Analyzing Large Data Sets with Apache Spark

Name: Analyzing Large Data Sets with Apache Spark Training Course
Brand: DumpsArena
SKU: Analyzing Large Data Sets with Apache Spark
Price: 14.99 USD
Availability: InStock
Rating: 5.0 (52 reviews)

Best Seller 42 Lectures 4h 54m 45s

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Curriculum For This Course

1. Getting Started with Spark

5 lectures 27m 14s

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

2. Spark Basics and Simple Examples

11 lectures 1h 34m 28s

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

3. Advanced Examples of Spark Programs

10 lectures 1h 12m 40s

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

4. Running Spark on a Cluster

8 lectures 49m 1s

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

5. SparkSQL, DataFrames, and DataSets

3 lectures 20m 16s

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

6. Other Spark Technologies and Libraries

5 lectures 31m 6s

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

Analyzing Large Data Sets with Apache Spark

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