Book Image

SQL Query Design Patterns and Best Practices

By : Steve Hughes, Dennis Neer, Dr. Ram Babu Singh, Shabbir H. Mala, Leslie Andrews, Chi Zhang
5 (1)
Book Image

SQL Query Design Patterns and Best Practices

5 (1)
By: Steve Hughes, Dennis Neer, Dr. Ram Babu Singh, Shabbir H. Mala, Leslie Andrews, Chi Zhang

Overview of this book

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.
Table of Contents (21 chapters)
1
Part 1: Refining Your Queries to Get the Results You Need
6
Part 2: Solving Complex Business and Data Problems in Your Queries
11
Part 3: Optimizing Your Queries to Improve Performance
14
Part 4: Working with Your Data on the Modern Data Platform

Understanding hierarchical data

Hierarchical data, as per the name, defines data items that are related to each other by a hierarchical relationship. When we think of hierarchical data, we get a visual of a tree in our mind and a root node and one or multiple leaves; in a relational database, it’s often referred to as a parent-child relation. Every child will have one parent and one parent can have one or multiple children.

Here are a few common examples of hierarchical data items in databases:

  • Employee/manager relationship
  • Organizational hierarchy
  • Folder/files system
  • Graph of links between web pages
  • Tasks assigned under a project

MS SQL has a built-in data type, hierarchyid, and it is specially designed to store and query hierarchical data and optimized for most common cases representing tree structure hierarchical data.

There are two ways to represent nodes in this data type—string and bit representation.

The / character is used...