Name: Analyzing Large Data Sets with Apache Spark
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Analyzing Large Data Sets with Apache Spark

Get ready for your exam by enrolling in our comprehensive training course. This course includes a full set of instructional videos designed to equip you with in-depth knowledge essential for passing the certification exam with flying colors.

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Getting Started with Spark

1. Introduction
2m 16s
2. How to Use This Course
1m 41s
3. [Activity]Getting Set Up: Installing Python, a JDK, Spark, and its Dependencies.
14m 50s
4. [Activity] Installing the MovieLens Movie Rating Dataset
3m 35s
5. [Activity] Run your first Spark program! Ratings histogram example.
4m 52s

Spark Basics and Simple Examples

1. Introduction to Spark
10m 11s
2. The Resilient Distributed Dataset (RDD)
12m 17s
3. Ratings Histogram Walkthrough
13m 33s
4. Key/Value RDD's, and the Average Friends by Age Example
16m 13s
5. [Activity] Running the Average Friends by Age Example
5m 39s
6. Filtering RDD's, and the Minimum Temperature by Location Example
8m 10s
7. [Activity]Running the Minimum Temperature Example, and Modifying it for Maximums
5m 8s
8. [Activity] Running the Maximum Temperature by Location Example
3m 21s
9. [Activity] Counting Word Occurrences using flatmap()
7m 28s
10. [Activity] Improving the Word Count Script with Regular Expressions
4m 44s
11. [Activity] Sorting the Word Count Results
7m 44s

Advanced Examples of Spark Programs

1. [Activity] Find the Most Popular Movie
5m 52s
2. [Activity] Use Broadcast Variables to Display Movie Names Instead of ID Numbers
8m 23s
3. Find the Most Popular Superhero in a Social Graph
4m 29s
4. [Activity] Run the Script - Discover Who the Most Popular Superhero is!
6m
5. Superhero Degrees of Separation: Introducing Breadth-First Search
7m 54s
6. Superhero Degrees of Separation: Accumulators, and Implementing BFS in Spark
6m 44s
7. [Activity] Superhero Degrees of Separation: Review the Code and Run it
9m 14s
8. Item-Based Collaborative Filtering in Spark, cache(), and persist()
10m 12s
9. [Activity] Running the Similar Movies Script using Spark's Cluster Manager
10m 54s
10. [Exercise] Improve the Quality of Similar Movies
2m 58s

Running Spark on a Cluster

1. Introducing Elastic MapReduce
5m 8s
2. [Activity] Setting up your AWS / Elastic MapReduce Account and Setting Up PuTTY
9m 55s
3. Partitioning
4m 21s
4. Create Similar Movies from One Million Ratings - Part 1
5m 12s
5. [Activity] Create Similar Movies from One Million Ratings - Part 2
11m 27s
6. Create Similar Movies from One Million Ratings - Part 3
3m 28s
7. Troubleshooting Spark on a Cluster
3m 43s
8. More Troubleshooting, and Managing Dependencies
5m 47s

SparkSQL, DataFrames, and DataSets

1. Introducing SparkSQL
6m 8s
2. Executing SQL commands and SQL-style functions on a DataFrame
8m 16s
3. Using DataFrames instead of RDD's
5m 52s

Other Spark Technologies and Libraries

1. Introducing MLLib
8m 10s
2. [Activity] Using MLLib to Produce Movie Recommendations
2m 56s
3. Analyzing the ALS Recommendations Results
4m 53s
4. Using DataFrames with MLLib
7m 31s
5. Spark Streaming and GraphX
7m 36s