Cape - a system for explaining outliers in aggregation results through counterbalancing.
Project description
Cape
Cape () is a system for explaining outliers (surprisingly low or high) aggregation function results for group-by queries in SQL. The user provides the system with a query and a surprising outcome for this query. Cape uses patterns discovered the describe trends that hold in the data in aggregation to explain such outliers.
Installation
Cape requires python 3. Install with pip:
pip install capexplain
Install from github
git clone git@github.com:IITDBGroup/cape.git capexplain
cd capexplain
python3 setup.py install
Usage
Cape provides a single binary capexplain that support multiple subcommands. The general form is:
capexplain COMMAND [OPTIONS]
Options are specific to each subcommand. Use capexplain help to see a list of supported commands and capexplain help COMMAND get more detailed help for a subcommand.
Overview
Cape currently only supports PostgreSQL as a backend database. To use Cape to explain an aggregation outlier, you first have to let cape find patterns for the table over which are you are aggregating. This an offline step that only has to be executed once for each table (unless you want to rerun pattern mining with different parameter settings).
Mining Patterns
Use capexplain mine [OPTIONS] to mine patterns. Cape will store the discovered patterns in the database.
Explaining Outliers
To explain an aggregation outlier use capexplain explain [OPTIONS].
Links
Cape is developed by researchers at Illinois Institute of Technology and Duke University. For more information and publications see the Cape project page http://www.cs.iit.edu/~dbgroup/projects/cape.html.
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