Querying Databricks with Spark SQL

Databricks stands out as a widely embraced platform dedicated to the creation of data lakes. Within its framework, it extends support to a specialized version of Structured Query Language (SQL) known as Spark SQL. If you are interested in learning more about how to use Spark SQL to analyze data in a data lake, then this book is for you.

The book covers everything from basic queries to complex data-processing tasks. It begins with an introduction to SQL and Spark. It then covers the basics of SQL, including data types, operators, and clauses. The next few chapters focus on filtering, aggregation, and calculation. Additionally, it covers dates and times, formatting output, and using logic in your queries. It also covers joining tables, subqueries, derived tables, and common table expressions. Additionally, it discusses correlated subqueries, joining and filtering datasets, using SQL in calculations, segmenting and classifying data, rolling analysis, and analyzing data over time. The book concludes with a chapter on advanced data presentation.

By the end of the book, you will be able to use Spark SQL to perform complex data analysis tasks on data lakes.

KEY FEATURES

* Learn SQL from the ground up, with no prior programming or SQL knowledge required.
* Progressively build your knowledge and skills, from basic data querying to complex analytics.
* Gain hands-on experience with SQL, covering all levels of knowledge from novice to expert.

WHAT YOU WILL LEARN

* Use Spark SQL to read data from a data lake.
* Learn how to filter, aggregate, and calculate data using Spark SQL.
* Learn how to join tables, use subqueries, and create derived tables in Spark SQL.
* Analyze data over time using Spark SQL to ​track trends and identify patterns in data.
* Present data in a visually appealing way using Spark SQL.

WHO THIS BOOK IS FOR

This book is for anyone who wants to learn how to use SQL to analyze big data. Whether you are a data analyst, student, database developer, accountant, business analyst, data scientist, or anyone else who needs to extract insights from large datasets, this book will teach you the skills you need to get the job done.

1. Writing Basic SQL Queries
2. Filtering Data
3. Applying Complex Filters to Queries
4. Simple Calculations
5. Aggregating Output
6. Working with Dates in Databricks
7. Formatting Text in Query Output
8. Formatting Numbers and Dates
9. Using Basic Logic to Enhance Analysis
10. Using Multiple Tables When Querying Data
11. Using Advanced Table Joins
12. Subqueries
13. Derived Tables
14. Common Table Expressions
15. Correlated Subqueries
16. Datasets Manipulation
17. Using SQL for More Advanced Calculations
18. Segmenting and Classifying Data
19. Rolling Analysis
20. Analyzing Data Over Time
21. Complex Data Output

Adam Aspin is an independent business intelligence consultant based in the United Kingdom. He has worked in Business Intelligence and analytics for over 25 years, and now focuses on Power BI. During this time, he has developed several dozen BI and analytics systems based on several different data platforms. Adam has been working with Databricks since it was first introduced, and has helped to deliver several analytical projects for multiple clients across Europe based on this technology.
Adam is a graduate of Oxford University. He has applied his skills for a range of clients in finance, banking, utilities, telecoms, construction, and retail. He is the author of a number of books, Querying MySQL, Querying MariaBD, Querying SQL Server, Querying Databricks with Spark SQL among others.