python - 如何使用map reduce MRJob

Question

I need to apply the map reduce function from MRJob and I can't arrive. I have a big list with two codes and a sentence, as following:

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    L = ['E-0053 C-0169  It's goig to be a good day\n', 'D-0312 B-0291 Peter has arrived late\n', 'A- 
    0417 B-0187  for more information please call the following number\n']

I need to use map reduce to obtain a list that counts the number of words that have each sentences for each pair of combinations of letter from the code. For example, the solution with the list example would be:

enter code here
    [EC 6, DB 4, AB 8]

I've tried with:

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    C1 = [i [0] for i in L]
    C2 = [i [7] for i in L]
    C1_C2 = [C1[i]+C2[i] for i in range(len(C1))] 

    class count(MRJob):
       def mapper(self, _, C1_C2):
          [elem.split() for elem in L]
          yield C1_C2, [(len(i)-2) for i in sentence]

    def reducer(self, key, values):
       yield key, sum(values)


    count.run()

Answer 1

You could try this :

L = [
    "E-0053 C-0169  It's goig to be a good day\n", 
    "D-0312 B-0291 Peter has arrived late\n",
    "A-0417 B-0187  for more information please call the following number\n"
]
result = [i[0] + i[7] + " " + str(len(i.split()) - 2) for i in L]
print(result)

Output :

['EC 7', 'DB 4', 'AB 8']