Expert T-SQL Window Functions in SQL Server 2019: The Hidden Secret to Fast Analytic and Reporting Queries (SQL Server 2019 專家級 T-SQL 窗口函數：快速分析與報告查詢的隱藏秘訣)
Kellenberger, Kathi, Groom, Clayton, Pollack, Ed
買這商品的人也買了...
-
世界第一簡單電路學$320$272 -
T-SQL Window Functions: For Data Analysis and Beyond 3/e$1,600$1,520 -
$250T-SQL 性能調優秘笈 — 基於 SQL Server 2012 窗口函數 -
圖解資料庫的工作原理$450$356 -
ASP.NET Core 6 實戰守則：超易懂的跨平台開發入門教學 (iT邦幫忙鐵人賽系列書)$600$468
相關主題
商品描述
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 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
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.
商品描述(中文翻譯)
成為一位能夠使用窗口函數解決 T-SQL 查詢問題的專家。用易於撰寫且執行效能更佳的查詢替換緩慢的游標和自我連接。這本新版書提供了擴展的範例，包括來自體育界的一章，並涵蓋了 SQL Server 2019 的最新性能增強功能。
窗口函數在分析和商業智能報告中非常有用。它們在 SQL Server 2012 中得到了充分的發展，但並不像應該那樣被廣泛認識和使用。這組函數是 SQL 中最值得注意的發展之一，本書展示了每個開發人員和數據庫管理員如何從它們在解決日常業務問題中的表達能力中受益。一旦您開始使用 ROW_NUMBER 和 LAG 等窗口函數，您將發現許多使用它們的方法。您將以不同的方式處理 SQL Server 查詢，思考的是數據集而不是個別行。您的查詢將運行更快，更容易撰寫，並且更容易在未來進行拆解、維護和增強。
僅僅知道和使用這些函數是不夠的。您還需要了解如何調整查詢。《Expert T-SQL Window Functions in SQL Server》清楚地解釋了如何獲得最佳性能。本書還涵蓋了在某些情況下舊技術是最佳選擇的罕見情況。
您將學到什麼
- 解決複雜的查詢問題，而無需使用緩慢且難以閱讀的自我連接
- 在結果集中創建滑動窗口，用於計算運行總計和移動平均值等
- 從同一個 SELECT 語句中同時返回聚合和詳細數據
- 計算 lag 和 lead 等值，這些值從結果集中的多個行中訪問數據
- 理解 OVER 子句語法以及如何控制窗口
- 避免可能導致意外結果的框架錯誤
本書適合對象
任何撰寫 T-SQL 查詢的人，包括數據庫管理員、開發人員、業務分析師和數據科學家。在閱讀本書之前，您應該了解如何連接表格、撰寫 WHERE 子句和構建聚合查詢。
作者簡介
Kathi Kellenberger is a data platform MVP and the editor of Simple-Talk at Redgate Software. She has worked with SQL Server for over 20 years. She is also co-leader of the PASS Women in Technology Virtual Group and an instructor at LaunchCode. In her spare time, Kathi enjoys spending time with family and friends, singing, and cycling.
Clayton Groom is a data warehouse and analytics consultant at Clayton Groom, LLC. He has worked with SQL Server for 25 years. His expertise lies in designing and building data warehouse and analytic solutions on the Microsoft technology stack, including Power BI, SQL Server, Analysis Services, Reporting Services and Excel.
Edward Pollack has over 20 years of experience in database and systems administration and architecture, developing a passion for performance optimization and making things go faster. He has spoken at many SQL Saturdays, 24 Hours of PASS, and PASS Summits, and has coordinated SQL Saturday Albany since its inception in 2014.
作者簡介(中文翻譯)
Kathi Kellenberger 是一位資料平台 MVP，也是 Redgate Software 的 Simple-Talk 編輯。她在 SQL Server 領域已有超過 20 年的工作經驗。她同時也是 PASS Women in Technology Virtual Group 的共同領導者，並在 LaunchCode 擔任教師。在閒暇時間，Kathi 喜歡與家人和朋友相處、唱歌和騎自行車。
Clayton Groom 是 Clayton Groom, LLC 的資料倉儲和分析顧問。他在 SQL Server 領域已有 25 年的工作經驗。他的專長在於設計和構建基於 Microsoft 技術堆棧的資料倉儲和分析解決方案，包括 Power BI、SQL Server、Analysis Services、Reporting Services 和 Excel。
Edward Pollack 在資料庫和系統管理和架構方面擁有超過 20 年的經驗，對性能優化和加速事物的熱情使他深入研究。他曾在許多 SQL Saturdays、24 Hours of PASS 和 PASS Summits 上發表演講，並自 2014 年起協調 SQL Saturday Albany 活動。
