Added SA_Mapper.py with POC code that reads in batches of tweets that need sentiment data and then adds a record with fake data one by one.
Updated SA_Mapper.py to now continuously grab batches of tweets and fake-process them. It also restricts itself to one batch per 5 seconds, which eventually will be important when there aren't that many tweets per batch.
refactored sa_mapper.py to be a basic POC mapper script that hadoop would actually want. created a new sa_worker.py script that now includes some incomplete POC code for using EMR + S3 to set some fake data.
Fleshed out EMR portion of SA_Worker.py. Ready to start testing.
Adding print statements for debugging (logging isn't in master yet) and fleshing out SA_* scripts to debug EMR job failures.
Fixed SA_Mapper.py so it works on EMR.
Fleshed out SA_Worker.py and broke out code into different functions.
Added a sa_reducer.py script. It's an indentity script + it does some formatting.
Parameterized the tweet_batch query string and increased the default batch size.
Added scaffolding for a set of unit tests for SA_Worker.py. A lot more work is needed to setup a proper test environment for the tests since every method needs access to one or more databases or other cloud resources.
Improved SA_Worker to have both an EMR threshold and seperate batch size. Also broke out EMR args into seperate variables with descriptive comments. Fixed a couple bugs as well.
Cleaned up and polished up SA_Mapper.py and SA_Worker.py.
Merge branch 'SA_Harness'