SQL Query Design Patterns and Best Practices: A practical guide to writing readable and maintainable SQL queries using its design patterns (Paperback)
暫譯: SQL 查詢設計模式與最佳實踐:撰寫可讀性與可維護性高的 SQL 查詢的實用指南

Hughes, Steve, Neer, Dennis, Singh, Ram Babu

  • 出版商: Packt Publishing
  • 出版日期: 2023-03-31
  • 售價: $1,490
  • 貴賓價: 9.5$1,416
  • 語言: 英文
  • 頁數: 270
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1837633282
  • ISBN-13: 9781837633289
  • 相關分類: SQLDesign Pattern
  • 立即出貨 (庫存 < 3)

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商品描述

Enhance your SQL query writing skills to provide greater business value using advanced techniques such as common table expressions, window functions, and JSON

Key Features

• Examine query design and performance using query plans and indexes
• Solve business problems using advanced techniques such as common table expressions and window functions
• Use SQL in modern data platform solutions with JSON and Jupyter notebooks

Book Description

SQL has been the de facto standard when interacting with databases for decades and shows no signs of going away. Through the years, report developers or data wranglers have had to learn SQL on the fly to meet the business needs, so if you are someone who needs to write queries, SQL Query Design and Pattern Best Practices is for you.

This book will guide you through making efficient SQL queries by reducing set sizes for effective results. You’ll learn how to format your results to make them easier to consume at their destination. From there, the book will take you through solving complex business problems using more advanced techniques, such as common table expressions and window functions, and advance to uncovering issues resulting from security in the underlying dataset. Armed with this knowledge, you’ll have a foundation for building queries and be ready to shift focus to using tools, such as query plans and indexes, to optimize those queries. The book will go over the modern data estate, which includes data lakes and JSON data, and wrap up with a brief on how to use Jupyter notebooks in your SQL journey.

By the end of this SQL book, you’ll be able to make efficient SQL queries that will improve your report writing and the overall SQL experience.

What you will learn

• Build efficient queries by reducing the data being returned
• Manipulate your data and format it for easier consumption
• Form common table expressions and window functions to solve complex business issues
• Understand the impact of SQL security on your results
• Understand and use query plans and hints to optimize your queries
• Understand the impact of indexes on your query performance and design
• Work with data lake data and JSON in SQL queries
• Organize your queries using Jupyter notebooks

Who This Book Is For

This book is for SQL developers, data analysts, report writers, data scientists, and other data gatherers looking to expand their skills for complex querying as well as for building more efficient and performant queries.

For those new to SQL, this book can help you accelerate your learning and keep you from making common mistakes.

商品描述(中文翻譯)

增強您的 SQL 查詢撰寫技能,利用共用表達式、視窗函數和 JSON 等進階技術提供更大的商業價值

主要特點

・檢視查詢設計和性能,使用查詢計畫和索引
・利用共用表達式和視窗函數等進階技術解決商業問題
・在現代數據平台解決方案中使用 SQL,搭配 JSON 和 Jupyter notebooks

書籍描述

SQL 在與資料庫互動方面已經是事實上的標準,數十年來顯示出不會消失的跡象。多年來,報告開發人員或數據處理者必須隨時學習 SQL 以滿足商業需求,因此如果您需要撰寫查詢,則《SQL 查詢設計與模式最佳實踐》這本書適合您。

本書將指導您通過減少集大小來製作高效的 SQL 查詢,以獲得有效的結果。您將學習如何格式化結果,使其在目的地更易於消耗。接著,本書將帶您通過使用更進階的技術(如共用表達式和視窗函數)來解決複雜的商業問題,並進一步揭示由於底層數據集的安全性而產生的問題。掌握這些知識後,您將擁有建立查詢的基礎,並準備將重點轉向使用工具(如查詢計畫和索引)來優化這些查詢。本書將介紹現代數據環境,包括數據湖和 JSON 數據,並簡要說明如何在 SQL 旅程中使用 Jupyter notebooks。

在這本 SQL 書籍結束時,您將能夠撰寫高效的 SQL 查詢,改善您的報告撰寫和整體 SQL 體驗。

您將學到的內容

・通過減少返回的數據來建立高效的查詢
・操作您的數據並格式化以便於消耗
・形成共用表達式和視窗函數以解決複雜的商業問題
・了解 SQL 安全性對結果的影響
・理解並使用查詢計畫和提示來優化查詢
・了解索引對查詢性能和設計的影響
・在 SQL 查詢中處理數據湖數據和 JSON
・使用 Jupyter notebooks 組織您的查詢

本書適合對象

本書適合 SQL 開發人員、數據分析師、報告撰寫者、數據科學家及其他希望擴展其複雜查詢技能以及建立更高效和高性能查詢的數據收集者。

對於 SQL 新手,本書可以幫助您加速學習,避免常見錯誤。

目錄大綱

1. Reducing Rows and Columns in Your Result Sets
2. Efficiently Aggregating Data in Your Results
3. Formatting Your Results for Easier Consumption
4. Manipulating Your Data Results Using Conditional SQL
5. Using Common Table Expressions
6. Analyze Your Data Using Window Functions
7. Reshaping Your Data with Advanced Techniques
8. Impact of SQL Security on Query Results
9. Understanding Query Plans
10. Understanding Query Hints
11. Understanding the Impact of Indexes on Your Query Design
12. Handling JSON Data in SQL Server
13. Integrating File Data and Data Lake Content with SQL
14. Organizing and Sharing Your Queries with Jupyter Notebooks
15. Appendix – Preparing Your Environment

目錄大綱(中文翻譯)

1. Reducing Rows and Columns in Your Result Sets

2. Efficiently Aggregating Data in Your Results

3. Formatting Your Results for Easier Consumption

4. Manipulating Your Data Results Using Conditional SQL

5. Using Common Table Expressions

6. Analyze Your Data Using Window Functions

7. Reshaping Your Data with Advanced Techniques

8. Impact of SQL Security on Query Results

9. Understanding Query Plans

10. Understanding Query Hints

11. Understanding the Impact of Indexes on Your Query Design

12. Handling JSON Data in SQL Server

13. Integrating File Data and Data Lake Content with SQL

14. Organizing and Sharing Your Queries with Jupyter Notebooks

15. Appendix – Preparing Your Environment