Sesame

About

Sesame is scalable stream mining library on modern hardware written in C++

By now Sesame contains several representative real-world stream clustering algorithms and synthetic algorithms

Quick Start

Installation

pip3 install pysame

Python Example

#!python3

from pysame import Benne, Birch, BenneObj

X = [[0, 1], [0.3, 1], [-0.3, 1], [0, -1], [0.3, -1], [-0.3, -1]]

# run birch algorithm
brc = Birch(
    n_clusters=2,
    dim=2,
    distance_threshold=0.5,
)
print(brc.partial_fit(X).predict(X))

# run benne algorithm
bne = Benne(
    n_clusters=2,
    dim=2,
    distance_threshold=0.5,
    obj=BenneObj.accuracy,
)
print(bne.partial_fit(X).predict(X))

Build Sesame

Prerequisites

• gcc 12 or lator
• cmake 3.14 or later
• boost
• gflags

Checkout Source Code

git clone https://github.com/intellistream/Sesame --recursive --depth=1
cd Sesame

Build

mkdir build
cd build
cmake .. -DCMAKE_BUILD_TYPE=Release
make -j$(nproc)

Run Tests

Download the datasets from Zenodo and put them in the datasets directory:

cd Sesame/datasets
pip3 install zenodo_get
zenodo_get 8210331

Run the tests:

cd Sesame/build/test
./google_test

Real-world algorithms

Synthetic algorithms

Datasets

Datasets can download from zenodo: https://zenodo.org/records/8210331

How to Cite Sesame

• [SIGMOD 2023] Xin Wang and Zhengru Wang and Zhenyu Wu and Shuhao Zhang and Xuanhua Shi and Li Lu. Data Stream Clustering: An In-depth Empirical Study, SIGMOD, 2023

@inproceedings{wang2023sesame,
    title        = {Data Stream Clustering: An In-depth Empirical Study},
    author       = {Xin Wang and Zhengru Wang and Zhenyu Wu and Shuhao Zhang and Xuanhua Shi and Li Lu},
    year         = 2023,
    booktitle    = {Proceedings of the 2023 International Conference on Management of Data (SIGMOD)},
    location     = {Seattle, WA, USA},
    publisher    = {Association for Computing Machinery},
    address      = {New York, NY, USA},
    series       = {SIGMOD '23},
    abbr         = {SIGMOD},
    bibtex_show  = {true},
    selected     = {true},
    pdf          = {papers/Sesame.pdf},
    code         = {https://github.com/intellistream/Sesame},
    doi          = {10.1145/3589307},
    url          = {https://doi.org/10.1145/3589307}
}