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2022-04-07T17:31:00Z

DevelopmentData ScienceApache Spark

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

Apache Spark tutorial with 20+ hands-on examples of analyzing large data sets on your desktop or on Hadoop with Python!
Bestseller
Rating: 4.5 out of 54.5 (12,750 ratings)
75,172 students
Created by Sundog Education by Frank Kane, Frank Kane, Sundog Education Team
Last updated 4/2022
English
English, French [Auto], 

What you'll learn

  • Use DataFrames and Structured Streaming in Spark 3
  • Use the MLLib machine learning library to answer common data mining questions
  • Understand how Spark Streaming lets your process continuous streams of data in real time
  • 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
  • Understand how Spark SQL lets you work with structured data
  • Tune and troubleshoot large jobs running on a cluster
  • Share information between nodes on a Spark cluster using broadcast variables and accumulators
  • Understand how the GraphX library helps with network analysis problems

Requirements

  • Access to a personal computer. This course uses Windows, but the sample code will work fine on Linux as well.
  • Some prior programming or scripting experience. Python experience will help a lot, but you can pick it up as we go.

Description

New! Updated for Spark 3, more hands-on exercises, and a stronger focus on DataFrames and Structured Streaming.

“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, EBay, NASA JPL, and Yahoo all use Spark to quickly extract meaning from massive data sets across a fault-tolerant Hadoop cluster. You'll learn those same techniques, using your own Windows system right at home. It's easier than you might think.

Learn and master the art of framing data analysis problems as Spark problems through over 20 hands-on examples, and then scale them up to run on cloud computing services in this course. You'll be learning from an ex-engineer and senior manager from Amazon and IMDb.

  • Learn the concepts of Spark's DataFrames and Resilient Distributed Datastores

  • Develop and run Spark jobs quickly using Python and pyspark

  • Translate complex analysis problems into iterative or multi-stage Spark scripts

  • Scale up to larger data sets using Amazon's Elastic MapReduce service

  • Understand how Hadoop YARN distributes Spark across computing clusters

  • Learn about other Spark technologies, like Spark SQL, Spark Streaming, and GraphX

By the end of this course, you'll be running code that analyzes gigabytes worth of information – in the cloud – in a matter of minutes. 

This course uses the familiar Python programming language; if you'd rather use Scala to get the best performance out of Spark, see my "Apache Spark with Scala - Hands On with Big Data" course instead.

We'll have some fun along the way. You'll get warmed up with some simple examples of using Spark to analyze movie ratings data and text in a book. Once you've got the basics under your belt, we'll move to some more complex and interesting tasks. We'll use a million movie ratings to find movies that are similar to each other, and you might even discover some new movies you might like in the process! We'll analyze a social graph of superheroes, and learn who the most “popular" superhero is – and develop a system to find “degrees of separation" between superheroes. Are all Marvel superheroes within a few degrees of being connected to The Incredible Hulk? You'll find the answer.

This course is very hands-on; you'll spend most of your time following along with the instructor as we write, analyze, and run real code together – both on your own system, and in the cloud using Amazon's Elastic MapReduce service. 7 hours of video content is included, with over 20 real examples of increasing complexity you can build, run and study yourself. Move through them at your own pace, on your own schedule. The course wraps up with an overview of other Spark-based technologies, including Spark SQL, Spark Streaming, and GraphX.

Wrangling big data with Apache Spark is an important skill in today's technical world. Enroll now!

  • " I studied "Taming Big Data with Apache Spark and Python" with Frank Kane, and helped me build a great platform for Big Data as a Service for my company. I recommend the course!  " - Cleuton Sampaio De Melo Jr.

Who this course is for:

  • People with some software development background who want to learn the hottest technology in big data analysis will want to check this out. This course focuses on Spark from a software development standpoint; we introduce some machine learning and data mining concepts along the way, but that's not the focus. If you want to learn how to use Spark to carve up huge datasets and extract meaning from them, then this course is for you.
  • If you've never written a computer program or a script before, this course isn't for you - yet. I suggest starting with a Python course first, if programming is new to you.
  • If your software development job involves, or will involve, processing large amounts of data, you need to know about Spark.
  • If you're training for a new career in data science or big data, Spark is an important part of it.

Featured review

Amiri McCain
Amiri M.
77 courses
26 reviews
Rating: 5.0 out of 5hace 2 años
Great course to get you going with Apache Spark and Python! Frank's delivery is very thorough yet unpretentious; his explanations for each new concept that he introduces is down to earth and easy to follow. I took a similar course as part of Udacity's Data Engineering Nanodegree program and I am glad that I took Frank's course beforehand because Udacity's way of explaining it and the lessons they provided were unclear and confusing.

Instructors

Sundog Education by Frank Kane
Founder, Sundog Education. Machine Learning Pro
Sundog Education by Frank Kane
  • 4.6 Instructor Rating
  • 125,983 Reviews
  • 599,873 Students
  • 32 Courses

Sundog Education's mission is to make highly valuable career skills in big data, data science, and machine learning accessible to everyone in the world. Our consortium of expert instructors shares our knowledge in these emerging fields with you, at prices anyone can afford. 

Sundog Education is led by Frank Kane and owned by Frank's company, Sundog Software LLC. Frank spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers, all the time. Frank holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. In 2012, Frank left to start his own successful company, Sundog Software, which focuses on virtual reality environment technology, and teaching others about big data analysis.

Frank Kane
Founder, Sundog Education
Frank Kane
  • 4.6 Instructor Rating
  • 120,235 Reviews
  • 551,239 Students
  • 23 Courses

Frank spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers, all the time. Frank holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. In 2012, Frank left to start his own successful company, Sundog Software, which focuses on virtual reality environment technology, and teaching others about big data analysis.

Due to our volume of students, I am unable to respond to private messages; please post your questions within the Q&A of your course. Thanks for understanding.

Sundog Education Team
Sundog Education Team
Sundog Education Team
  • 4.6 Instructor Rating
  • 119,518 Reviews
  • 544,774 Students
  • 20 Courses

Our mission is to make highly valuable skills in machine learning, big data, AI, and data science accessible at prices anyone in the world can afford. Our current online courses have reached over 500,000 students worldwide. Sundog Education CEO, Frank Kane, spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers, all the time. Frank holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. In 2012, Frank left to start his own successful company, Sundog Software, which focuses on virtual reality environment technology and teaching others about big data analysis.

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