python - 如何使用map reduce MRJob

Question

我需要从 MRJob 应用 map reduce 功能，但我无法到达。 我有一个包含两个代码和一个句子的大列表，如下所示：

enter code here
    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']

我需要使用 map reduce 来获取一个列表，该列表计算代码中每对字母组合的每个句子的单词数。 例如，列表示例的解决方案是：

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

我试过：

enter code here

    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

你可以试试这个：

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)

输出 ：

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