Apache Spark Basics – Quick Start to Spark

Course Code: 1339

Overview
Schedule classes
What you'll learn
Outline
Prerequisites
Who should attend

Overview

Apache Spark Basics introduces the participants to the Spark environment. This course is designed as a two-day, fast-paced training which covers the benefits, features and common uses & tools. During the course, participants work in a dynamic and hands-on learning environment.

Schedule Classes

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Course Delivery

This course is available in the following formats:

Live Classroom
Duration: 3 days

Live Virtual Classroom
Duration: 3 days

What You'll learn

Where Spark fits into the Big Data ecosystem
How to use core Spark features for critical data analysis
Key Spark technologies such as Spark shell for interactive data analysis, Spark internals, RDDs, Dataframes and Spark SQL

Outline

Module 1: Spark Basics

Background and history
Spark and Hadoop
Spark concepts and architecture
Spark ecosystem (core, Spark SQL, MLib, streaming)

Module 2: First look at Spark

Spark in local mode
Spark web UI
Spark shell
Analyzing dataset – part 1
Inspecting RDDs

Module 3: RDDs in depth

Partitions
RDD Operations / transformations
RDD types
MapReduce on RDD
Caching and persistence
Sharing cached RDDs

Module 4: Spark SQL & Dataframes

Dataframes
Dataframes DDL
Spark SQL
Defining tables and importing datasets
Queries

Prerequisites

Participants must attend the Java Programming Fundamentals (for Java training), Introduction to Python Programming (for Python training) and Introduction to SQL (Basic familiarity is needed, not in-depth SQL skills) courses, prior to taking up this course, or have equivalent knowledge and skills.

Who Should Attend

This is an Introductory-level course, geared for Developers and Architects seeking to be proficient in Spark tools & technologies. Participants should be experienced developers who are comfortable with Java, Scala or Python programming. Participants should also be able to navigate Linux command line and have basic knowledge of Linux editors (such as VI/nano) for editing code.

This course is highly recommended for: