def runner(job):
inout_opts = [("inputformat", "text"), ("outputformat", "text")]
o1 = job.additer(Parse_comunidad_contratos_mapper,
join_comunidad_contratos_reduce,
opts=inout_opts)
if __name__ == "__main__": main(runner)
class join_comunidades_provincias_contratos_reduce:
def __init__(self):
self.provincia = load_comunidades_provincias('./Comunidades_y_provincias.csv')
def __call__(self, key, value):
try:
total_contratos_mujeres = 0
total_contratos_hombres = 0
acc_mujeres = 0
acc_hombres = 0
comunidad = self.provincia.get(provincia)
provincia = key[:]
for v in values:
total_contratos_mujeres, total_contratos_hombres = v[:]
acc_mujeres += int(total_contratos_mujeres)
acc_hombres += int(total_contratos_hombres)
if contratos_mujeres > 0 and provincia in self.provincia:
total_contratos_mujeres += int(contratos_mujeres)
if contratos_hombres > 0 and provincia in self.provincia:
total_contratos_hombres += int(contratos_hombres)
yield comunidad, (acc_mujeres, acc_hombres)
except:
pass
from dumbo import main
def runner(job):
inout_opts = [("inputformat", "text"), ("outputformat", "text")]
o1 = job.additer(Parse_contratos_municipio_mapper, join_comunidades_provincias_contratos_reduce, opts=inout_opts)
if __name__ == "__main__":
main(runner)
import os
from dumbo import main, opt
@opt( "addpath", "yes" )
def mapper0( key, value ):
yield "N", key[0]
def reducer0( key, values ):
yield len(set( values )), ""
def runner( job ):
job.additer( mapper0, reducer0 )
def starter( prog ):
return
if __name__ == "__main__":
main( runner, starter )
def runner(job):
compute_svd = gopts.getintkey('svd')
mapper = mrmc.ID_MAPPER
reducer = full.FullTSQRRed2(compute_svd)
job.additer(mapper=mapper,
reducer=reducer,
opts=[('numreducetasks', str(1))])
def starter(prog):
# set the global opts
gopts.prog = prog
mat = mrmc.starter_helper(prog, True)
if not mat: return "'mat' not specified"
matname, matext = os.path.splitext(mat)
output = prog.getopt('output')
if not output:
prog.addopt('output', '%s-full-tsqr-2%s' % (matname, matext))
gopts.getintkey('svd', 0)
gopts.save_params()
if __name__ == '__main__':
dumbo.main(runner, starter)
# value = json.loads(value)
try:
key = value['prb_id']
except KeyError:
key = 'NO_PROBE_ID'
measurement_type = value['type']
value['is_failure'] = None
if measurement_type == 'ping':
detect_ping_failure(value) # mutates the dictionary
elif measurement_type == 'dns':
detect_dns_failure(value) # mutates the dictionary
elif measurement_type == 'traceroute':
detect_traceroute_failure(value) # mutates the dictionary
try:
yield (key, value['timestamp']), (value['timestamp'],
value['is_failure'], value)
except KeyError:
yield (key, 'NO_TIMESTAMP'), ('NO_TIMESTAMP', value['is_failure'],
value)
def runner(job):
job.additer(TimestampMapper)
if __name__ == "__main__":
main(runner)
if not word in self.stopwords:
yield word, 1
def normalize(self, word):
word = word.lower()
return self.lemmatizer.lemmatize(word)
def tokenize(self, sentence):
for word in wordpunct_tokenize(sentence):
yield self.normalize(word)
@property
def stopwords(self):
if not self._stopwords:
self._stopwords = nltk.corpus.stopwords.words('english')
return self._stopwords
def reducer(key, values):
yield key, sum(values)
def runner(job):
job.additer(Mapper, reducer, reducer)
def starter(prog):
excludes = prog.delopt("stopwords")
if excludes: prog.addopt("param", "stopwords="+excludes)
if __name__ == "__main__":
import dumbo
dumbo.main(runner, starter)
from dumbo import main, opt
from dumbo.lib import sumreducer
from aqualab.dumbo.util import *
import json
class ProbeMapper:
#@aquaflows.lib.parsers.Json
def __call__(self, key, value):
while type(value) == str or type(value) == unicode:
value = json.loads(value)
try:
yield value['prb_id'], value
except KeyError:
yield 'NO_PROBE_ID', value
def runner(job):
job.additer(ProbeMapper)
if __name__ == "__main__":
main(runner)
status = v[0];
# Generate the exit
if (status != "" and len(info)>0):
yield info, status
# Jobs workflow function
def runner(job):
# Step 1: Prepare users, details deliver
opts = [ ("inputformat","text"), \
("outputformat","text") ]
multimapper = MultiMapper();
multimapper.add("users", users_parser)
multimapper.add("details", deliveries_parser)
o1 = job.additer(multimapper, reducer1, \
opts=opts )
# Step 2: Get status description
multimapper = MultiMapper();
multimapper.add("status", status_parser)
o2 = job.additer(multimapper, identityreducer, \
opts=opts, input=[job.root] )
# Step 3: Join results
o3 = job.additer(identitymapper, reducer2, \
opts=opts, input=[o1, o2] )
if __name__ == "__main__":
from dumbo import main
dumbo.main(runner)
def reducer1(key, values):
""" Output:
K=>(row1, 'earthquake', 1), V=>10,
K=>(row2, 'strike', 1), V=>5
"""
yield (key, sum(values))
def mapper2(key, value):
doc_num, issue_id, word = key
occurences = value
yield (doc_num, issue_id), (word, occurences)
def reducer2(key, values):
# Pulls it all into memory but that should be ok
word_occurences = list(values)
yield key, word_occurences
def runner(job):
job.additer(mapper1, reducer1)
job.additer(mapper2, reducer2)
if __name__ == '__main__':
""" Usage: dumbo start issues_from_text.py -input /some/hdfs/input -output /some/hdfs/output -hadoop /path/to/hadoop """
import dumbo
dumbo.main(runner)
"country_code", "country_name", "region", "region_name", "city",
"postal_code", "latitude", "longitude", "area_code", "time_zone",
"metro_code"
]
saved_fields = [
"cc", "country", "st", "state", "city", "postcode", "lat", "lng",
"areacode", "tz", "metrocode"
]
for field, save_as in zip(fields, saved_fields):
val = gir[field]
if val is None: continue
d[save_as] = val
value["geo"] = d
yield key, value
def runner(job):
job.additer(Mapper)
def starter(prog):
parseArgs(prog)
if __name__ == "__main__":
main(runner, starter)
