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Apache Spark 2.0 with Scala - Hands On with Big Data!

By: Frank Kane

  • 5
  • (6)
  • 07:20:04
  • 51
  • 14
  • Language: English
449 4990
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Course Summary

New! Updated for Spark 2.0.0.

“Big data" analysis is a hot and highly valuable skill – and this course will teach you the hottest technology in big data: Apache Spark. Employers including Amazon

Read More

Target Audience

  • Software engineers who want to expand their skills into the world of big data processing on a cluster
  • If you have no previous programming or scripting experience, you'll want to take an introductory programming course first.

Pre-Requisites

  • Some prior programming or scripting experience is required. A crash course in Scala is included, but you need to know the fundamentals of programming in order to pick it up.
  • You will need a desktop PC and an Internet connection. The course is created with Windows in mind, but users comfortable with MacOS or Linux can use the same tools.
  • The software needed for this course is freely available, and I'll walk you through downloading and installing it.

Curriculum

  • Introduction, and Getting Set Up
    14:30
  • [Activity] Create a Histogram of Real Movie Ratings with Spark!
    14:01
  • [Activity] Scala Basics, Part 1
    12:52
  • [Exercise] Scala Basics, Part 2
    09:41
  • [Exercise] Flow Control in Scala
    07:18
  • [Exercise] Functions in Scala
    08:47
  • [Exercise] Data Structures in Scala
    16:38
  • Introduction to Spark
    08:40
  • The Resilient Distributed Dataset
    11:04
  • Ratings Histogram Walkthrough
    07:33
  • Spark Internals
    04:42
  • Key / Value RDD's, and the Average Friends by Age example
    12:21
  • [Activity] Running the Average Friends by Age Example
    07:58
  • Filtering RDD's, and the Minimum Temperature by Location Example
    06:43
  • [Activity] Running the Minimum Temperature Example, and Modifying it for Maximum
    10:11
  • [Activity] Counting Word Occurrences using Flatmap()
    08:59
  • [Activity] Improving the Word Count Script with Regular Expressions
    06:41
  • [Activity] Sorting the Word Count Results
    08:10
  • [Exercise] Find the Total Amount Spent by Customer
    03:37
  • [Exercise] Check your Results, and Sort Them by Total Amount Spent
    04:26
  • Check Your Results and Implementation Against Mine
    03:26
  • [Activity] Find the Most Popular Movie
    04:30
  • [Activity] Use Broadcast Variables to Display Movie Names
    08:52
  • [Activity] Find the Most Popular Superhero in a Social Graph
    14:10
  • Superhero Degrees of Separation: Introducing Breadth-First Search
    06:52
  • Superhero Degrees of Separation: Accumulators, and Implementing BFS in Spark
    05:53
  • Superhero Degrees of Separation: Review the code, and run it!
    10:41
  • Item-Based Collaborative Filtering in Spark, cache(), and persist()
    08:16
  • [Activity] Running the Similar Movies Script using Spark's Cluster Manager
    14:13
  • [Exercise] Improve the Quality of Similar Movies
    02:41
  • [Activity] Using spark-submit to run Spark driver scripts
    06:58
  • [Activity] Packaging driver scripts with SBT
    14:06
  • Introducing Amazon Elastic MapReduce
    07:11
  • Creating Similar Movies from One Million Ratings on EMR
    12:47
  • Partitioning
    05:07
  • Best Practices for Running on a Cluster
    05:31
  • Troubleshooting, and Managing Dependencies
    09:08
  • Introduction to SparkSQL
    07:08
  • [Activity] Using SparkSQL
    07:00
  • [Activity] Using DataFrames and DataSets
    06:38
  • [Activity] Using DataSets instead of RDD's
    07:23
  • Introducing MLLib
    07:38
  • [Activity] Using MLLib to Produce Movie Recommendations
    07:22
  • [Activity] Linear Regression with MLLib
    11:37
  • [Activity] Using DataFrames with MLLib
    10:04
  • Spark Streaming Overview
    09:53
  • [Activity] Set up a Twitter Developer Account, and Stream Tweets
    12:12
  • Structured Streaming
    04:01
  • GraphX, Pregel, and Breadth-First-Search with Pregel
    10:38
  • [Activity] Superhero Degrees of Separation using GraphX
    08:59
  • Learning More, and Career Tips
    04:15

About the Author

Frank Kane, Founder of Sundog Software, LLC

Founder & CEO of Sundog Software, makers of the SilverLining Sky, Cloud, and Weather SDK and the Triton Ocean SDK. Broad and deep experience in software engineering, computer graphics, technical leadership, and machine learning.

More From Author

Reviews

Faryal Julia
5

Good course with lot of working examples. Instructor has good command over the subject.

Apache Spark 2.0 with Scala - Hands On with Big Data!

By: Frank Kane 5
  • 07:20:04
  • 51
  • 14
  • Language: English
4990 449
  • 15 days Money back Gurantee
  • Unlimited Access
  • Android, iPhone and iPad Access
  • Certificate of Completion

Course Summary

New! Updated for Spark 2.0.0.

“Big data" analysis is a hot and highly valuable skill – and this course will teach you the hottest technology in big data: Apache Spark. Employers including Amazon

Read More

Target Audience

  • Software engineers who want to expand their skills into the world of big data processing on a cluster
  • If you have no previous programming or scripting experience, you'll want to take an introductory programming course first.

Pre-Requisites

  • Software engineers who want to expand their skills into the world of big data processing on a cluster
  • If you have no previous programming or scripting experience, you'll want to take an introductory programming course first.

About the Author

Frank Kane, Founder of Sundog Software, LLC

Founder & CEO of Sundog Software, makers of the SilverLining Sky, Cloud, and Weather SDK and the Triton Ocean SDK. Broad and deep experience in software engineering, computer graphics, technical leadership, and machine learning.

More From Author

Review & Rating

Faryal Julia 5

Good course with lot of working examples. Instructor has good command over the subject.