The implementation of S5P a skewness-aware vertex-cut partitioner. The work is published at ACM SIGMOD 2024.
Please cite the paper as follows:

Zezhong Ding, Yongan Xiang, Shangyou Wang, Xike Xie, S. Kevin Zhou. “Play like a Vertex: A Stackelberg Game Approach for Streaming Graph Partitioning”. In Proceedings of the 2024 International Conference on Management of Data (SIGMOD ‘24). https://arxiv.org/abs/2402.18304

We tested the program (main) on Ubuntu 20.046 LTS.

The programs require the below packages: g++, cmake, glog, gflags, boost:

sudo apt-get install libgoogle-glog-dev libgflags-dev libboost-all-dev cmake g++

#C++
cd cpp
mkdir build && cd build
cmake ..
make

#java
cd Java
#Details in Java Folder

Parameters:

• filename(inputGraphPath): path to the edge list file
• Vcount: $|V|$
• Ecount: $|E|$
• batchsize: default: 1000
• the number of partitions: $partitionNum$
• Skewness coefficient: $\tau$($\beta$)

• OK: https://snap.stanford.edu/data/com-Orkut.html
• TW: https://snap.stanford.edu/data/twitter-2010.html
• FR: https://snap.stanford.edu/data/com-Friendster.html
• LJ: https://snap.stanford.edu/data/com-LiveJournal.html
• IT: http://law.di.unimi.it/webdata/it-2004/
• UK7: http://law.di.unimi.it/webdata/uk-2007-05/
• IN: https://law.di.unimi.it/webdata/in-2004/
• SK: https://law.di.unimi.it/webdata/sk-2005/
• UK2: https://law.di.unimi.it/webdata/uk-2002/
• AR: https://law.di.unimi.it/webdata/arabic-2005/
• WB: https://law.di.unimi.it/webdata/webbase-2001/
• Synthetic Graphs (R-MAT/TrillionG): https://github.com/chan150/TrillionG (SIGMOD'17)

@article{ding2024play,
  title={Play like a Vertex: A Stackelberg Game Approach for Streaming Graph Partitioning},
  author={Ding, Zezhong and Xiang, Yongan and Wang, Shangyou and Xie, Xike and Zhou, S Kevin},
  journal={arXiv preprint arXiv:2402.18304},
  year={2024}
}