如何通过识别python Hadoop中的键来处理Mapreduce

时间:2018-03-03 15:41:50

标签: python hadoop mapreduce reducers

我有两个来自地图功能的关键值:纽约和其他。所以,我的关键输出是:NY 1,或者其他1.只有这两种情况。

我的地图功能:

    #!/usr/bin/env python
    import sys
    import csv
    import string

    reader = csv.reader(sys.stdin, delimiter=',')
    for entry in reader:
        if len(entry) == 22:
            registration_state=entry[16]
            print('{0}\t{1}'.format(registration_state,int(1)))

现在我需要使用reducer来处理地图输出。我的减少:

#!/usr/bin/env python
import sys
import string


currentkey = None
ny = 0
other = 0
# input comes from STDIN (stream data that goes to the program)
for line in sys.stdin:

    #Remove leading and trailing whitespace
    line = line.strip()

    #Get key/value 
    key, values = line.split('\t', 1)  
    values = int(values)
#If we are still on the same key...
    if key == 'NY':
        ny = ny + 1
    #Otherwise, if this is a new key...
    else:
        #If this is a new key and not the first key we've seen
        other = other + 1


#Compute/output result for the last key 
print('{0}\t{1}'.format('NY',ny))
print('{0}\t{1}'.format('Other',other))

从这些中,mapreduce将提供两个输出结果文件,每个文件包含NY和Others输出。即一个包含:NY 1248,其他4677;另一个:纽约0,其他1000.这是因为两个缩小了地图的输出分割,所以生成了两个结果,通过组合(合并)最终输出将得到结果。

但是,我想更改我的reduce或map函数,以便只对一个键进行每个简化处理,即一个仅减少处理NY作为键值,另一个处理其他键。我希望有一个结果包含:

NY 1258, Others 0; Another: NY 0, Others 5677. 

如何调整功能以达到我期望的效果?

1 个答案:

答案 0 :(得分:0)

可能你需要使用Python迭代器和生成器。 这个link给出了一个很好的例子。我尝试用相同的(未经测试的)

重新编写代码

映射器:

#!/usr/bin/env python
"""A more advanced Mapper, using Python iterators and generators."""

import sys

def main(separator='\t'):
    reader = csv.reader(sys.stdin, delimiter=',')
    for entry in reader:
    if len(entry) == 22:
        registration_state=entry[16]
        print '%s%s%d' % (registration_state, separator, 1)

if __name__ == "__main__":
    main()

减速机:

!/usr/bin/env python
"""A more advanced Reducer, using Python iterators and generators."""

from itertools import groupby
from operator import itemgetter
import sys

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

def main(separator='\t'):
    for current_word, group in groupby(data, itemgetter(0)):
        try:
            total_count = sum(int(count) for current_word, count in group)
            print "%s%s%d" % (current_word, separator, total_count)
        except ValueError:
            # count was not a number, so silently discard this item
            pass

if __name__ == "__main__":
    main()