mrjob is a Python package 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.
Some important features:
- 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, install simplejson and make sure $HADOOP_HOME is set.
python setup.py install
Try it out!
# locally python mrjob/examples/mr_word_freq_count.py README.rst > counts # on EMR python mrjob/examples/mr_word_freq_count.py README.rst -r emr > counts # on your Hadoop cluster python mrjob/examples/mr_word_freq_count.py README.rst -r hadoop > counts
Setting up EMR on Amazon
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:
- The contents of $MRJOB_CONF
- ~/.mrjob (deprecated)
- mrjob.conf anywhere in your $PYTHONPATH (deprecated)
See mrjob.conf.example for more information.