Querying Databricks with Spark SQL: Leverage SQL to query and analyze Big Data for insightsКНИГИ » ОС И БД
Название: Querying Databricks with Spark SQL: Leverage SQL to query and analyze Big Data for insights Автор: Adam Aspin Издательство: BPB Publications Год: 2024 Страниц: 638 Язык: английский Формат: epub (true) Размер: 37.4 MB
A practical guide to using Spark SQL to perform complex queries on your Databricks data.
Description: 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.
Data is the lifeblood of the enterprise. Whether “Big Data” or the data stored in classic databases, it is queried using a variant of Structured Query Language (SQL). So, simply put, SQL is key to data analysis. A mastery of SQL will help you to delve deep into the data that is stored in corporate databases. You can apply SQL to analyse the data and then present it in a clearly understandable form.
Databricks lets you use its flavour of SQL to query the data that this platform contains. This means that SQL can usually serve a vital role in preparing the data for final delivery, irrespective of the output application that you are using to present your analysis. Most end-user tools have an option for entering SQL to help derive meaning from the underlying data sources. Consequently, a knowledge of SQL can help you analyse data faster and more clearly. The aim of this book is to give you the necessary mastery of SQL, and specifically the Databricks flavour of SQL (known as SparkSQL) to enable you to get the most out of your data, and to deliver the insights that will drive your competitive advantage.
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. - 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. This book is there to help anyone who wants to know more about using SQL to deliver analysis. This means that you could be: • A data analyst • A student • A database developer • An accountant • A business analyst Or indeed anyone who needs to deliver accurate analytics from the data stored in Databricks.
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Querying Databricks with Spark SQL: Leverage SQL to query and analyze Big Data for insights 
