Using mrjob

By February 10, 2017

Another way to run Hadoop jobs is through mrjob. Mrjob is useful for testing out smaller data on another system (such as your laptop), and later being able to run it on something larger, like a Hadoop cluster. To run an mrjob on your laptop, you can simply remove the “-r hadoop” from the command in the example we use here.

A classic example is a word count, taken from the official mrjob documentation here.

Save this file as mrjob_test.py.

"""The classic MapReduce job: count the frequency of words.
"""
from mrjob.job import MRJob
import re

WORD_RE = re.compile(r"[\w']+")


class MRWordFreqCount(MRJob):

    def mapper(self, _, line):
        for word in WORD_RE.findall(line):
            yield (word.lower(), 1)

    def combiner(self, word, counts):
        yield (word, sum(counts))

    def reducer(self, word, counts):
        yield (word, sum(counts))


if __name__ == '__main__':
     MRWordFreqCount.run()

Then, run the following command:

python mrjob_test.py -r hadoop /etc/motd

You should receive an output with the word count of the file /etc/motd. You can also try this with any other file you have that contains text.

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