parallel.py: Pool: apply_async(): Return a result object like multiprocessing.Pool.apply_async()

bin/map: Use new parallel.py for parallel processing

Added parallel.py for parallel processing

bin/map: Use dummy synchronous Pool implementation if not using parallel processing

bin/map: Use multiprocessing instead of pp for parallel processing because it's easier to use (it uses the Python threading API and doesn't require providing all the functions a task calls). Allow the user to set the cpus option to to use all system CPUs (needed because in test mode, the default is 0 CPUs to turn off parallel processing).

disown_all, stop_imports: Use /bin/bash instead of /bin/sh because array subscripting is used

input.Makefile: Editing import: Use $(datasrc) instead of $(db) since $(db) is only set for DB-source inputs

input.Makefile: Import: If profile is on and test mode is on, output formatted profile stats to stdout

sql.py: index_cols(): Cache return values in db.index_cols

bin/map: Don't import pp unless cpus != 0 because it's slow and doesn't need to happen if we're not using parallelization. cpus option defaults to 0 in test mode so tests run faster.