Apache Spark Certification

Module 1 - Introduction to Spark - Getting started

What is Spark and what is its purpose?

Components of the Spark unified stack

Resilient Distributed Dataset (RDD)

Downloading and installing Spark standalone

Scala and Python overview

Launching and using Spark’s Scala and Python shell ©

Module 2 - Resilient Distributed Dataset and DataFrames

Understand how to create parallelized collections and external datasets

Work with Resilient Distributed Dataset (RDD) operations

Utilize shared variables and key-value pairs

Module 3 - Spark application programming

Understand the purpose and usage of the SparkContext

Initialize Spark with the various programming languages

Describe and run some Spark examples

Pass functions to Spark

Create and run a Spark standalone application

Submit applications to the cluster

Module 4 - Introduction to Spark libraries

Understand and use the various Spark libraries

Module 5 - Spark configuration, monitoring and tuning

Understand components of the Spark cluster

Configure Spark to modify the Spark properties, environmental variables, or logging properties

Monitor Spark using the web UIs, metrics, and external instrumentation

Understand performance tuning considerations