Amazon’s Elastic MapReduce (EMR) is a managed Hadoop framework that allows enterprise and academic users to quickly and easily process huge data sets. Use cases can include log analysis, web indexing, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics. AWS Elastic MapReduce works, using the MapReduce architecture, by distributing and processing raw data across resizable and managed clusters of Amazon instances. Data output from this process is then reduced to a single set.
Despite how complex all that can sound and the fact that there is something of a steep learning curve the first time you confront it, AWS Elastic MapReduce is actually not all that difficult to use. And considering how critical it can be to control the flow of your growing data stores in an age that’s come to be defined by data, getting on top of Big Data can make all the difference in the world.
To make all this as accessible as possible, Cloud Academy’s own senior DevOps engineer (and in-house tech guru) Antonio Angelino, has just created a guided lab through which you will launch an actual MapReduce cluster using Amazon’s EMR.
Specifically, Antonio’s lab will help you confidently move through the entire process. You will:
Need the kind of confidence and experience that you would normally find only through spending time in an actual production environment? Take Cloud Academy’s AWS Elastic MapReduce Lab today!
Trainer Antonio Angelino has been particularly busy lately: besides this new Lab, he’s also completely reworked our AWS Relational Database Service (RDS) Lab, actually re-writing 60% of the steps. So if you’ve been meaning to get a better understanding of Amazon’s RDS, there’s never been a better time!
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