At the core of working with large-scale datasets is a thorough knowledge of Big Data platforms like Apache Spark and Hadoop. In this course, Developing Spark Applications with Python & Cloudera, you’ll learn how to process data at scales you previously thought were out of your reach. First, you’ll learn all the technical details of how Spark works. Next, you’ll explore the RDD API, the original core abstraction of Spark. Finally, you’ll discover how to become more proficient using Spark SQL and DataFrames. When you’re finished with this course, you’ll have a foundational knowledge of Apache Spark with Python and Cloudera that will help you as you move forward to develop large-scale data applications that enable you to work with Big Data in an efficient and performant way.
Author Name: Xavier Morera
Author Description:
Xavier Morera is driven by one passion: taking on the challenge of understanding complex topics and sharing that knowledge with others. He’s currently focused on the transformative fields of AI, machine learning, generative AI, search, and big data. As an entrepreneur, project manager, technical author, and trainer, Xavier brings a diverse set of skills and deep expertise to every project he takes on. He holds multiple certifications with Cloudera, Microsoft, and the Scrum Alliance and has been… more

Table of Contents

• Course Overview
  1min
• Why Spark with Python and Cloudera?
  13mins
• Getting an Environment & Data: CDH + StackOverflow
  42mins
• Refreshing Your Knowledge: Python Fundamentals for This Course
  30mins
• Understanding Spark: An Overview
  27mins
• Getting Technical with Spark
  46mins
• Learning the Core of Spark: RDDs
  42mins
• Going Deeper into Spark Core
  46mins
• Increasing Proficiency with Spark: DataFrames & Spark SQL
  38mins
• Continuing the Journey on DataFrames and Spark SQL
  36mins
• Understanding a Typed API: Datasets Works with Scala, Not Python
  5mins
• Final Takeaway and Continuing the Journey with Spark
  11mins