You must write a short proposal (1-2 pages), describing the application you will implement using the DataCutter middleware. The application you choose should be one with functionality that can be partitioned into a set of interacting components/filters, with data flowing between the components on DataCutter streams. You will also need a reasonable sized dataset to test your application on. Since you have a 500MB disk quota on the cluster (redleader), your dataset should be smaller than that.
In addition to the data server you will implement using DataCutter, you will also have to provide a GUI client for generating requests/queries to the server, and viewing results. You can build this however you want, but keep it relatively simple and use good existing tools (e.g., Java Swing, or other packages for building GUIs).
For the interim report, you should expand on your proposal to make explicit the details of your DataCutter application. That includes a precise description of the data you are using (and how much data you have), and of the queries you will support. You should also fully describe the DataCutter filters you are implementing to process the queries. Some description of the user interface for the application is also required. The report should expand on the proposal, so will be longer, perhaps 3 or 4 pages.
You will run your DataCutter application on the red/blue cluster, so that's where you should do your development work. DataCutter is installed on redleader in ~chansen/work/DataCutter-2.1/ , with documentation in doc/ , binaries in bin/ , etc. You should be able to set up your environment to use the software directly from that directory, but use your filter code and configuration files from your directory. See the documentation for details. Questions about DataCutter details should be directed to Christian Hansen.