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Building Hadoop Clusters

Deploy multi-node Hadoop clusters to harness the Cloud for storage and large-scale data processing
Course from Udemy
 84 students enrolled
 en
Explore Amazon's Web Services to manage big data
Configure network and security settings when deploying instances to the cloud
Explore methods to connect to cloud instances using your client machine
Set up Linux environments and configure settings for services and package installations
Examine Hadoop's general architecture and what each service brings to the table
Harness and navigate Hadoop's file storage and processing mechanisms
Install and master Apache Hadoop User Interface (HUE)

Hadoop is an Apache top-level project that allows the distributed processing of large data sets across clusters of computers using simple programming models. It allows you to deliver a highly available service on top of a cluster of computers, each of which may be prone to failures. While Big Data and Hadoop have seen a massive surge in popularity over the last few years, many companies still struggle with trying to set up their own computing clusters.

This video series will turn you from a faltering first-timer into a Hadoop pro through clear, concise descriptions that are easy to follow.

We'll begin this course with an overview of Amazon's cloud service and its use. We'll then deploy Linux compute instances and you'll see how to connect your client machine to Linux hosts and configure your systems to run Hadoop. Finally, you'll install Hadoop, download data, and examine how to run a query.

This video series will go beyond just Hadoop; it will cover everything you need to get your own clusters up and running. You will learn how to make network configuration changes as well as modify Linux services. After you've installed Hadoop, we'll then go over installing HUE—Hadoop's UI. Using HUE, you will learn how to download data to your Hadoop clusters, move it to HDFS, and finally query that data with Hive.

Learn everything you need to deploy Hadoop clusters to the Cloud through these videos. You'll grasp all you need to know about handling large data sets over multiple nodes.

About the Author

Sean Mikha is a technical architect who specializes in implementing large-scale data warehouses using Massively Parallel Processing (MPP) technologies. Sean has held roles at multiple companies that specialize in MPP technologies, where he was a part of implementing one of the largest commercial clinical data warehouses in the world. Sean is currently a solution architect, focusing on architecting Big Data solutions while also educating customers on Hadoop technologies. Sean graduated from UCLA with a BS in Computer Engineering, and currently lives in Southern California.

Building Hadoop Clusters
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