Write mapreduce programs in python that would run in Hadoop setup in cloud

I am working with input, output, python and Mapreduce framework in Linux cloud. My project is to write multiple mappers and reducers using python to solve and submit solutions to 3 different problem scenarios , all of the solutions tested in Hadoop set up in Linux cloud. (strictly restricted to writing programs that would work on the cloud- I am using AWS Cloud). For each problem, along with the mapper and reducer, you will be supposed to create a final program (or script) to combine the partial output files into one file. The combining program is supposed to only be combining the part files and sorting them, not affecting the stateless-ness of the mapper and reducer in any way. This project is due on the 13th of October(12th preferable). Will appreciate if you could quote a reasonable charge for completing this task on time. The output files expected are- [login to view URL], [login to view URL] (For Problem 1), [login to view URL], [login to view URL] (For problem 2a OR 2b), [login to view URL] and [login to view URL] for Problem 3. The output can be just python codes written with proper formatting and comments in notepad++. But MOST important pointers are- 1. Mappers and reducers cannot be trivial. They have to be STATELESS. 2. The code has to be tested on a local Hadoop setup first. (only write programs that you know will run in the cloud) 3. For each problem, along with your mapper and reducer, create a final program (or script) to combine the partial output files into one file. Your combining program should only be combining the part files and sorting them. If you are doing any extra work in the combining program, then you likely did something incorrect in the mapper or reducer. Please read through the instructions carefully and let me know if you have any further questions. I can send the exact project requirements, relevant attachments and any other info you might need asap, once you confirm if this is something you could do. Thanks!