我尝试在python中使用mapreducer和dumbo库。下面是我的实验测试代码，我希望我能收到所有的记录从Map到减速机输出。

def mapper(key, value):
    fields = value.split("\t");    
    myword = fields[0] + "\t" + fields[1]
    yield myword, value

def reducer(key, values):
    for value in values:
        mypid = value
        words = value.split("\t")
    global count
    count = count + 1
    myword = str(count) + "--" + words[1]  ##to count total lines in recuder's output records
    yield myword, 1

if __name__ == "__main__":
    dumbo.run(mapper, reducer)

下面是MapReduce框架的日志。我期望“减少输入记录”等于“减少输出记录”，但事实并非如此。我的测试代码有什么问题，或者我误解了mapreducer中的某些内容？谢谢。

Map-Reduce Framework
            Map input records=405057
            Map output records=405057
            Map output bytes=107178919
            Map output materialized bytes=108467155
            Input split bytes=2496
            Combine input records=0
            Combine output records=0
            Reduce input groups=63096
            Reduce shuffle bytes=108467155
            Reduce input records=405057
            Reduce output records=63096
            Spilled Records=810114

对减速机进行如下改造：

def reducer(key, values):
    global count
    for value in values:
        mypid = value
        words = value.split("\t")

        count = count + 1
        myword = str(count) + "--" + words[1]  ##to count total lines in recuder's output records
        yield myword, 1