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SURE

This repo is the code implementation of paper "Fast and Fine-grained Autoscaler for Streaming Jobs with Reinforcement Learning (IJCAI'2022)".

Code Structure

  • run.py is the entrance file.
  • env is the implementation of stream processing system and a gym wrapper.
  • model contains the implementation of our Neural Variational Subgraph Sampler and Mutual Information loss.
  • schedule_algo is the RL algorithm.
  • utils is the folder containing helper classes and functions.

Citation

If you find our paper or code useful, please cite the following BibTex:

@inproceedings{ijcai2022p0080,
  title     = {Fast and Fine-grained Autoscaler for Streaming Jobs with Reinforcement Learning},
  author    = {Xing, Mingzhe and Mao, Hangyu and Xiao, Zhen},
  booktitle = {Proceedings of the Thirty-First International Joint Conference on
               Artificial Intelligence, {IJCAI-22}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
}