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. Recently search analytics solutions have also been added
- Simple and easy to use batch and real time web analytic
- Highly configurable
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/
- https://pkghosh.wordpress.com/2019/04/24/elastic-search-or-solr-search-result-quality-evaluation-with-ncdg-on-spark/
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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
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
Please feel free to email me at [email protected]
Contributors are welcome. Please email me at [email protected]