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Databricks Certified Associate Developer for Apache Spark Using Python

You're reading from   Databricks Certified Associate Developer for Apache Spark Using Python The ultimate guide to getting certified in Apache Spark using practical examples with Python

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Product type Paperback
Published in Jun 2024
Publisher Packt
ISBN-13 9781804619780
Length 274 pages
Edition 1st Edition
Languages
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Author (1):
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Saba Shah Saba Shah
Author Profile Icon Saba Shah
Saba Shah
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Toc

Table of Contents (18) Chapters Close

Preface 1. Part 1: Exam Overview
2. Chapter 1: Overview of the Certification Guide and Exam FREE CHAPTER 3. Part 2: Introducing Spark
4. Chapter 2: Understanding Apache Spark and Its Applications 5. Chapter 3: Spark Architecture and Transformations 6. Part 3: Spark Operations
7. Chapter 4: Spark DataFrames and their Operations 8. Chapter 5: Advanced Operations and Optimizations in Spark 9. Chapter 6: SQL Queries in Spark 10. Part 4: Spark Applications
11. Chapter 7: Structured Streaming in Spark 12. Chapter 8: Machine Learning with Spark ML 13. Part 5: Mock Papers
14. Chapter 9: Mock Test 1
15. Chapter 10: Mock Test 2
16. Index 17. Other Books You May Enjoy

What is Spark SQL?

Spark SQL is a powerful module within the Apache Spark ecosystem that allows for the efficient processing and analysis of structured data. It provides a higher-level interface for working with structured data compared to the traditional RDD-based API of Apache Spark. Spark SQL combines the benefits of both relational and procedural processing, enabling users to seamlessly integrate SQL queries with complex analytics. By leveraging Spark’s distributed computing capabilities, Spark SQL enables scalable and high-performance data processing.

It provides a programming interface to work with structured data using SQL queries, DataFrame API, and Datasets API.

It allows users to query data using SQL-like syntax and provides a powerful engine for executing SQL queries on large datasets. Spark SQL also supports reading and writing data from various structured sources such as Hive tables, Parquet files, and JDBC databases.

Advantages of Spark SQL

Spark SQL...

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