This is aim to Python version of cdsw-simple-serving.

This repo has:

• data preparation with RDD
• built a simple machine learning pipeline with Spark.ml
• export built model
• example web server code for scoring

Currently, this repo doesn't have following features:

• export built model as PMML

pip install -r requirements.txt -c constraints.txt

• HDFS_HOST for handling HDFS files via hdfs package

• as a template for collaboration with Data Engineer and Data Scientist
• create job dependencies from data preparation to model serving

1. Create virtualenv for your app: virtualenv -p python2 venv && source ./venv/bin/activate
2. Install dependent libraries: pip install -r requirements-webapp.txt
3. Run example app: spark-submit serving/web_app.py

then, you can POST data as follows:

$ curl -v -H "Accept: application/json" -H "Content-type: application/json" -X POST -d '{"Temperature":23.18,"Humidity":27.272,"Light":426,"CO2":721.25,"HumidityRatio":0.00478}' http://localhost:5000/api/predict

or, if you want to use gunicorn

1. pip install -r requirements-webapp.txt
2. Download spark repo
3. Install pyspark dependencies: cd some-spark-director/python && pip install -e
4. Run example app: cd serving; gunicorn web_app:app --log-file -