Databricks Certified Associate Developer for Apache Spark Using Python: The ultimate guide to getting certified in Apache Spark using practical exampl

Learn the concepts and exercises needed to get certified as a Databricks Associate Developer for Apache Spark 3.0 and validate your skills as a Spark expert with an industry-recognized credential

1. Understand the fundamentals of Apache Spark to help you design robust and fast Spark applications
2. Delve into various data manipulation components for each phase of your data engineering project
3. Prepare for the certification exam with sample questions and mock exams, and get closer to your goal
4. Purchase of the print or Kindle book includes a free PDF eBook

With extensive data being collected every second, computing power cannot keep up with this pace of rapid growth. To make use of all the data, Spark has become a de facto standard for big data processing. Migrating data processing to Spark will not only help you save resources that will allow you to focus on your business, but also enable you to modernize your workloads by leveraging the capabilities of Spark and the modern technology stack for creating new business opportunities.

This book is a comprehensive guide that lets you explore the core components of Apache Spark, its architecture, and its optimization. You’ll become familiar with the Spark dataframe API and its components needed for data manipulation. Next, you’ll find out what Spark streaming is and why it’s important for modern data stacks, before learning about machine learning in Spark and its different use cases. What’s more, you’ll discover sample questions at the end of each section along with two mock exams to help you prepare for the certification exam.

By the end of this book, you’ll know what to expect in the exam and how to pass it with enough understanding of Spark and its tools. You’ll also be able to apply this knowledge in a real-world setting and take your skillset to the next level.

1. Create and manipulate SQL queries in Spark
2. Build complex Spark functions using Spark UDFs
3. Architect big data apps with Spark fundamentals for optimal design
4. Apply techniques to manipulate and optimize big data applications
5. Build real-time or near-real-time applications using Spark Streaming
6. Work with Apache Spark for machine learning applications

This book is for you if you’re a professional looking to venture into the world of big data and data engineering, a data professional who wants to endorse your knowledge of Spark, or a student. Although working knowledge of Python is required, no prior Spark knowledge is needed. Additionally, experience with Pyspark will be beneficial.