1. Download the Amazon Elastic MapReduce CLI from the location below
wget http://elasticmapreduce.s3.amazonaws.com/elastic-mapreduce-ruby.zip
wget http://elasticmapreduce.s3.amazonaws.com/elastic-mapreduce-ruby.zip
2. Unzip it
unzip elastic-mapreduce-ruby.zip
unzip elastic-mapreduce-ruby.zip
3. Create a shell script with following code (create_jf.sh)
ruby elastic-mapreduce \
-v \
—create \
—alive \
—region “us-east-1” \
—access-id <your_access_id> \
—private-key <your_private_kay> \
—key-pair <your_key_pair> \
—ami-version latest \
—visible-to-all-users \
—hbase \
—name “HBASE from CLI” \
—instance-group MASTER \
—instance-count 1 \
—instance-type m1.large \
—instance-group CORE \
—instance-count 1 \
—instance-type m1.large \
—pig-interactive \
—pig-versions latest \
—hive-interactive \
—hive-versions latest \
—bootstrap-action “s3://elasticmapreduce/bootstrap-actions/configure-hadoop” \
—args “-m,mapred.tasktracker.map.tasks.maximum=6,-m,mapred.tasktracker.reduce.tasks.maximum=2”
4. Create job flow
bash create_jf.sh
5. Monitor job flow from AWS console
Copy the job flow Id you get after successful run of create_jf.sh and search it with AWS EMR console.
bash create_jf.sh
5. Monitor job flow from AWS console
Copy the job flow Id you get after successful run of create_jf.sh and search it with AWS EMR console.
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