Installing things on the EMR cluster requires using a bootstrap script. There are two versions that do roughly the same thing. They are: emr_packages_nltk.sh and emr_packages.sh . The first downloads the nltk language models from s3 and the second downloads the nltk language models from the internet. The emr_packages_nltk.sh is significantly faster than emr_packages.sh, but it requires that the user download the data first and then upload it to s3.
$ mkdir nltk_data
$ python -m nltk.downloader -d ./nltk_data all
$ tar -zcvf nltk_data.tgz
Then either through s3 command line or the web user interface, upload the data to s3.
$ hadoop fs -put nltk_data.tgz s3://<bucket_name>/some/dir
Look in the hadoop/mr directory. That is where all of the python scripts are that run hadoop. An example job is as follows:
$ cd hadoop/python
$ zip -r rdt.mod rdt
$ mv rdt.mod ../mr
$ hadoop fs -put small_sample.json /in
$ ./mr_clean.py /in /clean
That is the pattern that all of the scripts use. If you read the mr_*.py scripts if shows the parameters necessary to run each mapreduce job. The rdt.mod contains the rdt-python module. This module is necessary to run anything using nltk and the custom module..: