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

(12 customer reviews)
Product is rated as #64 in category Development

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

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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.

12 reviews for Taming Big Data with Apache Spark and Python – Hands On!

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  1. Gaston Buedo

    Muy buen curso, muy bien explicado. Hay partes donde un novato se pierde un poco, pero en general cubre todo y esta excelente, es muy bueno para guardarse los ejemplos y tomarlo mas de una vez.

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  2. Mihir Sabnis

    Got good exposure on Spark with very well explained examples and concepts.
    Thanks for covering these many concepts in short time span.

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  3. Nagaraj Gotur

    Have great handson examples, by practicing them you can become an expert. The level of coding involved is an expert level.

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  4. Gorden Pfitzmann

    Very nice voice. Good and easy understandable content. A few things like streaming did not work (some settings probably).

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  5. VENKATA SIVA GOWTHAM PUTTA

    Update lecture 5 and remake it using spark 3 versions
    Installation using the shown process has changed now,it took a whole day to re installation with good compactable matchings in hadoop,python,spark.

    if not every student looses intrest on this course.

    excluding that everything is great.

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  6. Jfforerob

    Great teacher with real world experience on the field, I recommend this course and the one on machine learning.

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  7. Diego Pérez Alonso

    Muy bueno. Te da una visión general e incluso tiene ejercicios para que vayas “tocando”. Te ofrece unos buenos conocimientos sobre spark con python, diferenciando entre sus diferentes partes. Quizás y para mi gusto le falta algo de la parte de streaming, pero para eso puedes continuar con su curso especializado.

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  8. Crispin Kalala Mukanya

    The course provides needed insights with regard to working with spark on big data projects. It’s really interesting!

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  9. Daniel Rosenberger

    Covers all the important basic and gives a good impression on what parts are usefull for certain tasks.

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  10. Dave Taylor

    Frank and Sundog Education make things really easy to learn. Obviously a lot of hard work has gone into creating the content so you learn what’s important and are reassured about all the periphery stuff which isn’t at the heart of the topic you are learning. Even then there is enough information about other topics to make you aware what other courses may be available so you are free to take your own direction. The pace of the course is efficient which keeps you interested but not totally overwhelming so you can’t keep up. If I want to learn a subject and I see that Sundog Education happens to have one I’d definitely put that at the top of the list. Thanks Frank and Sundog Education!

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  11. Ali Imran Khan

    Very interesting and well designed so easy to learn and practice

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  12. A R

    tl;dr: This lesson is a valuable look into PySpark RDD algorithms, but not modern data science analysis methods with PySpark3.

    The code uses vague naming conventions which makes it difficult to following along.

    The lesson will tell you how to deploy pyspark, but it’s method to install/deploy Sparkv2 which also happens to work for Sparkv3.

    That said, since I bought this course, I am not an expert, and I may not have the experience required to understand why this lesson teaches PySpark this way.

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

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