Hi,
Your question has an academic sound, so I'll give it an academic answer ;).
Unfortunately, there are not really any good generalized (ie. cross join a
large matrix with a large matrix) methods for doing joins in map-reduce. The
fundamental reason for this is that in the general case you're
Hi Huazhong,
Sounds like an interesting application. Here's a few tips.
1. If the frames are not independent, you should find a way to key them
according to their order before dumping them in Hadoop so that they can be
sorted as part of your map reduce task. BTW, the video won't appear split
Last time I checked EMR only runs 0.18.3. You can use EC2 though, which
winds up being cheaper anyways.
On Wed, Dec 16, 2009 at 8:51 PM, 松柳 lamfeeli...@gmail.com wrote:
Hi all, I'm wondering whether Amazon starts to support the newest stable
version of Hadoop, or we can still just use 0.18.3?
One important thing to note is that, with cross products, you'll almost
always get better performance if you can fit both files on a single node's
disk rather than distributing the files.
On Tue, Dec 8, 2009 at 9:18 AM, laser08150815 la...@laserxyz.de wrote:
pmg wrote:
I am evaluating
As far as replication goes, you should look at a project called pastry.
Apparently some people have used hadoop mapreduce on top of it. You will
need to be clever, however, in how you do your mapreduce because you
probably won't want the job to eat all the users cpu time.
On Dec 2, 2009 5:11 PM,
The tool looks interesting. You should consider providing the source for it.
Is it written in a language that can run on platforms besides windows?
On Nov 17, 2009 10:40 AM, Cubic cubicdes...@gmail.com wrote:
Hi list.
This tool is a graphic interface for Hadoop.
It may improove your productivity
Hi,
What you can fit in distributed cache generally depends on the available
disk space on your nodes. With most clusters 300 mb will not be a problem,
but it depends on the cluster and the workload you're processing.
On Sat, Nov 14, 2009 at 10:34 PM, 于凤东 fengdon...@gmail.com wrote:
I have a
