Cloudera Developer Training for Apache Spark

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Cloudera Developer Training for Apache Spark

BD-346

Apache Spark is the next-generation successor to MapReduce. Spark is a powerful, opensource processing engine for data in the Hadoop cluster, optimized for speed, ease of use, and sophisticated analytics. The Spark framework supports streaming data processing and complex, iterative algorithms, enabling applications to run up to 100x faster than traditional Hadoop MapReduce programs.

Cloudera University’s three-day training course for Apache Spark enables participants to build complete, unified big data applications combining batch, streaming, and interactive analytics on all their data. With Spark, developers can write sophisticated parallel applications to execute faster decisions, better decisions, and real-time actions, applied to a wide variety of use cases, architectures, and industries.

Course Objectives

Through instructor-led discussion and interactive, hands-on exercises, participants will navigate the Hadoop ecosystem, learning topics such as:
• Using the Spark shell for interactive data analysis
• The features of Spark’s Resilient Distributed Datasets
• How Spark runs on a cluster
• Parallel programming with Spark
• Writing Spark applications
• Processing streaming data with Spark

Audience & Prerequisites

This course is best suited to developers and engineers. Course examples and exercises are presented in Python and Scala, so knowledge of one of these programming languages is required. Basic knowledge of Linux is assumed. Prior knowledge of Hadoop is not required.

Course Topics
  • Introduction
  • Why Spark?
  • Spark Basics
  • Working with RDDs
  • The Hadoop Distributed File System
  • Running Spark on a Cluster
  • Parallel Programming with Spark
  • Caching and Persistence
  • Writing Spark Applications
  • Spark, Hadoop, and the Enterprise Data Center
  • Spark Streaming
  • Common Spark Algorithms
  • Improving Spark Performance
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