value = row[index]
if value != 0:
f.write('(' + str(index) + ',' + str(value) + ')\t')
f.write('\n')
for (tid, feature) in per_cluster.collect():
f.write(tid + '\t' + str(count) + '\n')
fi.write(tid + '\t' + str(count) + '\n')
"""
for (tid, feature) in per_cluster.collect():
f.write(tid)
for row in feature.toarray():
for unit in range(len(row)):
f.write('\t')
f.write(str(row[unit]))
f.write('\n')
"""
f.close()
fi.close()
sc.stop()
return
if __name__ == '__main__':
weibo_file = '../data/no_weibo.txt'
result_file = 'results/initial.txt'
print "start", now()
load_cut_to_rdd(local2mfs(weibo_file), result_file)
print "end", now()
for (tid, feature) in per_cluster.collect():
f.write(tid)
"""
for row in feature.toarray():
for unit in range(len(row)):
f.write('\t')
f.write(str(row[unit]))
"""
f.write('\n')
f.close()
sc.stop()
return
if __name__ == '__main__':
# topic = "APEC-微博"
# print topic
input_file = "../data/source_chaijing.txt"
output_file = "../data/out_chaijing2.txt"
result_file = "results/result_chaijing.txt"
print "step1", now()
# load_data_from_mongo(topic, input_file)
print "step2", now()
# cut_words_local(input_file, output_file)
print "step3", now()
load_cut_to_rdd(local2mfs(output_file), result_file)
print "end", now()
f.write(str(unit))
f.write("\n")
for (index, (dist, num)) in cluster_variance.collect():
f.write(str(index))
f.write("\t")
f.write(str(dist))
f.write("\t")
f.write(str(num))
f.write("\n")
f.close()
sc.stop()
return
if __name__ == "__main__":
topic = "APEC-微博"
print topic
input_file = "data/source_APEC.txt"
output_file = "data/out_APEC.txt"
result_file = "data/result_APEC.txt"
print "step1", now()
load_data_from_mongo(topic, input_file)
print "step2", now()
cut_words_local(input_file, output_file)
print "step3", now()
load_cut_to_rdd(local2mfs(output_file), result_file)
print "end", now()
for index in range(len(row)):
value = row[index]
if value != 0:
f.write('('+str(index)+','+str(value)+')\t')
f.write('\n')
for (tid, feature) in per_cluster.collect():
f.write(tid+'\t'+str(count)+'\n')
fi.write(tid+'\t'+str(count)+'\n')
"""
for (tid, feature) in per_cluster.collect():
f.write(tid)
for row in feature.toarray():
for unit in range(len(row)):
f.write('\t')
f.write(str(row[unit]))
f.write('\n')
"""
f.close()
fi.close()
sc.stop()
return
if __name__ == '__main__':
weibo_file = '../data/no_weibo.txt'
result_file = 'results/initial.txt'
print "start", now()
load_cut_to_rdd(local2mfs(weibo_file), result_file)
print "end", now()