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MRJob sort reducer output


MRJob sort reducer output

By : user2172438
Date : October 23 2020, 08:10 PM
I think the issue was by ths following , You can sort the values as integers in second reducer and then converting them in to the zero padded representation:
code :
import re

from mrjob.job import MRJob
from mrjob.step import MRStep

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


class MRWordFrequencyCount(MRJob):

    def steps(self):
        return [
            MRStep(
                mapper=self.mapper_extract_words, combiner=self.combine_word_counts,
                reducer=self.reducer_sum_word_counts
            ),
            MRStep(
                reducer=self.reduce_sort_counts
            )
        ]

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

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

    def reducer_sum_word_counts(self, key, values):
        yield None, (sum(values), key)

    def reduce_sort_counts(self, _, word_counts):
        for count, key in sorted(word_counts, reverse=True):
            yield ('%020d' % int(count), key)


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MRjob: Can a reducer perform 2 operations?

MRjob: Can a reducer perform 2 operations?


By : sarita
Date : March 29 2020, 07:55 AM
will be helpful for those in need Pai's solution is technically correct, but in practice this will give you a lot of strife, as setting the partitioning can be a big pain (see https://groups.google.com/forum/#!topic/mrjob/aV7bNn0sJ2k).
You can achieve this task more easily by using mrjob.step, and then creating two reducers, such as in this example: https://github.com/Yelp/mrjob/blob/master/mrjob/examples/mr_next_word_stats.py
code :
from mrjob.job import MRJob
import re
from mrjob.step import MRStep
from collections import defaultdict

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

class MRComplaintFrequencyCount(MRJob):

    def mapper(self, _, line):
        self.increment_counter('group','num_mapper_calls',1)

        #Issue is third column in csv
        issue = line.split(",")[3]

        for word in wordRe.findall(issue):
            #Send all map outputs to same reducer
            yield word.lower(), 1

    def reducer(self, key, values):
        self.increment_counter('group','num_reducer_calls',1)  
        wordCounts = defaultdict(int)
        total = 0         
        for value in values:
            word, count = value
            total+=count
            wordCounts[word]+=count

        for k,v in wordCounts.iteritems():
            # word, frequency, relative frequency 
            yield k, (v, float(v)/total)

    def combiner(self, key, values):
        self.increment_counter('group','num_combiner_calls',1) 
        yield None, (key, sum(values))


if __name__ == '__main__':
    MRComplaintFrequencyCount.run()
mrjob: suppress key (or value) in reducer output

mrjob: suppress key (or value) in reducer output


By : Ashirov Sirojiddin
Date : March 29 2020, 07:55 AM
should help you out You can use mrjob.protocol.JSONValueProtocol (notice the Value. See the documentation) as the output protocol instead of mrjob.protocol.JSONProtocol.
The documentation has more information on using custom protocols.
Passing parameters to reducer in MRjob

Passing parameters to reducer in MRjob


By : mohamed abdallah
Date : March 29 2020, 07:55 AM
fixed the issue. Will look into that further How about passing your parameters to job config and then reading them with get_jobconf_value?
Something like this:
code :
from mrjob.compat import get_jobconf_value

class MRDataQuality(MRJob):

  def reducer(self, groupId, meterList):
    ...
    startDate = get_jobconf_value("my.job.settings.startdate")
    endDate = get_jobconf_value("my.job.settings.enddate")

    for meterId in meterList:
      sys.stderr.write("Querying: " + str(meterId) + "\n")
      df = extract_meter_data(table, meterId, startDate, endDate)    
mrdq_job = MRDataQuality(args=['-r', 'hadoop', '--conf-path', 'mrjob.conf', '--jobconf', 'mapred.reduce.tasks=42', '--jobconf', 'my.job.settings.startdate=2013-06-10', '--jobconf', 'my.job.settings.enddate=2013-06-11', meterFile])
How can I write an iteration in Python using mrjob mapper reducer, for which the counter is a part of the computation in

How can I write an iteration in Python using mrjob mapper reducer, for which the counter is a part of the computation in


By : Almaksour
Date : March 29 2020, 07:55 AM
around this issue I have a program that iterates a mapper and a reducer n times consecutively. However, for each iteration, the mapper of each key-value pair computes a value that depends on n. , Why don't you try defining your count in the class?
code :
class MRWord(MRJob):
    count = []
def mapper_init_def(self):
   self.count = {}
MRJob and python - .csv file output for Reducer?

MRJob and python - .csv file output for Reducer?


By : user3853209
Date : March 29 2020, 07:55 AM
To fix this issue To manage input and output formats in mrjob, you need to use protocols.
Luckily, there is an existing package which implements a CSV protocol that you could use - https://pypi.python.org/pypi/mr3px
code :
from mr3px.csvprotocol import CsvProtocol
class CsvOutputJob(MRJob):
    ...
    OUTPUT_PROTOCOL = CsvProtocol  # write output as CSV
def reducer(self, geo_key, info_list):
    for row in info_list:
        yield (None, row) 
runners:
  emr:
    ...
    bootstrap:
      - sudo apt-get install -y python-setuptools
      - sudo easy_install pip
      - sudo pip install mr3px
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