Udemy - Taming Big Data with Apache Spark 3 and Python – Hands On!

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[FreeAllCourse.Com] Udemy - Taming Big Data with Apache Spark 3 and Python - Hands On! 1. Getting Started with Spark
  • 1. Introduction.mp4 (9.1 MB)
  • 1. Introduction.srt (4.2 KB)
  • 2. How to Use This Course.mp4 (11.5 MB)
  • 2. How to Use This Course.srt (3.1 KB)
  • 3. Udemy 101 Getting the Most From This Course.mp4 (19.7 MB)
  • 3. Udemy 101 Getting the Most From This Course.srt (4.0 KB)
  • 4. [Activity]Getting Set Up Installing Python, a JDK, Spark, and its Dependencies..mp4 (223.1 MB)
  • 4. [Activity]Getting Set Up Installing Python, a JDK, Spark, and its Dependencies..srt (24.9 KB)
  • 4.1 Apache Spark.html (0.1 KB)
  • 4.2 winutils.exe.html (0.1 KB)
  • 4.3 JDK.html (0.1 KB)
  • 5. [Activity] Installing the MovieLens Movie Rating Dataset.mp4 (7.9 MB)
  • 5. [Activity] Installing the MovieLens Movie Rating Dataset.srt (5.6 KB)
  • 6. [Activity] Run your first Spark program! Ratings histogram example..mp4 (66.2 MB)
  • 6. [Activity] Run your first Spark program! Ratings histogram example..srt (11.3 KB)
  • 6.1 ratings-counter.py.py (0.4 KB)
2. Spark Basics and Simple Examples
  • 1. Introduction to Spark.mp4 (34.0 MB)
  • 1. Introduction to Spark.srt (16.9 KB)
  • 10. [Activity] Improving the Word Count Script with Regular Expressions.mp4 (23.8 MB)
  • 10. [Activity] Improving the Word Count Script with Regular Expressions.srt (7.4 KB)
  • 10.1 word-count-better.py.py (0.5 KB)
  • 11. [Activity] Sorting the Word Count Results.mp4 (32.9 MB)
  • 11. [Activity] Sorting the Word Count Results.srt (12.6 KB)
  • 11.1 word-count-better-sorted.py.py (0.7 KB)
  • 12. Tally up amount spent by customer using Spark.html (0.1 KB)
  • 13. Sort your results by amount spent per customer.html (0.1 KB)
  • 2. The Resilient Distributed Dataset (RDD).mp4 (36.0 MB)
  • 2. The Resilient Distributed Dataset (RDD).srt (18.8 KB)
  • 3. Ratings Histogram Walkthrough.mp4 (80.0 MB)
  • 3. Ratings Histogram Walkthrough.srt (22.3 KB)
  • 3.1 ratings-counter.py.py (0.4 KB)
  • 4. KeyValue RDD's, and the Average Friends by Age Example.mp4 (61.7 MB)
  • 4. KeyValue RDD's, and the Average Friends by Age Example.srt (25.8 KB)
  • 5. [Activity] Running the Average Friends by Age Example.mp4 (47.5 MB)
  • 5. [Activity] Running the Average Friends by Age Example.srt (9.2 KB)
  • 5.1 fakefriends.csv.html (0.1 KB)
  • 5.2 friends-by-age.py.py (0.6 KB)
  • 6. Filtering RDD's, and the Minimum Temperature by Location Example.mp4 (30.9 MB)
  • 6. Filtering RDD's, and the Minimum Temperature by Location Example.srt (13.1 KB)
  • 6.1 min-temperatures.py.py (0.7 KB)
  • 6.2 1800.csv.html (0.1 KB)
  • 7. [Activity]Running the Minimum Temperature Example, and Modifying it for Maximums.mp4 (55.5 MB)
  • 7. [Activity]Running the Minimum Temperature Example, and Modifying it for Maximums.srt (8.7 KB)
  • 7.1 min-temperatures.py.py (0.7 KB)
  • 7.2 1800.csv.html (0.1 KB)
  • 8. [Activity] Running the Maximum Temperature by Location Example.mp4 (22.1 MB)
  • 8. [Activity] Running the Maximum Temperature by Location Example.srt (5.8 KB)
  • 8.1 max-temperatures.py.py (0.7 KB)
  • 9. [Activity] Counting Word Occurrences using flatmap().mp4 (29.4 MB)
  • 9. [Activity] Counting Word Occurrences using flatmap().srt (12.5 KB)
  • 9.1 word-count.py.py (0.4 KB)
  • 9.2 Book.txt (258.7 KB)
3. Advanced Examples of Spark Programs
  • 1. [Activity] Find the Most Popular Movie.mp4 (31.2 MB)
  • 1. [Activity] Find the Most Popular Movie.srt (9.1 KB)
  • 1.1 popular-movies.py.py (0.5 KB)
  • 10. [Exercise] Improve the Quality of Similar Movies.mp4 (20.6 MB)
  • 10. [Exercise] Improve the Quality of Similar Movies.srt (5.9 KB)
  • 2. [Activity] Use Broadcast Variables to Display Movie Names Instead of ID Numbers.mp4 (38.9 MB)
  • 2. [Activity] Use Broadcast Variables to Display Movie Names Instead of ID Numbers.srt (13.3 KB)
  • 2.1 popular-movies-nicer.py.py (0.9 KB)
  • 3. Find the Most Popular Superhero in a Social Graph.mp4 (25.0 MB)
  • 3. Find the Most Popular Superhero in a Social Graph.srt (7.3 KB)
  • 3.1 Marvel Graph.txt (1.6 MB)
  • 3.2 most-popular-superhero.py.py (0.9 KB)
  • 3.3 Marvel Names.txt (343.6 KB)
  • 4. [Activity] Run the Script - Discover Who the Most Popular Superhero is!.mp4 (29.0 MB)
  • 4. [Activity] Run the Script - Discover Who the Most Popular Superhero is!.srt (9.2 KB)
  • 4.1 Marvel Graph.txt (1.6 MB)
  • 4.2 Marvel Names.txt (343.6 KB)
  • 4.3 most-popular-superhero.py.py (0.9 KB)
  • 5. Superhero Degrees of Separation Introducing Breadth-First Search.mp4 (38.2 MB)
  • 5. Superhero Degrees of Separation Introducing Breadth-First Search.srt (13.8 KB)
  • 6. Superhero Degrees of Separation Accumulators, and Implementing BFS in Spark.mp4 (25.9 MB)
  • 6. Superhero Degrees of Separation Accumulators, and Implementing BFS in Spark.srt (11.1 KB)
  • 7. [Activity] Superhero Degrees of Separation Review the Code and Run it.mp4 (92.5 MB)
  • 7. [Activity] Superhero Degrees of Separation Review the Code and Run it.srt (16.6 KB)
  • 7.1 degrees-of-separation.py.py (3.6 KB)
  • 8. Item-Based Collaborative Filtering in Spark, cache(), and persist().mp4 (46.6 MB)
  • 8. Item-Based Collaborative Filtering in Spark, cache(), and persist().srt (18.0 KB)
  • 9. [Activity] Running the Similar Movies Script using Spark's Cluster Manager.mp4 (57.7 MB)
  • 9. [Activity] Running the Similar Movies Script using Spark's Cluster Manager.srt (18.1 KB)
  • 9.1 movie-similarities.py.py (3.5 KB)
4. Running Spark on a Cluster
  • 1. Introducing Elastic MapReduce.mp4 (29.0 MB)
  • 1. Introducing Elastic MapReduce.srt (8.8 KB)
  • 2. [Activity] Setting up your AWS Elastic MapReduce Account and Setting Up PuTTY.mp4 (65.6 MB)
  • 2. [Activity] Setting up your AWS Elastic MapReduce Account and Setting Up PuTTY.srt (16.7 KB)
  • 3. Partitioning.mp4 (24.6 MB)
  • 3. Partitioning.srt (7.0 KB)
  • 4. Create Similar Movies from One Million Ratings - Part 1.mp4 (28.8 MB)
  • 4. Create Similar Movies from One Million Ratings - Part 1.srt (8.4 KB)
  • 4.1 movie-similarities-1m.py.py (3.6 KB)
  • 5. [Activity] Create Similar Movies from One Million Ratings - Part 2.mp4 (60.1 MB)
  • 5. [Activity] Create Similar Movies from One Million Ra

Description

Taming Big Data with Apache Spark 3 and Python – Hands On!



Dive right in with 15+ hands-on examples of analyzing large data sets with Apache Spark, on your desktop or on Hadoop!

What you’ll learn?

   Use DataFrames and Structured Streaming in Spark 3
   Frame big data analysis problems as Spark problems
   Use Amazon’s Elastic MapReduce service to run your job on a cluster with Hadoop YARN
   Install and run Apache Spark on a desktop computer or on a cluster
   Use Spark’s Resilient Distributed Datasets to process and analyze large data sets across many CPU’s
   Implement iterative algorithms such as breadth-first-search using Spark
   Use the MLLib machine learning library to answer common data mining questions
   Understand how Spark SQL lets you work with structured data

Created by Sundog Education by Frank Kane, Frank Kane
Last updated 1/2020
English
English, French [Auto-generated]

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Udemy - Taming Big Data with Apache Spark 3 and Python – Hands On!

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1.9 GB
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Udemy - Taming Big Data with Apache Spark 3 and Python – Hands On!

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