Querying Databricks with Spark SQL: Leverage SQL to query and analyze Big Data for insights Front Cover

Querying Databricks with Spark SQL: Leverage SQL to query and analyze Big Data for insights

  • Length: 556 pages
  • Edition: 1
  • Publisher:
  • Publication Date: 2023-10-05
  • ISBN-10: 9355518013
  • ISBN-13: 9789355518019
  • Sales Rank: #0 (See Top 100 Books)

A practical guide to using Spark SQL to perform complex queries on your Databricks data

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.


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.

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.

Table of Contents

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

To access the link, solve the captcha.