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

 

What Will I Learn?
  • 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
  • Understand how Spark Streaming lets your process continuous streams of data in real time
  • 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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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

“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 AmazonEBayNASA 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 15 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 Resilient Distributed Datastores
  • Develop and run Spark jobs quickly using Python
  • 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. 

Who is the target audience?
  • 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.

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

 

Big Data with Apache Spark and Python – Hands On


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