Hey Matt, What do you mean by 'real-time' though? While HDFS has pretty good contiguous data read speeds (and you get N x replicas to read from), if you're looking to "cache" frequently accessed files into memory then HDFS does not natively have support for that. Otherwise, I agree with Brock, seems like you could make it work with HDFS (sans MapReduce - no need to run it if you don't need it).
The presence of NameNode audit logging will help your file access analysis requirement. On Tue, Oct 16, 2012 at 1:17 AM, Matt Painter <m...@deity.co.nz> wrote: > Hi, > > I am a new Hadoop user, and would really appreciate your opinions on whether > Hadoop is the right tool for what I'm thinking of using it for. > > I am investigating options for scaling an archive of around 100Tb of image > data. These images are typically TIFF files of around 50-100Mb each and need > to be made available online in realtime. Access to the files will be > sporadic and occasional, but writing the files will be a daily activity. > Speed of write is not particularly important. > > Our previous solution was a monolithic, expensive - and very full - SAN so I > am excited by Hadoop's distributed, extensible, redundant architecture. > > My concern is that a lot of the discussion on and use cases for Hadoop is > regarding data processing with MapReduce and - from what I understand - > using HDFS for the purpose of input for MapReduce jobs. My other concern is > vague indication that it's not a 'real-time' system. We may be using > MapReduce in small components of the application, but it will most likely be > in file access analysis rather than any processing on the files themselves. > > In other words, what I really want is a distributed, resilient, scalable > filesystem. > > Is Hadoop suitable if we just use this facility, or would I be misusing it > and inviting grief? > > M -- Harsh J
