Some university's big data project.
Author: Kalev Kalda Sikes
Id: 100425828
Dt: 2015-03-05
This code is written in rust, a relatively new language. To compile, you'll need both the cargo and rust packages. On Archlinux, these are available in the standard repositories and can be installed with a quick sudo pacman -Syu rust cargo. On other platforms installation methods may vary.
At the time of writing, the cargo and rust package versions are as follows:
community/cargo 0.8.0-1
Rust package manager
community/rust 1:1.6.0-1
Systems programming language focused on safety, speed and concurrency
To build the project for debugging, a normal cargo build is sufficient. Before running any experiments, however, one must build an optimized 'release'. This can be done with cargo build --release
The two main executables are target/release/apriori and target/release/pcy ( or alternatively target/debug/*). There are also two other executables test_apriori and test_pcy, which have more verbose output and slightly 'lighter' default settings, which are intended for code-testing purposes.
Each executable should be invoked in the following format:
$executable [ -b buffer_size ] [ -s support_threshold ] [ data_file ]
For apriori and pcy the default values of these args are buffer_size=16, support_threshold=0.01, and datafile="data/retail.dat".
There are two main experiments - src/support_exp.sh and src/subset_exp.sh. These can be invoked directly, or with args specifying the algorithm, support thresholds, or data files to run the experiment on. For details, see the scripts themselves.
Additionally, there are two more scripts - src/run_subset_exp.sh and src/run_support_exp.sh, which were written for running batches of experiments on a four-core machine.
Finally, if on has the netflix dataset located at data/netflix.dat, one can use the src/run_netflix.sh script for running the pcy executable against it.