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README

## Getting Started on Hadoop
## Paco Nathan <ceteri@gmail.com>
##
## Silicon Valley Cloud Computing Meetup
## http://www.meetup.com/cloudcomputing/calendar/13911740/
## Mountain View, 2010-07-19

GitHub src repo:
    http://github.com/ceteri/ceteri-mapred

Presentation slides available here in Keynote format or 
online at SlideShare:
    doc/enron.key
    http://www.slideshare.net/pacoid/getting-started-on-hadoop


See the "WordCount" example at:
    bin/run_wc.sh

See the "Enron Email Dataset" demo at:
    bin/run_enron.sh

R statistics demo:
    thresh.R, thresh.tsv

Gephi graph demo:
    graph.gephi


## to run your own code on Elastic MapReduce

    1. create a bucket in S3
    2. copy the Python scripts into a "src" folder there
    3. determine some subset of the email message input
	cat msgs.tsv | head -1000 > input
    4. copy "input" to your S3 "src" folder
    5. follow examples in slide deck, based on params below


## Hadoop job flow 1 on Elastic MapReduce

-input s3n://ceteri-mapred/enron/src/input 
-output s3n://ceteri-mapred/enron/src/output 
-mapper '"python map_parse.py http://ceteri-mapred.s3.amazonaws.com/ stopwords"'
-reducer '"python red_idf.py 2500"'
-cacheFile s3n://ceteri-mapred/enron/src/map_parse.py#map_parse.py
-cacheFile s3n://ceteri-mapred/enron/src/red_idf.py#red_idf.py
-cacheFile s3n://ceteri-mapred/enron/src/stopwords#stopwords

## Hadoop job flow 2 on Elastic MapReduce

-input s3n://ceteri-mapred/enron/src/output 
-output s3n://ceteri-mapred/enron/src/filter 
-mapper '"python map_filter.py"'
-reducer '"python red_filter.py 0.0633"'
-cacheFile s3n://ceteri-mapred/enron/src/map_filter.py#map_filter.py
-cacheFile s3n://ceteri-mapred/enron/src/red_filter.py#red_filter.py

## after downloading the partition file named "filter" from S3, then
## run the following command to build a lexicon:

cat filter/part-* | sort -k1 -k4 -nr > lexicon