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

Scenarios and business problems

In this example, we are going to extract the details of customer invoices and combine them with the MIN, MAX, and COUNT instances of each customer’s aggregated data. Refer to the following code:

SELECT CustomerID,
  InvoiceID,
  InvoiceDate,
  FORMAT(MIN(InvoiceDate) OVER (PARTITION BY CustomerID),  'yyyy-MM-dd') as FirstOrderDate,
  FORMAT(MAX(InvoiceDate) OVER (PARTITION BY CustomerID),  'yyyy-MM-dd') as LastOrderDate,
  COUNT(*) OVER (PARTITION BY CustomerID) AS SalesCount
  FROM [Sales].[Invoices]
  WHERE Year(InvoiceDate) = 2016

Partial results, shown in Figure 6.5, of this query show that for each customer, there is the first invoice date, the last invoice date, and the count of invoices for the year for each customer with some details for each invoice.

Figure 6.5 – Sample results set combining aggregate information without losing the details

Figure 6.5 – Sample results set combining...