Pivotal Topic and Sentiment Analysis Engine

This demo show cases Pivotal's Topic and Sentiment Analysis Engine using MADlib and GPText. The webserver will query a back-end (internal to Pivotal) corpus of over 800 million tweets in response to a search query and display topic & sentiment analysis dashboards powered by D3.js plots.

More information on the technology behind the demo can be found here:

Pre-requisites

This demo is not self-contained. There is a webserver component and there is a backend Greenplum Database Component. This repo only contains the webserver component. To be able to get a fully functional demo, you'll have to build the back-end database, install the libraries (MADlib, GPText) and load a dataset as well. Please contact the author if you interested in going through all that.

We recommend that you install Anaconda Python for building this demo. Additionally, you will also need to install the psycopg2 library (run: conda install psycopg2 in your Anaconda environment). You should also be able to connect to the Pivotal GPDB DCA, which you to be within Pivotal PA VPN.

Configuration

You'll have to create a config file to connect to your backend database. Create a file in your home directory ~/.dbconn.config like so:

[db_connection]
user = gpadmin
password = XXXXX
hostname = 127.0.0.1 (or the IP of your DB server)
port = 5432 (the port# of your DB)
database = vatsandb (or the database you wish to connect to)

Starting the webserver

You can start the development server by running the script $TASA_HOME/tasa/deploy.This will start the dev server on localhost on port 8081.

Front-end code

Note that Ruby 2.1.1 and Bundler is required to develop and to compile the assets. A tool such as https://rvm.io/ may be useful. RVM installs both Ruby and Bundler. You may need to install RVM and bundler like so:

\curl -sSL https://get.rvm.io | bash -s stable --ruby
gem install bundler
rvm install ruby-2.1.1

Additionally you'll also need to install phantomjs for your browser (Chrome). Checkout https://bitbucket.org/ariya/phantomjs/downloads/.Start the Rails development server:

cd tasa/tasa
bundle install
bin/rails server

The Rails server serves the development assets at: http://localhost:3000. Before deploying, compile the UI assets via:

cd tasa
rake #only needed if you'd like to run all the tests, else go to step below
RAILS_ENV=production rake compile #compiles all the assets to $TASA_HOME/tasa/public/assets (not versioned on GitHub)

If rake fails complaining that the folder webserver/common/static/tasa does not exist, create it and re-run rake. Start the a development server:

./deploy

Adding a New Visualization

We have an example of how to add a time series graph in the new-visualization-example branch.

git branch -a
git checkout new-visualization-example

See the most recent commit on that branch for the example code.

PCF Deployment

If you've followed the steps above to compile the new UI assets, you can deploy your app to PCF. You'll first have to connect to your PCF endpoint, for example:

cf login -a https://api.pcf1-rdu.nasa.pivotal.io

Enter your email address, password and choose the right space to deploy your app on (ex: "demos").

The file manifest.yml defined the buildpacks and other params relevant for a cf push. The app can be pushed to your PCF instance using the following command:

cf push tasacf -f manifest.yml

User Provided Service

Create user provided service for database creds:

cf cups tasacreds -p '{"hostname":"<hostname>","username":"<user>","password":"<password>", "databasename":"<database>", "port":"<port>" }'

Bind the service to the app using:

cf bind-service tasacf tasacreds

Accessing the demo

Currently the demo is accessible at: https://tasacf.pcf1-rdu.nasa.pivotal.io/

Author

Srivatsan Ramanujam, Apr-Aug 2013

Contributors

Ofri Afek (Design)
Vinson Chuong (Dev)
Greg Cobb (Dev) 
Joelle Gernez (PM)
Jarrod Vawdrey (DS)

gaos1 / tasa