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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

Structured Streaming in Spark

The world of data processing has evolved rapidly as data volume and data velocity increase every day. With that, the need to analyze and derive insights from real-time data is becoming increasingly crucial. Structured Streaming, a component of Apache Spark, has emerged as a powerful framework to process and analyze data streams in real time. This chapter delves into the realm of Structured Streaming, exploring its capabilities, features, and real-world applications.

In this chapter, we will cover the following topics:

  • Real-time data processing
  • The fundamentals of streaming
  • Streaming architectures
  • Spark Streaming
  • Structured Streaming
  • Streaming sources and sinks
  • Advanced topics in Structured Streaming
  • Joins in Structured Streaming

By the end of this chapter, you will understand Spark Streaming and the power of real-time data insights.

We will start by looking at what real-time data processing means.

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