Cloudera Data Engineering: Developing Applications with Apache Spark

PT27633
Training Summary
This four-day hands-on training course delivers the key concepts and knowledge developers need to use Apache Spark to develop high-performance, parallel applications on the Cloudera Data Platform (CDP). Hands-on exercises allow students to practice writing Spark applications that integrate with CDP core components, such as Hive and Kafka. Participants will learn how to use Spark SQL to query structured data, how to use Spark Streaming to perform real-time processing on streaming data, and how to work with “big data” stored in a distributed file system. After taking this course, participants will be prepared to face real-world challenges and build applications to execute faster decisions, better decisions, and interactive analysis, applied to a wide variety of use cases, architectures, and industries.
Prerequisites
All students are expected to have basic Linux experience, and basic proficiency with either Python or Scala programming languages. Basic knowledge of SQL is helpful. Prior knowledge of Spark and Hadoop is not required.
Duration
4 Days/Lecture & Lab
Audience
This course is designed for developers and data engineers.
Course Topics
  • Introduction to Zeppelin
  • HDFS Introduction
  • YARN Introduction
  • Distributed Processing History
  • Working with DataFrames
  • Introduction to Apache Hive
  • Hive and Spark Integration
  • Data Visualization with Zeppelin
  • Distributed Processing Challenges
  • Spark Distributed Processing
  • Writing, Configuring, and Running Spark Applications
  • Introduction to Structured Streaming
  • Message Processing with Apache Kafka
  • Structured Streaming with Apache Kafka
  • Aggregating and Joining Streaming DataFrames
  • Working with Datasets in Scala

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