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Data generation using pure python, HAWQ (with PL/Python), or MapReduce (streaming via python)

Instructions are included for each of the 3. MapReduce version is in the early stages and it's not currently recommended.

TODO:

  • location of locations_partitions.csv is hardcoded (fixed?)

  • come up with a realistic template so numbers aren't out of whack

  • script to calculate expected outputs based on profiles

  • for transactions, give the option to provide either a folder of all profiles to iterate through or just one json (automatic checking)

  • user input to generate config files

  • test output against profiles

  • add shell scripts to install python packages

  • add shell scripts to fix hard coding for HAWQ and MR

  • clean up HAWQ and MR code

  • add more/better data

  • improve performance of MapReduce

  • Spark streaming?

  • create_pickles doesn't run if the number of years doesn't match the profile inputs

  • work on making datasets repeatable via random seed

  • script to replace hashbang with which python

  • script to replace hard links

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fake data generation of credit card transactions using python

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