Ryan Womack, Data Librarian
Rutgers University
http://ryanwomack.com
twitter: @ryandata
https://github.com/ryandata/bigdata

Screencast version of workshop originally delivered at IASSIST (iassistdata.org) Annual Conference, June 2015.

Part 3 steps through accessing Amazon Web Services and launching a Hadoop cluster via Amazon Elastic Map Reduce (EMR).

Amazon EMR enables fast processing of large structured or unstructured datasets, and in this recorded webinar we’ll show you how to setup an Amazon EMR job flow to analyse application logs, and perform Hive queries against it. Also, we will review best practices around data file organisation on Amazon Simple Storage Service (S3), how clusters can be started from the AWS web console and command line, and how to monitor the status of a MapReduce job.

Finally we take a look at Hadoop ecosystem tools you can use with Amazon EMR and the additional features of the service.

View and download the slides from this webinar on Slideshare here: http://www.slideshare.net/AmazonWebServices/amazon-emr-masterclass

Check out the rest of the Masterclass webinars for 2015 here: http://aws.amazon.com/campaigns/emea/masterclass/

See the Journey Through the Cloud webinar series here: http://aws.amazon.com/campaigns/emea/journey/

Amazon Elastic MapReduce (EMR) の機能と利点について簡単にご紹介いたします。
詳細は、http://aws.amazon.com/jp/elasticmapreduce をご覧ください。

Connect with me or follow me at
https://www.linkedin.com/in/durga0gadiraju
https://www.facebook.com/itversity
https://github.com/dgadiraju
https://www.youtube.com/c/TechnologyMentor
https://twitter.com/itversity

Connect with me or follow me at
https://www.linkedin.com/in/durga0gadiraju
https://www.facebook.com/itversity
https://github.com/dgadiraju
https://www.youtube.com/c/TechnologyMentor
https://twitter.com/itversity