Analysis of the most frequent co-stars in IMDb with Hadoop. [Alice Aardvark, Bob Bobcat, Carol Chimera. Group 42]
State what is the main goal of the project. State what sorts of question(s) you want to answer or what sort of system you want to build. (Questions may be non-technical -- e.g., is there a global correlation between coffee consumption and research output -- so long as they require data analysis or other technical solutions.)
Describe the raw dataset that you considered for your project. Where did it come from? Why was it chosen? What information does it contain? What format was it in? What size was it? How many lines/records? Provide links.
Detail the methods used during the project. Provide an overview of the techniques/technologies used, why you used them and how you used them. Refer to the source-code delivered with the project. Describe any problems you encountered.
Detail the results of the project. Different projects will have different types of results; e.g., run-times or result sizes, evaluation of the methods you're comparing, the interface of the system you've built, and/or some of the results of the data analysis you conducted.
Summarise main lessons learnt. What was easy? What was difficult? What could have been done better or more efficiently?
You can use this for key code snippets that you don't want to clutter the main text.