...

1. Start your map reduce cluster, when you are trying out new jobs for the first time, specifying --alive will keep your hosts alive as you work through the any bugs. But in general you do not want to run jobs with --alive because you'll need to remember to explicitly shut the hosts down when the job is done.

   Code Block

   ~/WordCount>/work/platform/bin/elastic-mapreduce-cli/elastic-mapreduce --credentials ~/.ssh/$USER-credentials.json --create --master-instance-type=m1.small \ --slave-instance-type=m1.small --num-instances=3 --enable-debugging --bootstrap-action s3://sagebio-$USER/scripts/bootstrapLatestR.sh --name RWordCount --alive Created job flow j-1H8GKG5L6WAB4 ~/WordCount>/work/platform/bin/elastic-mapreduce-cli/elastic-mapreduce --credentials ~/.ssh/$USER-credentials.json --list j-1H8GKG5L6WAB4 STARTING RWordCount PENDING Setup Hadoop Debugging

2. Look around on the AWS Console:
   • See your new job listed in the Elastic MapReduce tab
   • See the individual hosts listed in the EC2 tab
3. Create your job step file

   Code Block

   ~/WordCount>cat wordCount.json [ { "Name": "R Word Count MapReduce Step 1: small input file", "ActionOnFailure": "CANCEL_AND_WAIT", "HadoopJarStep": { "Jar": "/home/hadoop/contrib/streaming/hadoop-streaming.jar", "Args": [ "-input","s3n://sagebio-ndeflaux/input/AnInputFile.txt", "-output","s3n://sagebio-ndeflaux/output/wordCountTry1", "-mapper","s3n://sagebio-ndeflaux/scripts/mapper.R", "-reducer","s3n://sagebio-ndeflaux/scripts/reducer.R", ] } }, { "Name": "R Word Count MapReduce Step 2: lots of input", "ActionOnFailure": "CANCEL_AND_WAIT", "HadoopJarStep": { "Jar": "/home/hadoop/contrib/streaming/hadoop-streaming.jar", "Args": [ "-input","s3://elasticmapreduce/samples/wordcount/input", "-output","s3n://sagebio-ndeflaux/output/wordCountTry2", "-mapper","s3n://sagebio-ndeflaux/scripts/mapper.R", "-reducer","s3n://sagebio-ndeflaux/scripts/reducer.R", ] } } ]

4. Add the steps to your jobflow

   Code Block
   ~/WordCount>/work/platform/bin/elastic-mapreduce-cli/elastic-mapreduce --credentials ~/.ssh/$USER-credentials.json --json wordCount.json --jobflow j-1H8GKG5L6WAB4 Added jobflow steps

5. Check progress by "Debugging" your job flow
   Image Added
6. When your jobs are done, look for your output in your S3 bucket
   Image Added

What next?

• Take a look at the Elastic MapReduce FAQ
• Take a look at the other Computation Examples