'type': int,
'args': ['oid'],
'function': lambda v: v
},
}))
engines.append(select)
counties_grouper = Group(select.output(), {'oid': lambda a, b: a == b})
engines.append(counties_grouper)
joiner = Join(counties_grouper.output(), geonames_aggregate.output())
engines.append(joiner)
mux_streams.append(joiner.output())
# mux_streams.append(counties_select.output())
mux = Mux(*mux_streams)
engines.append(mux)
result_stack = ResultFile(
'results.txt',
mux.output(),
)
engines.append(result_stack)
#result_stack = ResultStack(
# mux.output(),
#)
#engines.append(result_stack)
info_queue = Queue()
data_schema.append(Attribute('rowid', int, True))
data_source = DBTable('test.db', 'person', data_schema)
# definition of the data source
#data_source = CSVFile('test.csv', data_schema)
data_accessors = []
selects = []
for i in range(0, 1):
# create a data accessor
data_accessor = DataAccessor(demux, data_source, FindRange)
name_age_combiner = NameAgeCombiner(data_accessor.output().schema())
selects.append(Select(data_accessor.output(), name_age_combiner))
data_accessors.append(data_accessor)
mux = Mux(*[s.output() for s in selects])
#name_age_combiner_reverse = NameAgeCombinerReverse(demux.schema())
#select2 = Select(demux, name_age_combiner_reverse)
#name_age_combiner = NameAgeCombiner(data_accessor.output().schema())
#select = Select(data_accessor.output(), name_age_combiner)
#name_age_combiner_reverse = NameAgeCombinerReverse(data_accessor.output().schema())
#select2 = Select(data_accessor.output(), name_age_combiner_reverse)
result_stack = ResultStack(
# query_streamer.output(),
mux.output(),
# data_accessor.output(),
)
