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1. install VMware on the local machine
2. import Hadoop server from http://www.cloudera.com/hadoop-training-virtual-machine^{Image Removed}
3. fire VM up
4. To use Streamers add system variable:
   export SJAR=/usr/lib/hadoop/contrib/streaming/hadoop-0.20.1+133-streaming.jar
   Now you can writhe M?R in any language
5. upload Shakespeare text to HDFS (Hadoop Distributed File System)
   cd ~/git/data
   tar vzxf shakespeare.tar.gz
   check nothig is in HDFS
   hadoop fs -ls /user/training
   add unpacked text gile to HDFS and check again
   hadoop fs -put input /user/training/inputShak
6. (source) (target)
   hadoop fs -ls /user/training
7. Execute M/R job using 'cat' & 'wc'

   Code Block
   hadoop jar $SJAR \ -mapper cat \ -reducer wc \ -input inputShak \ -output outputShak

   1. inspect output in
      hadoop fs -cat outputShak/p*
      175376 948516 5398106
8. Task: write own Map & Reduce counting frequency of words:
   mapper : read text data from stdin
   write "<key> <value>" to stdout (<key>=word, <value>=1)
   example:
   $ echo "foo foo quux labs foo bar quux" | ./mapper.py
   1. Python Mapper

      Code Block
      title mapp1.py borderStyle solid
      #!/usr/bin/env python # my 1st mapper: writes <word> 1 import sys data = sys.stdin.readlines() for ln in data: L=ln.split() for key in L: if len(key)>1: print key,1

      reducer : read a stream of "<word> 1" from stdin
      write "<word> <count>" to stdout

      Code Block
      title redu1.py borderStyle solid
      #!/usr/bin/env python # my 1st reducer: reads: <word> <vlue., sums key values from the same consecutive key, writes <word> <sum> import sys data = sys.stdin.readlines() myKey="" myVal=0 for ln in data: #print ln, L=ln.split() #print L nw=len(L)/2 for i in range(nw): #print i key=L[0+2*i] val=int(L[2*i+1]) #print key,val,nw if myKey==key: myVal=myVal+val else: if len(myKey)>0: print myKey, myVal, myKey=key myVal=val if len(myKey)>0: print myKey, myVal,

   2. Execute:

      Code Block
      hadoop jar $SJAR \ -mapper $(pwd)/mapp1.py \ -reducer $(pwd)/redu1.py \ -input inputShak \ -output outputShak3

Cloudera - my 1st EC2 cluster deployed

1. follow instruction http://archive.cloudera.com/docs/ec2.html^{Image Removed}
   1. Item 2.1 . I uploaded 3 tar files: 'client script', 'boto', and 'simplejson'.
      • Un-tarred all 3: tar vzxf ....
      • execute twice , in 'boto' and 'simplejson' directories

        Code Block
        sudo python setup.py install

      • move hadoop-ec2 to permanent place & add to path (for easier use)

        Code Block
        tar vzxf cloudera-for-hadoop-on-ec2-py-0.3.0-beta..tar.gz sudo mv cloudera-for-hadoop-on-ec2-py-0.3.0-beta /opt/ export HADOOP_EC2_HOME=/opt/cloudera-for-hadoop-on-ec2-py-0.3.0-beta export PATH=$PATH:$HADOOP_EC2_HOME

      • exported by hand environment variables
        AWS_ACCESS_KEY_ID - Your AWS Access Key ID
        AWS_SECRET_ACCESS_KEY - Your AWS Secret Access Key
      • create a directory called ~/.hadoop-ec2 w/ file ec2-clusters.cfg with content:

        Code Block
        [my-hadoop-cluster] ami=ami-6159bf08 instance_type=m1.small key_name=janAmazonKey2 availability_zone=us-east-1c private_key=/home/training/.ec2/ ssh_options=-i %(private_key)s -o StrictHostKeyChecking=no

      • filer a cluster of 1 server+2 nodes
        hadoop-ec2 launch-cluster my-hadoop-cluster 2
      • define bunch of variables in  /usr/src/hadoop/contrib/ec2/bin/hadoop-ec2-env.sh

1+2 machines are up and running:

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More advance instruction about Running Hadoop on Amazon EC2

http://wiki.apache.org/hadoop/AmazonEC2^{Image Removed}