/MTB

A time-series prediction benchmarking tool tailored to enterprise scenarios.

Primary LanguagePythonOtherNOASSERTION

WWW Visits Badge

MTB: A Time-Series Prediction Benchmarking Tool Tailored to Enterprise Scenarios

The data used by MTB comes from publicly available data from Meituan, and the raw data can be accessed from here

Introduction

MTB is a time-series prediction benchmarking tool tailored to enterprise scenarios. MTB establishes prediction performance evaluation standards that align with enterprise expectations, enabling a fair comparison of time-series prediction algorithms based on their performance with real enterprise traffic data.

Quickstart

  1. Install MTB: You can install the MTB package directly from PyPI using:

    pip install mtbenchmark

  2. Load Data: MTB implements the PyTorch dataset interface, and you can load data using the following code. For more details, refer to example.py:

    The data will be automatically downloaded from Google Drive on the first run, or you can manually download it: link.

    train_dataset = mt_dataset.MTDataset(features='svc1', split="train")
val_dataset = mt_dataset.MTDataset(features='svc1', split="val")
test_dataset = mt_dataset.MTDataset(features='svc1', split="test")

Cite

If you find this repo useful, please cite our paper.

@inproceedings{guo2024pass,
  title={PASS: Predictive Auto-Scaling System for Large-scale Enterprise Web Applications},
  author={Guo, Yunda and Ge, Jiake and Guo, Panfeng and Chai, Yunpeng and Li, Tao and Shi, Mengnan and Tu, Yang and Ouyang, Jian},
  booktitle={Proceedings of the ACM on Web Conference 2024},
  pages={2747--2758},
  year={2024}
}

License

This dataset is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).

You are free to:

  • Share: Copy and redistribute the dataset in any medium or format.
  • Adapt: Remix, transform, and build upon the dataset for any purpose, even commercially.

Attribution Requirement:
If you use this dataset, please cite it.

For full license details, see CC BY 4.0 License.