def main():
friendships = open(sys.argv[1])
MapReduce.execute(friendships, mapper, reducer)
def main():
# Assumes first argument is a file of json objects formatted as strings,
#one per line.
MapReduce.execute(open(sys.argv[1]), mapper2, reducer2)
import sys
from MapReduce import *
fmr=MapReduce()
def reducer(person,count_list):
fmr.emit((person,sum(count_list)))
def mapper(record):
fmr.emit_intermediate(record[0],1)
if __name__=='__main__':
fdata=open(sys.argv[1])
fmr.execute(fdata,mapper,reducer)
import sys
from MapReduce import *
indexmr = MapReduce()
def mapper(record):
book = record[0]
words = record[1].split()
for word in words:
indexmr.emit_intermediate(word, book)
def reducer(word, books):
indexmr.emit((word, books))
if __name__ == '__main__':
data = open(sys.argv[1])
indexmr.execute(data, mapper, reducer)
from MapReduce import *
import sys
mr = MapReduce()
def mapper(record):
mr.emit_intermediate((record[0], record[1]), 1)
mr.emit_intermediate((record[1], record[0]), 1)
def reducer(key, list_of_values):
if len(list_of_values) > 1:
return
mr.emit(key)
inputdata = open(sys.argv[1])
mr.execute(inputdata, mapper, reducer)
import sys
from MapReduce import *
dnarm = MapReduce()
def mapper(record):
kind = record[0]
trimseq = record[1][0:-10]
dnarm.emit_intermediate(trimseq, kind)
def reducer(trimseq, kinds):
dnarm.emit((trimseq, kinds))
if __name__ == '__main__':
DNAseq = open(sys.argv[1])
dnarm.execute(DNAseq, mapper, reducer)
print[i[1] for i in dnarm.result]
def main():
persons = open(sys.argv[1])
MapReduce.execute(persons, mapper, reducer)
def main():
MapReduce.execute(open(sys.argv[1]), mapper, reducer)
import sys
from MapReduce import *
joinmr=MapReduce()
def mapper(record):
key=record[1]
value=record
joinmr.emit_intermediate(key,value)
def reducer(orderid,ord_list):
order=[record[2:] for record in ord_list if record[0]=='order']
item=[record[2:] for record in ord_list if record[0]=='line_item']
for orec in order:
for irec in item:
joinmr.emit(tuple([orderid]+orec+irec))
if __name__=='__main__':
jsdata=open(sys.argv[1])
joinmr.execute(jsdata,mapper,reducer)
count=0
for i in joinmr.result:
count+=1
print 'record N0.',count,i
import sys
from MapReduce import *
dnarm=MapReduce()
def mapper(record):
kind=record[0]
trimseq=record[1][0:-10]
dnarm.emit_intermediate(trimseq,kind)
def reducer(trimseq,kinds):
dnarm.emit((trimseq,kinds))
if __name__=='__main__':
DNAseq=open(sys.argv[1])
dnarm.execute(DNAseq,mapper,reducer)
print [i[1] for i in dnarm.result]
def main():
records_file = open(sys.argv[1])
MapReduce.execute(records_file, mapper, reducer)
import sys
from MapReduce import *
fmr = MapReduce()
def reducer(person, count_list):
fmr.emit((person, sum(count_list)))
def mapper(record):
fmr.emit_intermediate(record[0], 1)
if __name__ == '__main__':
fdata = open(sys.argv[1])
fmr.execute(fdata, mapper, reducer)
def main():
friendships = open(sys.argv[1])
MapReduce.execute(friendships, mapper, reducer)
docid.add(record[0].encode('utf-8'))
term.add(record[1].encode('utf-8'))
docid = list(docid)
term = list(term)
conn.close()
#pre-define the sizes of a&b, which are L*M&M*N
M = len(docid)
matmr = MapReduce()
def mapper(record):
for m in range(M + 1):
matmr.emit_intermediate((record[0], m), ('a', record[1], record[2]))
matmr.emit_intermediate((m, record[0]), ('b', record[1], record[2]))
def reducer(key, klist):
d = {}
d['a'] = {}
d['b'] = {}
maxm = 0
for t in klist:
d[t[0]][t[1]] = t[2]
mult = sum([d['a'].get(i, 0) * d['b'].get(i, 0) for i in term])
matmr.emit((key[0], key[1], mult))
if __name__ == '__main__':
matmr.execute(matrix, mapper, reducer)
import sys
from MapReduce import *
indexmr=MapReduce()
def mapper(record):
book=record[0]
words=record[1].split()
for word in words:
indexmr.emit_intermediate(word,book)
def reducer(word,books):
indexmr.emit((word,books))
if __name__=='__main__':
data=open(sys.argv[1])
indexmr.execute(data,mapper,reducer)
import sys
from MapReduce import *
joinmr = MapReduce()
def mapper(record):
key = record[1]
value = record
joinmr.emit_intermediate(key, value)
def reducer(orderid, ord_list):
order = [record[2:] for record in ord_list if record[0] == 'order']
item = [record[2:] for record in ord_list if record[0] == 'line_item']
for orec in order:
for irec in item:
joinmr.emit(tuple([orderid] + orec + irec))
if __name__ == '__main__':
jsdata = open(sys.argv[1])
joinmr.execute(jsdata, mapper, reducer)
count = 0
for i in joinmr.result:
count += 1
print 'record N0.', count, i
def main():
dna = open(sys.argv[1])
MapReduce.execute(dna, mapper, reducer)
def main ():
# Assumes first argument is a file of json objects formatted as strings,
#one per line.
MapReduce.execute(open(sys.argv[1]), mapper2, reducer2)
def main():
dna = open(sys.argv[1])
MapReduce.execute(dna, mapper, reducer)
for record in cursor:
matrix.append(record)
docid.add(record[0].encode('utf-8'))
term.add(record[1].encode('utf-8'))
docid=list(docid)
term=list(term)
conn.close()
#pre-define the sizes of a&b, which are L*M&M*N
M=len(docid)
matmr=MapReduce()
def mapper(record):
for m in range(M+1):
matmr.emit_intermediate((record[0],m),('a',record[1],record[2]))
matmr.emit_intermediate((m,record[0]),('b',record[1],record[2]))
def reducer(key,klist):
d={}
d['a']={}
d['b']={}
maxm=0
for t in klist:
d[t[0]][t[1]]=t[2]
mult=sum([d['a'].get(i,0)*d['b'].get(i,0) for i in term])
matmr.emit((key[0],key[1],mult))
if __name__=='__main__':
matmr.execute(matrix,mapper,reducer)
def main():
persons = open(sys.argv[1])
MapReduce.execute(persons, mapper, reducer)
