python中Groupby和list理解的头痛

Question

我从Hadoop教程中得到这个。它是一个reducer，它基本上从stdin接收（单词，count）对，并对它们求和。在

def read_mapper_output(file, separator='\t'):
    for line in file:
        yield line.rstrip().split(separator, 1)

def main(separator='\t'):
    data = read_mapper_output(sys.stdin, separator=separator)
    for current_word, group in groupby(data, itemgetter(0)):
        try:
            total_uppercount = sum(int(count) for current_word, count in group)
            print "%s%s%d" % (current_word, separator, total_count)
        except ValueError:
            pass

现在，我希望能够接受元组（word，count1，count2），但是这个groupby和{}业务对我来说是完全难以理解的。我现在怎么用第二个值来修改它呢？ 一、 输入是（字，count1，count2），输出是（word，count1，count2）。在

编辑1:

^{pr2}$

这是一个Hadoop作业，因此输出如下：

11/11/23 18:44:21 INFO streaming.StreamJob:  map 100%  reduce 0%
11/11/23 18:44:30 INFO streaming.StreamJob:  map 100%  reduce 17%
11/11/23 18:44:33 INFO streaming.StreamJob:  map 100%  reduce 2%
11/11/23 18:44:42 INFO streaming.StreamJob:  map 100%  reduce 12%
11/11/23 18:44:45 INFO streaming.StreamJob:  map 100%  reduce 0%
11/11/23 18:44:51 INFO streaming.StreamJob:  map 100%  reduce 3%
11/11/23 18:44:54 INFO streaming.StreamJob:  map 100%  reduce 7%
11/11/23 18:44:57 INFO streaming.StreamJob:  map 100%  reduce 0%
11/11/23 18:45:05 INFO streaming.StreamJob:  map 100%  reduce 2%
11/11/23 18:45:06 INFO streaming.StreamJob:  map 100%  reduce 8%
11/11/23 18:45:08 INFO streaming.StreamJob:  map 100%  reduce 7%
11/11/23 18:45:09 INFO streaming.StreamJob:  map 100%  reduce 3%
11/11/23 18:45:12 INFO streaming.StreamJob:  map 100%  reduce 100%
...
11/11/23 18:45:12 ERROR streaming.StreamJob: Job not Successful!

从日志中：

java.lang.RuntimeException: PipeMapRed.waitOutputThreads(): subprocess failed with code 1
    at org.apache.hadoop.streaming.PipeMapRed.waitOutputThreads(PipeMapRed.java:311)
    at org.apache.hadoop.streaming.PipeMapRed.mapRedFinished(PipeMapRed.java:545)
    at org.apache.hadoop.streaming.PipeReducer.close(PipeReducer.java:137)
    at org.apache.hadoop.mapred.ReduceTask.runOldReducer(ReduceTask.java:473)
    at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:411)
    at org.apache.hadoop.mapred.Child.main(Child.java:170)

java.lang.RuntimeException: PipeMapRed.waitOutputThreads(): subprocess failed with code 1
    at org.apache.hadoop.streaming.PipeMapRed.waitOutputThreads(PipeMapRed.java:311)
    at org.apache.hadoop.streaming.PipeMapRed.mapRedFinished(PipeMapRed.java:545)
    at org.apache.hadoop.streaming.PipeReducer.close(PipeReducer.java:137)
    at org.apache.hadoop.mapred.ReduceTask.runOldReducer(ReduceTask.java:473)
    at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:411)
    at org.apache.hadoop.mapred.Child.main(Child.java:170)

Shuffle Error: Exceeded MAX_FAILED_UNIQUE_FETCHES; bailing-out.

Answer 1

from collections import defaultdict

def main(separator='\t'):
    data = read_mapper_output(sys.stdin, separator=separator)
    counts = defaultdict(lambda: [0, 0])
    for word, (count1, count2) in data:
        values = counts[word]
        values[0] += count1
        values[1] += count2

    for word, (count1, count2) in counts.iteritems():
        print('{0}\t{1}\t{2}'.format(word, count1, count2))