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Development Development Tools Apache Spark

Introduction to Apache Spark for Developers and Engineers

Basic to intermediate level introduction to Apache Spark that provides the main skills required to use the technology
Rating: 4.0 out of 54.0 (118 ratings)
608 students
Created by Adastra Academy
Last updated 9/2015
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • Identify and understand the concepts of Big Data
  • Clearly describe Apache Spark
  • Understand and explain the various components of the Spark framework
  • Differentiate between Spark and Hadoop MapReduce
  • Download, install and use Spark on a local machine
  • Identify and understand the main Scala programming language concepts
  • Develop basic Spark applications
  • Explain and use Spark Resilient Distributed Datasets

Course content

5 sections • 55 lectures • 2h 52m total length

  • Preview02:24
  • Preview06:40
  • 1.3 Big Data Features and Traditional Datawarehousing Charactaristics
    05:40
  • 1.4 Use Case: Adastra's Big Data Reference Architecture
    02:01
  • 1.5 Section Conclusion
    00:46
  • 1.6 Big Data Concepts Quiz
    3 questions

  • 2.1 Introduction and topcis
    00:33
  • Preview02:54
  • 2.3 Spark's History
    03:21
  • 2.4 Why Use Spark
    05:38
  • 2.5 Section Conclusion
    00:36
  • 2.6 Spark Concepts Quiz
    5 questions

  • 3.1 Introduction and Topics
    00:31
  • 3.2 Spark Deployment Modes
    03:49
  • 3.3 Hands-on Exercise: Installing Stand-Alone Spark
    00:15
  • 3.4 Hands-on Exercise: Install Stand-Alone Spark on your computer
    16 pages
  • 3.5 Spark Install Quiz
    1 question
  • 3.6 The Spark Framework
    10:08
  • 3.7 Spark Application Concepts
    06:45
  • 3.8 Section Conclusion
    00:36
  • 3.9 Spark Infrastructure Quiz
    5 questions

  • 4.1 Introduction and topics
    00:36
  • 4.2 Scala Introduction & Language Features
    05:06
  • 4.3 Scala Language Basics-Base Types
    02:17
  • 4.4 Hands-on Examples: Scala Base Types
    5 pages
  • 4.5 Scala Language Basics-Operators
    03:36
  • 4.6 Hands-on Examples: Scala Operators
    5 pages
  • 4.7 Scala Language Constructs-Variables
    01:52
  • 4.8 Hands-on Examples: Scala Variables
    1 page
  • 4.9 Scala Language Constructs-Variables Quiz
    2 questions
  • 4.10 Scala Language Constructs-Arrays
    02:17
  • 4.11 Hands-on Examples: Scala Arrays
    1 page
  • 4.12 Scala Language Constructs-Lists
    02:18
  • 4.13 Hands-On Exercise: Scala Lists
    2 pages
  • 4.14 Scala Language Constructs-Collections
    02:06
  • 4.15 Quiz: Scala Arrays and Lists
    2 questions
  • 4.16 Scala Language Constructs-IF Expressions
    02:39
  • 4.17 Hands-On Excercise: Scala IF Expressions
    1 page
  • 4.18 Scala Language Constructs-MATCH-CASE Expressions
    01:28
  • 4.19 Hands-On Excercise: Scala MATCH-CASE Expressions
    1 page
  • 4.20 Scala Language Constructs-WHILE & FOR Loop Expressions
    02:09
  • 4.21 Hands-On Excercise: Scala WHILE & FOR Loop Expressions
    2 pages
  • 4.22 Quiz: Scala Loops and Execution Flow
    1 question
  • 4.23 Scala Language Basics-Functions
    01:39
  • 4.24 Hands-On Excercise: Scala Functions
    1 page
  • 4.25 Quiz: Scala Functions: Greatest Common Divisor
    1 question
  • 4.26 Scala Language Basics-Anonymous Functions
    03:26
  • 4.27 Hands-on Examples: Anonymous Functions
    1 page
  • 4.28 Scala Functions - Create your own function
    2 questions
  • 4.29 Scala Functions - quiz solution
    2 pages
  • 4.30 Section Conclusion
    00:53

  • 5.1 Introduction and sections
    01:09
  • 5.2 Resilient Distributed Datasets-Overview
    03:04
  • 5.3 Resilient Distributed Datasets
    10:26
  • 5.4 Hands-On Exercise: RDDs Lazy Evaluation & Actions
    5 pages
  • 5.5 RDDs Lazy Evaluation & Actions
    2 questions
  • 5.6 Resilient Distributed Datasets-How to Create
    03:32
  • 5.7 Hands-On Exercise: Creating an RDD from a Collection
    1 page
  • 5.8 RDD Creation
    2 questions
  • 5.9 Pair Resilient Distributed Datasets
    04:18
  • 5.10 Hands-On Exercise: Pair RDDs
    6 pages
  • 5.11 Pair RDDs - Joining datasets
    1 question
  • 5.12 Resilient Distributed Datasets-Persistence
    04:15
  • 5.13 Resilient Distributed Datasets-Shared Variables
    04:55
  • 5.14 Hands-on Examples: Distributed Shared Variables
    4 pages
  • 5.15 "Advanced" data processing with Spark
    1 question
  • 5.16 "Advanced" data processing with Spark - quiz solution
    1 page
  • 5.17 Section Conclusion
    01:10

Requirements

  • Basic understanding of Big Data concepts
  • Some understanding of a programming language such as Python, Java or Scala
  • Administrator privileges on a computer to download and install software

Description

What is Apache Spark?

Apache Spark is the next generation open source Big Data processing engine. Spark is designed to provide fast processing of large datasets and high performance for a wide range of applications. Spark enables in-memory cluster computing which greatly improves the speed of iterative algorithms and interactive data mining tasks.

Course Outcomes

'Introduction to Apache Spark' includes illuminating video lectures, practical hands-on Scala and Spark exercises, a guide to local installation of Spark, and quizzes. In this course, we guide students through:

  • An explanation of the Spark framework
  • The basics of programming in Scala, Spark's native language
  • An outline of how to work with Spark's primary abstraction, resilient distributed datasets (RDDs).

Upon completion of the course, students will be able to explain core concepts relating to Spark, understand the fundamentals of coding in Scala, and execute basic programming and data manipulation in Spark. This course will take approximately 8 hours to complete.

Recommended Experience

Programming Languages recommended for this course:

  • Scala (course exercises are in Scala)
  • Java
  • Python

Recommended for:

  • Data scientists and engineers
  • Developers
  • Individuals with a basic understanding of: Apache Hadoop, Big Data, programming languages (Scala, Java, or Python)

For students unfamiliar with Big Data and Hadoop, the course will provide a brief overview of each topic.

Why Adastra Academy?

Adastra Academy is a leading source of training and development for Information Management professionals and individuals interested in Data Management and Analytics technology. Our dedication to identifying and mastering emerging technologies guarantees our students are the first to have access to these quality courses. For an exceptional learning experience, our programs include hands-on labs and real world examples allowing students to easily apply their new knowledge.

Who this course is for:

  • Big Data Developers
  • Data Engineers
  • Big Data Consultants
  • Data Scientists

Instructor

Adastra Academy
Emerging Data Management and Analytics Technology Educators
Adastra Academy
  • 4.2 Instructor Rating
  • 4,618 Reviews
  • 41,690 Students
  • 6 Courses

We're focused on the tools and technologies that matter most for today and tomorrow.

Adastra Academy is a leading source of training and development for Information Management professionals and individuals interested in Data Management and Analytics technology. Our dedication to identifying and mastering emerging technologies guarantees our students are the first to gain access to critical skills. Our programs consist of hands-on labs and real world examples allowing students to easily apply their new knowledge.

As a division of Adastra Corporation, we leverage twenty years of world-class Information Management knowledge, experience, services and solutions to fuel the Academy and to advance Information Management professionals everywhere.

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