Developer For Apache Spark

Available Upon Request
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Course Objectives

This 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.

Descriptions

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.

Target Audience

This course is best suited to developers and engineers.

Training Outline

Day 1
  • Introduction
  • Introduction to Spark
  • Spark Basics
  • Working with RDDs in Spark
  • Aggregating Data with Pair RDDs
Day 2
  • Writing and Deploying Spark Applications
  • Parallel Processing
  • RDD Persistence
  • Basic Spark Streaming
Day 3
  • Advanced Spark Streaming
  • Common Patterns in Spark Data Processing
  • Improving Spark Performance
  • Spark SQL and DataFrames
  • Conclusion
  • Final questions and post-course survey

Prerequisite

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.