Autoplay
Autocomplete
Previous Lesson
Complete and Continue
Apache Spark with Scala - Hands On with Big Data
Getting Started
Introduction, and Getting Set Up (16:19)
Create a Histogram of Real Movie Ratings with Spark! (14:39)
Scala Crash Course
Scala Basics, Part 1
Scala Basics, Part 2 (9:41)
Flow Control in Scala (7:18)
Functions in Scala (8:47)
Data Structures in Scala (16:38)
Spark Basics and Simple Examples
Introduction to Spark (8:42)
The Resilient Distributed Dataset (11:06)
Ratings Histogram Walkthrough (7:35)
Spark Internals (4:44)
Key / Value RDD's, and the Average Friends by Age example (12:23)
Running the Average Friends by Age Example (8:00)
Filtering RDD's, and the Minimum Temperature by Location Example (6:45)
Running the Minimum Temperature Example, and Modifying it for Maximum (10:12)
Counting Word Occurrences using Flatmap() (9:01)
Improving the Word Count Script with Regular Expressions (6:43)
Sorting the Word Count Results (8:12)
Find the Total Amount Spent by Customer (3:38)
Check your Results, and Sort Them by Total Amount Spent (4:28)
Check Your Results and Implementation Against Mine (3:26)
Advanced Examples of Spark Programs
Find the Most Popular Movie (4:31)
Use Broadcast Variables to Display Movie Names (8:54)
Find the Most Popular Superhero in a Social Graph (14:12)
Superhero Degrees of Separation: Introducing Breadth-First Search (6:54)
Superhero Degrees of Separation: Accumulators, and Implementing BFS in Spark (5:55)
Superhero Degrees of Separation: Review the code, and run it! (10:43)
Item-Based Collaborative Filtering in Spark, cache(), and persist() (8:18)
Running the Similar Movies Script using Spark's Cluster Manager (14:15)
Improve the Quality of Similar Movies (2:42)
Running Spark on a Cluster
Using spark-submit to run Spark driver scripts (7:00)
Packaging driver scripts with SBT (13:14)
Introducing Amazon Elastic MapReduce (7:13)
Creating Similar Movies from One Million Ratings on EMR (11:33)
Partitioning (5:09)
Best Practices for Running on a Cluster (5:33)
Troubleshooting, and Managing Dependencies (9:10)
SparkSQL, DataFrames, and DataSets
Introduction to SparkSQL (7:10)
Using SparkSQL (7:03)
Using DataFrames and DataSets (6:38)
Using DataSets instead of RDD's (7:24)
Machine Learning with MLLib
Introducing MLLib (9:18)
If you have trouble running the following activity...
Using MLLib to Produce Movie Recommendations (14:35)
Linear Regression with MLLib (5:55)
Using DataFrames with MLLib (8:30)
Intro to Spark Streaming
Spark Streaming Overview (9:55)
Set up a Twitter Developer Account, and Stream Tweets (12:44)
Structured Streaming (4:17)
Intro to GraphX
GraphX, Pregel, and Breadth-First-Search with Pregel. (10:40)
Superhero Degrees of Separation using GraphX (9:01)
You Made It! Where to Go from Here.
Learning More, and Career Tips (4:15)
Create a Histogram of Real Movie Ratings with Spark!
Download
SparkScala.zip
Complete and Continue