skip to navigation
skip to content

mrjob 0.4

Python MapReduce framework

Package Documentation

Latest Version: 0.4.6


.. image::

mrjob is a Python 2.5+ package that helps you write and run Hadoop Streaming

`v0.3.4.1 documentation <http:"" mrjob=""/>`_

`v0.4-dev documentation <http:"" en="" latest=""/>`_

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.


From PyPI:

``pip install mrjob``

From source:

``python install``

A Simple Map Reduce Job

Code for this example and more live in ``mrjob/examples``.

.. code:: python

"""The classic MapReduce job: count the frequency of words.
from mrjob.job import MRJob
import re

WORD_RE = re.compile(r"[\w']+")

class MRWordFreqCount(MRJob):

def mapper(self, _, line):
for word in WORD_RE.findall(line):
yield (word.lower(), 1)

def combiner(self, word, counts):
yield (word, sum(counts))

def reducer(self, word, counts):
yield (word, sum(counts))

if __name__ == '__main__':

Try It Out!


# locally
python mrjob/examples/ README.rst > counts
# on EMR
python mrjob/examples/ README.rst -r emr > counts
# on your Hadoop cluster
python mrjob/examples/ README.rst -r hadoop > counts

Setting up EMR on Amazon

* create an `Amazon Web Services account <http:""/>`_
* sign up for `Elastic MapReduce <http:"" elasticmapreduce=""/>`_
* Get your access and secret keys (click "Security Credentials" on
`your account page <http:"" account=""/>`_)
* Set the environment variables ``$AWS_ACCESS_KEY_ID`` and
``$AWS_SECRET_ACCESS_KEY`` accordingly

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:

* The contents of ``$MRJOB_CONF``
* ``~/.mrjob.conf``
* ``/etc/mrjob.conf``

See `the mrjob.conf documentation
<http:"" mrjob="" configs-conf.html="">`_ for more information.

Project Links

* `Source code <http:"" yelp="" mrjob="">`_
* `Documentation <http:"" mrjob=""/>`_
* `Discussion group <http:"" group="" mrjob="">`_


* `Hadoop MapReduce <http:"" mapreduce=""/>`_
* `Elastic MapReduce <http:"" documentation="" elasticmapreduce=""/>`_

More Information

* `PyCon 2011 mrjob overview <http:"" pycon-us-videos-2009-2010-2011="" pycon-2011-mrjob-distributed-computing-for-everyone-4898987=""/>`_
* `Introduction to Recommendations and MapReduce with mrjob <http:"" 2012="" 08="" introduction-to-recommendations-with.html="">`_
(`source code <https:"" marcelcaraciolo="" recsys-mapreduce-mrjob="">`_)
* `Social Graph Analysis Using Elastic MapReduce and PyPy <http:"" 2011="" 05="" 04="" social-graph-analysis-using-elastic-mapreduce-and-pypy="">`_

Thanks to `Greg Killion <>`_
(` <http:""/>`_) for the logo.  
File Type Py Version Uploaded on Size
mrjob-0.4.tar.gz (md5) Source 2013-05-01 148KB
  • Downloads (All Versions):
  • 3108 downloads in the last day
  • 24256 downloads in the last week
  • 84218 downloads in the last month