CaJaDe

The source codes are located src/ folder. After importing databases to postgres, simply go to src/ folder,

It is recommended that you use virtualenv or similar virtual environment to deploy the code,

1. once you are in the virtual environment, run

pip install requirements.txt

2. CaJaDe uses GProM as the backend provenance generation system, please refer to GProM to install along with your Postgresql before going forward
3. We use NBA dataset as the demo dataset. User can download different sizes of the dataset in here. After extracting the .sql file, run psql -h [hostname] -p [port] -U [username] -d [your precreated db name] < [your .sql file]to import database to your local Postgresql, e.g, psql -h localhost -p 5432 -U postgres -d nba_db < nba.sql
4. After you've done first 3 steps, you are ready to go :)

run

python experiments.py -h

user could select specify the following flags to run experiments

usage: experiments.py [-h] [-M] [-F] [-o] [-s] [-m] [-H] [-P] [-t] -U  -p  -d

Running experiments of CaJaDe

optional arguments:
  -h, --help            show this help message and exit
  -M , --maximum_edges 
                        Maximum number of edges allowed in a join graph
                        (default: 3)
  -F , --f1_sample_rate 
                        Sample rate of apt when calculating the f1 score
                        (default: 1.0)
  -o , --optimized      use opt or not (y: yes, n: no), (default: y)
  -s , --db_size        scale factor of database, (default: 1.0)
  -m , --min_recall_threshold 
                        recall threshold when calculating f1 score (default:
                        1.0)
  -H , --db_host        database host, (default: localhost)
  -P , --port           database port, (default: 5432)
  -t , --f1_calc_type   f1 score type (s sample, o original), (default: s)

required named arguments:
  -U , --user_name      owner of the database (required)
  -p , --password       password to the database (required)
  -d , --db_name        database name (required)

and follow the instructions popped out to run the experiment.

The result of the experiment will be saved under the schema name exp_%Y_%m_%d_%H_%M_%S inside the database user chooses to use.