<font color="#330033"><font size="2"><font face="verdana,sans-serif">Tom / all:<br><br>I
was speaking to a friend of mine who works at Google, and he was
intimating how wonderfully awesome the Map Reduce / Hadoop stuff is. His
example was a computational job that would not be able to complete in
his lifetime on a single server can be distributed out to multiple nodes
and crunched and completed in minutes or hours, depending on how much
capacity I had to throw at the work.<br>
<br>To consider the direction of the IT industry as a whole, this is certainly an interesting discussion to have - <br><br>-
Companies are trying to do more cloud-like things, and a Hadoop elastic
cloud makes a lot of sense there, but getting that much data from
onsite to the cloud is a challenge. But, if the data set is that big,
would you not spend more $ on bandwidth transfer putting it to and
getting from the cloud than the GDP of some smaller countries? <br>
<br>- Doing an internal Hadoop architecture - certainly the way to go,
but what is the value of redesigning your data and processes to take
advantage of Hadoop when the investment has already been made in the
larger, vertically scaling hardware?<br>
<br>- Doing an internal Hadoop architecture that's based on an internal
elastic cloud (e.g. use capacity when needed, give it back when
finished) makes sense, but to the point of making the investment of
taking existing data and processes and converting it to the style needed
to be able to distribute the rows out to Hadoop, then it becomes
problematic.<br>
<br>I guess in short, I get it, but I don't see where it makes sense
yet, unless you are Google, Amazon, or one of the other "Top 10" biggies
out there.<br><br>Maybe this is where more public forum and discussion comes into play.<br>
<br>Interested in others' comments on what cloud is, and where it makes sense.<br><br></font></font></font><br>Angelo