The Power of Apache Spark and Hadoop

Cloudera Developer Training for Spark & Hadoop

Duration: 4 days

Industry: Information Technology

About this course

Cloudera Developer Training for Spark & Hadoop Course

This four-day hands-on training course delivers developers’ key concepts and expertise to use Apache Spark to develop high-performance parallel applications. Participants will learn how to use Spark SQL to query structured data and Spark Streaming to perform real-time processing on streaming data from a variety of sources. Developers will also practice writing applications that use core Spark to perform ETL processing and iterative algorithms. The course covers how to work with “big data” stored in a distributed file system and execute Spark applications on a Hadoop cluster. 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.

For more information, please check this blog from P2L, as well as this page.

Who can benefit?


This course is designed for developers and engineers who have programming experience, but prior knowledge of Hadoop and/or Spark is not required.


Course Objectives

  • How the Apache Hadoop ecosystem fits in with the data processing lifecycle
  • How data is distributed, stored, and processed in a Hadoop cluster
  • How to write, configure, and deploy Apache Spark applications on a Hadoop cluster
  • How to use the Spark shell and Spark applications to explore, process, and analyze distributed data • How to query data using Spark SQL, DataFrames, and Datasets
  • How to use Spark Streaming to process a live data stream
  • Introduction
  • Introduction to Apache Hadoop and the Hadoop Ecosystem
  • Apache Hadoop Overview
  • Apache Hadoop File Storage
  • Distributed Processing on an Apache Hadoop Cluster
  • Apache Spark Basics
  • Working with DataFrames and Schemas
  • Analyzing Data with DataFrame Queries
  • RDD Overview
  • Transforming Data with RDDs

This course is designed for developers and engineers who have programming experience, but prior knowledge of Spark and Hadoop is not required. Apache Spark examples and hands-on exercises are presented in Scala and Python. The ability to program in one of those languages is required. Basic familiarity with the Linux command line is assumed. Basic knowledge of SQL is helpful.

Contact P2L to schedule the dates for this course.