mrjob is a Python module that helps you write and run Hadoop Streaming jobs.
mrjob fully supports Amazon's Elastic MapReduce (EMR) service, which allows you to buy time on a Hadoop cluster on an hourly basis. It also works with your own Hadoop cluster.
Installation:
python setup.py install
Setting up EMR on Amazon
* create an Amazon Web Services account: http://aws.amazon.com/
* sign up for Elastic MapReduce: http://aws.amazon.com/elasticmapreduce/
* Get your access and secret keys (go to http://aws.amazon.com/account/ and click on "Security Credentials") and set the environment variables $AWS_ACCESS_KEY_ID and $AWS_SECRET_ACCESS_KEY accordingly
Try it out!
# locally
python mrjob/examples/mr_word_freq_count.py README.md > counts
# on EMR
python mrjob/examples/mr_word_freq_count.py README.md -r emr > counts
# on your Hadoop cluster
python mrjob/examples/mr_word_freq_count.py README.md -r hadoop > counts
Advanced Configuration
To run in other AWS regions, upload your source tree, run make, and use other advanced mrjob features, you'll need to set up mrjob.conf. mrjob looks for its conf file in:
* ~/.mrjob
* mrjob.conf anywhere in your $PYTHONPATH
* /etc/mrjob.conf
See mrjob.conf.example for more information.
Product's homepage
Here are some key features of "mrjob":
· Run jobs on EMR, your own Hadoop cluster, or locally (for testing).
· Write multi-step jobs (one map-reduce step feeds into the next)
· Duplicate your production environment inside Hadoop
· Upload your source tree and put it in your job's $PYTHONPATH
· Run make and other setup scripts
· Set environment variables (e.g. $TZ)
· Easily install python packages from tarballs (EMR only)
· Setup handled transparently by mrjob.conf config file
· Automatically interpret error logs from EMR
· SSH tunnel to hadoop job tracker on EMR
· Minimal setup
· To run on EMR, set $AWS_ACCESS_KEY_ID and $AWS_SECRET_ACCESS_KEY
· To run on your Hadoop cluster, set $HADOOP_HOME
Requirements:
· Python
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