result set for computing such as running totals and moving averages Return aggregate and detail data simultaneously from the same SELECT statement Compute lag and lead and other values that access data from multiple rows in a result set Understand the OVER clause syntax and how to control the window Avoid framing errors that can lead to unexpected results.
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700 1 $a Pollack, Ed. $3 2192001
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