221f9c7 Nov 30, 2013
100 lines (78 sloc) 3.32 KB
# Copyright 2011 Yelp
# Copyright 2013 David Marin
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# See the License for the specific language governing permissions and
# limitations under the License.
"""For any word that appears in a document, compute stats about which
words come next (including percentage).
This is meant as a simple demonstration of why SORT_VALUES is useful.
from mrjob.job import MRJob
from mrjob.step import MRStep
import re
WORD_RE = re.compile(r"[\w']+")
class MRNextWordStats(MRJob):
def steps(self):
return [MRStep(mapper=self.m_find_words,
def m_find_words(self, _, line):
"""Tokenize lines, and look for pairs of adjacent words.
Yield (prev_word, word), 1 and (prev_word, '*'), 1 for each pair
prev_word = None
for word in WORD_RE.findall(line):
word = word.lower()
if prev_word is not None:
# total up the number of times prev_word appears
# and the number of times next_word appears after it
yield (prev_word, '*'), 1
yield (prev_word, word), 1
prev_word = word
def c_combine_counts(self, key, counts):
"""Sum up all those 1s before passing data off to the reducer"""
yield key, sum(counts)
def r_sum_counts(self, key, counts):
"""Compute the number of times each pair of words appears, and the
number of times the first word in a pair appears, and send it to
a reducer that keys on the first word in the pair.
count = sum(counts)
prev_word, word = key
if word == '*':
# we want total to arrive at r_compute_stats first, so
# prefix it with "A", which comes before "B"
yield prev_word, ('A: total', count)
yield prev_word, ('B: stats', (word, count))
def r_compute_stats(self, prev_word, value):
"""For each pair of words, compute how many times it appears,
how many times the first word appears in a pair, and the percentage
of time the second word follows the first.
This relies on values appearing in sorted order; we need the total
number of times the first word appears before we can compute the
percentage for each second word.
total = None
for value_type, data in value:
if value_type == 'A: total':
total = data
assert value_type == 'B: stats'
word, count = data
# A comes before B, so total should already be set
percent = 100.0 * count / total
yield (prev_word, word), (total, count, percent)
if __name__ == '__main__':