CSC352 Homework 4 Solution

--D. Thiebaut 20:24, 25 April 2010 (UTC)

---

Problem #1: Timeline

Several observations were in order:

• The cluster only has 5 task-tracker nodes
• The default for Hadoop is two map tasks per task-tracker per job.
• This explains the maximum of 10 map tasks running first, then stopping, and then closing down, then 6 map tasks taking over, with an overlap of 4 map tasks.
• 4 files of approximately 180 MB comprise the input. Hadoop splits input files into splits of 64 MB.
• 180 MB will correspond to 3 or 4 splits, depending on the exact size of the file. This means between 12 to 16 splits for the 4 files.

Because we see that 16 (12+4) map tasks run altogether, we deduce that we had 16 splits total, requiring 16 tasks. 12 ran first, then were taken down while 4 more were started.

Problem #2

Below is a Map/Reduce pair of Python streaming programs for a job similar to what was required. Instead of reporting the unique categories, the program return the categories and a list of Ids of wiki pages in which they appear.

Examples of output

category:(10th century in ireland)	[10130001]category:(1976 films)	[10000001]
category:(argentine films)	[10000001]
category:(economy of côte d'ivoire)	[10160001]
category:(estuaries in england)	[100001,200002]
category:(hospitals in north carolina)	[1010001]
category:(lists of hospitals in the united states)	[1010001]

Mapper

hadoop@hadoop1:~/352/dft/hw4$ cat mapper_cat.py 
#!/usr/bin/env python
# mapper_cat.py
# D. Thiebaut
# 
# parses a wiki page that is in xml format
# and included in <xml> ... </xml> tags.
# Example:
#
#<xml>
#<title>Breydon Water</title>
#<id>100001</id>
#<contributors>
#<contrib>
#<ip>89.240.43.102</ip>
#
#<length>3119</length></contrib>
#</contributors>
#<categories>
#<cat>Estuaries in England</cat>
#<cat>Ramsar sites in England</cat>
#<cat>Royal Society for the Protection of Birds reserves in England</cat>
#<cat>Norfolk Broads</cat>
#<cat>Sites of Special Scientific Interest in Norfolk</cat>
#</categories>
#<pagelinks>
#<page>Arthur Henry Patterson</page>
#<page>Arthur Ransome</page>
#<page>Avocets</page>
#<page>Bewick's Swan</page>
#</pagelinks>
#<text>
#Image. Breydon-north.jpg thumb 250px ... Broads . Category. Sites of Special Scientific Interest in Norfolk . . . .
#</text>
#</xml>
#
# the program outputs the categories
# 
# cat 10000001.xml | ./mapper.py 
#  
#
# 1976 films 10000001
# Argentine films 10000001
# films 4 10000001
# category 3 10000001
# argentine 3 10000001
# 1976 3 10000001
# spanish 2 10000001
# language 2 10000001
# spanishlanguage 1 10000001
# que 1 10000001
# list 1 10000001
#

import sys


def grab( tag, xml ):
    """grabs the text between <tag> and </tag> in the xml text"""
    try:
        index1 = xml.find( '<%s>' % tag )
        index2 = xml.find( '</%s>' % tag, index1 )
        return xml[ index1+len( '<%s>' % tag ): index2 ]
    except:
        return ""

def grabAll( tag, xml ):
    """grabs all the strings between <tag> and </tag> in xml, and 
    returns them in a list"""
    index2 = 0
    list   = []
    while True:
        index1 = xml.find( '<%s>' % tag, index2 )
        if index1==-1: break
        index2 = xml.find( '</%s>' % tag, index1 )
        if index2==-1: break
        list.append( xml[ index1+len( '<%s>' % tag): index2 ] )
    return list
    
def processInput( debug=False ):
    #--- accumulate input lines from stdin ---
    xmlText = ""
    for line in sys.stdin:
        xmlText += line.lower()
    
    #--- grag the Id, and the categories ---
    id           = grab( "id", xmlText )
    categoryList = grabAll( "cat", xmlText )
    return ( id, categoryList )


def main( debug=False ):
    #--- get page Id, categories (if user wants them), and text ---
    id, categoryList  = processInput( debug )

    for cat in categoryList:
        print "%s\t%s" % ( cat, id )

    #--- debugging information ---
    if debug:
        print "-"*60
        print "DEBUG"
        print "-"*60
        print "id = ", id
        for cat in categoryList:
            print "cat:", cat
        print "-"*60
    
main( False )

Reducer

#!/usr/bin/env python
import sys
 
#--- get ready to read category, Id pairs ---
lastCategory = None
listOfIds = [] 

#--- input comes from STDIN ---
for line in sys.stdin:
    #--- remove leading and trailing whitespace ---
    line = line.strip()
    category, Id = line.split('\t', 1)

    #--- accumulate Ids for the same category ---
    if category==lastCategory:
        listOfIds.append( Id )
    else:
        if lastCategory is not None:
            print "category:(%s)\t[%s]" % ( lastCategory, ','.join( listOfIds ) )
        lastCategory = category
        listOfIds = [ Id ]


#--- write last category processed to stdout ---
if len( listOfIds )!= 0:
    print 'category:(%s)\t[%s]' % ( lastCategory, ','.join( listOfIds ) )

Problem #3

Mapper

#!/usr/bin/env python
# mapper_word.py
# D. Thiebaut
# 
# parses a wiki page that is in xml format
# and included in <xml> ... </xml> tags.
# Example:
#
#<xml>
#<title>Breydon Water</title>
#<id>100001</id>
#<contributors>
#<contrib>
#<ip>89.240.43.102</ip>
#
#<length>3119</length></contrib>
#</contributors>
#<categories>
#<cat>Estuaries in England</cat>
#<cat>Ramsar sites in England</cat>
#<cat>Royal Society for the Protection of Birds reserves in England</cat>
#<cat>Norfolk Broads</cat>
#<cat>Sites of Special Scientific Interest in Norfolk</cat>
#</categories>
#<pagelinks>
#<page>Arthur Henry Patterson</page>
#<page>Arthur Ransome</page>
#<page>Avocets</page>
#<page>Bewick's Swan</page>
#</pagelinks>
#<text>
#Image. Breydon-north.jpg thumb 250px ... Broads . Category. Sites of Special Scientific Interest in Norfolk . . . .
#</text>
#</xml>
#
# the program outputs the five most frequent words.
#
# ivoire	2
#aquatic	5
# estuary	10
# photo	1
# rob 	4
# years	1

import sys
import string


stopwords = {'all': 1, "she'll": 1, "don't": 1, 'being': 1, 'over': 1, 'through': 1, 'yourselves': 1, 'its': 1, 
             'before': 1, "he's": 1, "when's": 1, "we've": 1, 'had': 1, 'should': 1, "he'd": 1, 'to': 1, 
             'only': 1, "there's": 1, 'those': 1, 'under': 1, 'has': 1, "haven't": 1, 'do': 1, 'them': 1, 
             'his': 1, "they'll": 1, 'very': 1, "who's": 1, "they'd": 1, 'cannot': 1, "you've": 1, 'they': 1, 
             'not': 1, 'during': 1, 'yourself': 1, 'him': 1, 'nor': 1, "we'll": 1, 'did': 1, "they've": 1, 
             'this': 1, 'she': 1, 'each': 1, "won't": 1, 'where': 1, "mustn't": 1, "isn't": 1, "i'll": 1, 
             "why's": 1, 'because': 1, "you'd": 1, 'doing': 1, 'some': 1, 'up': 1, 'are': 1, 'further': 1, 
             'out': 1, 'what': 1, 'for': 1, 'while': 1, "wasn't": 1, 'does': 1, "shouldn't": 1, 'above': 1, 
             'between': 1, 'be': 1, 'we': 1, 'who': 1, "you're": 1, 'were': 1, 'here': 1, 'hers': 1, "aren't": 1, 
             'by': 1, 'both': 1, 'about': 1, 'would': 1, 'of': 1, 'could': 1, 'against': 1, "i'd": 1, 
             "weren't": 1, "i'm": 1, 'or': 1, "can't": 1, 'own': 1, 'into': 1, 'whom': 1, 'down': 1, "hadn't": 1, 
             "couldn't": 1, 'your': 1, "doesn't": 1, 'from': 1, "how's": 1, 'her': 1, 'their': 1, "it's": 1, 
             'there': 1, 'been': 1, 'why': 1, 'few': 1, 'too': 1, 'themselves': 1, 'was': 1, 'until': 1, 
             'more': 1, 'himself': 1, "where's": 1, "i've": 1, 'with': 1, "didn't": 1, "what's": 1, 'but': 1, 
             'herself': 1, 'than': 1, "here's": 1, 'he': 1, 'me': 1, "they're": 1, 'myself': 1, 'these': 1, 
             "hasn't": 1, 'below': 1, 'ought': 1, 'theirs': 1, 'my': 1, "wouldn't": 1, "we'd": 1, 'and': 1, 
             'then': 1, 'is': 1, 'am': 1, 'it': 1, 'an': 1, 'as': 1, 'itself': 1, 'at': 1, 'have': 1, 'in': 1, 
             'any': 1, 'if': 1, 'again': 1, 'no': 1, 'that': 1, 'when': 1, 'same': 1, 'how': 1, 'other': 1, 
             'which': 1, 'you': 1, "shan't": 1, ' ourselves': 1, 'our': 1, 'after': 1, "let's": 1, 'most': 1, 
             'ours ': 1, 'such': 1, 'on': 1, "he'll": 1, 'a': 1, 'off': 1, 'i': 1, "she'd": 1, 'yours': 1, 
             "you'll": 1, 'so': 1, "we're": 1, "she's": 1, 'the': 1, "that's": 1, 'having': 1, 'once': 1, 's':1}


def grab( tag, xml ):
    """grabs string between <tag> and </tag> in xml string"""
    try:
        index1 = xml.find( '<%s>' % tag )
        index2 = xml.find( '</%s>' % tag )
        return xml[ index1+len( '<%s>' % tag ): index2 ]
    except:
        return ""


def processInput( debug=False ):
    #--- accumulate input lines from stdin ---
    xmlText = ""
    for line in sys.stdin:
        xmlText += line.lower()
    
    #--- grab text and Id from xml input ---
    text = grab( "text", xmlText )
    id   = grab( "id", xmlText )

    return ( id, text )

def getMostFreq( text, debug=False ):
    """computes 5 most frequent words"""
    global stopwords

    table = string.maketrans( "", "" )
    punctuation = '!"#$%&()*+,-./:;<=>?@[\\]^_`{|}~'
    text  = text.translate( table, punctuation )
    words = text.lower().split()
    wordDico = {}
    for word in words:
        if stopwords.has_key( word ):
            continue
        if wordDico.has_key( word ):
            wordDico[ word ] += 1
        else:
            wordDico[ word ] = 1
    
    L = [ (freq,word) for (word,freq) in wordDico.items() ]
    L.sort()
    L = L[-10:]
    L.reverse()
    return L

def main( debug=False ):
    #--- get Id and text from stdin ---
    id, text = processInput( debug )

    #--- output most frquent words, if requested for ---
    mostFreqWords = getMostFreq( text, debug )
    for freq, word in mostFreqWords:
        print "%s\t%s" % ( word, freq )

    #--- debugging information ---
    if debug:
        print "-"*60
        print "DEBUG"
        print "-"*60
        print "id = ", id
        print "text = ", text[0:20],"...", text[-20:]
        print "mostFreqWords = ", mostFreqWords
        print "-"*60

    
main( False )

Reducer

#!/usr/bin/env python
# reducer_word.py
# 
import sys
 
# maps words to their counts
word2count = {}
 
# input comes from STDIN
for line in sys.stdin:
    # remove leading and trailing whitespace
    line = line.strip()
 
    # parse the input we got from mapper.py
    word, count = line.split('\t', 1)
    # convert count (currently a string) to int
    try:
        count = int(count)
    except ValueError:
        continue

    try:
        word2count[word] = word2count[word]+count
    except:
        word2count[word] = count
 
# write the results to STDOUT (standard output)
for word in word2count.keys():
    print '%s\t%s'% ( word, word2count[word] )