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)
Part 1: Refining Your Queries to Get the Results You Need
Part 2: Solving Complex Business and Data Problems in Your Queries
Part 3: Optimizing Your Queries to Improve Performance
Part 4: Working with Your Data on the Modern Data Platform

Understanding the OPENROWSET (BULK..) function

The OPENROWSET(BULK..) function is used to access remote data from a data source (for example, connect to a file stored in Data Lake Gen 2). It can be directly referenced in the FROM clause, similar to calling a table name and pulling data from it as a set of rows.

OPENROWSET(BULK..) can read different types of file structures – PARQUET, DELTA, or delimited text (CSV), and access can be controlled with different login options – Azure AD logins or SQL logins (publicly available files can be accessed by just the web data path).

There is a slight difference in using the OPENROWSET(BULK..) syntax while reading Parquet/Delta files or a CSV file.

Let’s look at the syntaxes used for the OPENROWSET(BULK..) function.

This is OPENROWSET(BULK..) for reading Parquet or Delta files:

--OPENROWSET syntax for Parquet/Delta Lake files
( { BULK 'storage path to Parquet file' , [DATA_SOURCE = <data...