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Introduction to Apache Spark

Course Summary

The Introduction to Apache Spark training course is designed to demonstrate the necessary skills to work with Apache Spark, an open-source engine for data in the Hadoop ecosystem optimized for speed and advanced analytics.

 

The course begins by examining how to use Spark as an alternative to traditional MapReduce processing. Next, it explores how Spark supports streamed data processing and iterative algorithms. The course concludes with a lesson on how Spark enables jobs to run faster than traditional Hadoop MapReduce.

Purpose
Learn how to use Apache Spark as an alternative to traditional MapReduce processing
Audience
Developers working on projects that use traditional Hadoop MapReduce
Role
Software Developer
Skill Level
Introduction
Style
Lecture | Hands-on Activities |Labs
Duration
3 Days
Related Technologies
Apache Spark | Hadoop | Apache | AWS

 

Learning Objectives
  • Describe how Apache Spark and Hadoop fit together
  • List three motivations for using Spark
  • Understand Resilient Distributed Datasets (RDDs)
  • Implement an application using the key Spark concepts

What You'll Learn:

In the Introduction to Apache Spark training course, you'll learn:

Spark Basics

  • What is Apache Spark?
  • Using the Spark Shell
  • Resilient Distributed Datasets (RDDs)
  • Functional Programming with Spark

The Hadoop Distributed File (HDFS) System

  • Why HDFS?
  • HDFS Architecture
  • Using HDFS

Spark and Hadoop

  • Spark and the Hadoop Ecosystem
  • Spark and MapReduce

RDDs

  • RDD Operations
  • KeyValue Pair RDDs
  • MapReduce and Pair RDD Operations

Running Spark on a Cluster

  • Standalone Cluster
  • The Spark Standalone Web UI

Parallel Programming with Spark

  • RDD Partitions and HDFS Data Locality
  • Working With Partitions
  • Executing Parallel Operations

Caching and Persistence

  • Distributed Persistence
  • Caches

Writing Spark Applications

  • SparkContext
  • Spark Properties
  • Building and Running a Spark Application
  • Logging

Spark Streaming

  • Streaming Overview
  • Sliding Window Operations
  • Spark Streaming Applications
real world content

Real-World Content

Project-focused demos and labs using your tool stack and environment, not some canned "training room" lab.
expert practitioners

Expert Practitioners

Industry experts that bring their battle scars into the classroom.
experiential learning

Experiential Learning

More coding than lecture, coupled with architectural and design discussions.
tailored outlines

Tailored Outlines

One-size-fits-all doesn't apply to training teams. That's where we come in!
“I appreciated the instructor's technique of writing live code examples rather than using fixed slide decks to present the material.”

VMware

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