Introduction

The original goal of visitante was to calculate various web analytic metric as defined by Avinash Kaushik (http://www.kaushik.net/avinash/) on the Hadoop, Spark and Storm platform. However, it has evolved into a general purpose log analytic and mining solution, beyond web server logs.

It also includes customer or marketing analytic solution. Since customer behavior data is mostly captured in logs, there is a close relationship between customer analytics and log analytics.

Philosophy

• Simple and easy to use batch and real time web analytic
• Highly configurable

Blogs

The following blogs of mine are good source of details of visitante

• http://pkghosh.wordpress.com/2012/06/05/big-web-analytic/
• http://pkghosh.wordpress.com/2012/08/10/big-web-checkout-abandonment/
• https://pkghosh.wordpress.com/2014/10/05/tracking-web-site-bounce-rate-in-real-time/
• https://pkghosh.wordpress.com/2016/01/19/detecting-incidents-with-context-from-log-data/
• https://pkghosh.wordpress.com/2016/02/23/customer-lifetime-value-present-and-future/

Solutions

• Hadoop based batch analytic for

  • Num of pages visited
  • Total time spent
  • Last page visited
  • Flow status (e.g., whether checkout flow was entered, entered but not completed or completed)
  • Incident detection
  • Pattern based event detection with context
  • Customer life time value

• Storm based real time analytic for

  • Bounce rate
  • Visit depth distribution

Build

For Hadoop 1

• mvn clean install

For Hadoop 2 (non yarn)

• git checkout nuovo
• mvn clean install

For Hadoop 2 (yarn)

• git checkout nuovo
• mvn clean install -P yarn

For spark

• Build chombo first in master branch with
  • mvn clean install
  • sbt publishLocal
• Build chombo-spark in chombo/spark directory
  • sbt clean package

Need help?

Please feel free to email me at [email protected]

Contribution

Contributors are welcome. Please email me at [email protected]