Hello Grant, Here is the link to the (future) page of example applications:
http://developer.amazonwebservices.com/connect/kbcategory.jspa?categoryID=263 This might be where a future Mahout example app might reside? Yours sincerely, Tim On Thu, Apr 2, 2009 at 7:19 PM, Grant Ingersoll <[email protected]> wrote: > Yeah, saw this today, too. Very cool. One of these days, I'll have time to > use the credits Amazon has donated to Apache and try this out more. I think > this furthers the need to make it easy to install Mahout on top of Hadoop in > this environment. Scripts for this would be a great donation. > > On Apr 2, 2009, at 4:28 AM, [email protected] wrote: > >> FYI. >> >> ---------- Forwarded message ---------- >> From: Amazon Web Services <[email protected]> >> Date: Apr 2, 2009 3:23pm >> Subject: Announcing Amazon Elastic MapReduce >> To: "[email protected]" <[email protected]> >> >> >> >> >> >> >> >> >> >>> Dear AWS Customer, >> >> >>> We are excited today to introduce the public beta of Amazon Elastic >>> MapReduce, a web service that enables businesses, researchers, data >>> analysts, and developers to easily and cost-effectively process vast amounts >>> of data. It utilizes a hosted Hadoop framework running on the web-scale >>> infrastructure of Amazon Elastic Compute Cloud (Amazon EC2) and Amazon >>> Simple Storage Service (Amazon S3). >> >> >>> Using Amazon Elastic MapReduce, you can instantly provision as much or as >>> little capacity as you like to perform data-intensive tasks for applications >>> such as web indexing, data mining, log file analysis, machine learning, >>> financial analysis, scientific simulation, and bioinformatics research. >>> Amazon Elastic MapReduce lets you focus on crunching or analyzing your data >>> without having to worry about time-consuming set-up, management or tuning of >>> Hadoop clusters or the compute capacity upon which they sit. >> >> >>> Working with the service is easy: Develop your processing application >>> using our samples or by building your own, upload your data to Amazon S3, >>> use the AWS Management Console or APIs to specify the number and type of >>> instances you want, and click "Create Job Flow." We do the rest, running >>> Hadoop over the number of specified instances, providing progress >>> monitoring, and delivering the output to Amazon S3. >> >> >>> We hope this new service will prove a powerful tool for your data >>> processing needs. You can sign up and start using the service today at >>> aws.amazon.com/elasticmapreduce. >> >> >> >>> Sincerely, >> >> >>> The Amazon Web Services Team >> >> >>> We hope you enjoyed receiving this message. If you wish to remove >>> yourself from receiving future product announcements or the AWS Newsletter, >>> please update your communication preferences. >> >> >>> Amazon Web Services LLC is a subsidiary of Amazon.com, Inc. Amazon.com is >>> a registered trademark of Amazon.com, Inc. This message produced and >>> distributed by Amazon Web Services, LLC, 1200 12th Ave South, Seattle, WA >>> 98144. >> > > -------------------------- > Grant Ingersoll > http://www.lucidimagination.com/ > > Search the Lucene ecosystem (Lucene/Solr/Nutch/Mahout/Tika/Droids) using > Solr/Lucene: > http://www.lucidimagination.com/search > >
