- This project aims at building a scalable transactional stream processing engine on modern hardware. It allows ACID transactions to be run directly on streaming data. It shares similar project vision with Flink StreamingLedger from Data Artisans (https://www.ververica.com/hubfs/Ververica/Docs/[2018-08]-dA-Streaming-Ledger-whitepaper.pdf), but MorphStream emphsizes more on improving system performance leveraging modern multicore processors.
- MorphStream is built based on our previous work of TStream (ICDE"20) but with significant changes: the codebase are exclusive.
- The code is still under active development and more features will be introduced. We are also actively maintaining the project wiki. Please checkout it for more detailed desciptions.
- We welcome your contributions, if you are interested to contribute to the project, please fork and submit a PR. If you have questions, feel free to log an issue or write an email to me: shuhao_zhang AT sutd.edu.sg
If you use MorphStream in your paper, please cite our work.
- [ICDE] Shuhao Zhang, Bingsheng He, Daniel Dahlmeier, Amelie Chi Zhou, Thomas Heinze. Revisiting the design of data stream processing systems on multi-core processors, ICDE, 2017 (code: https://github.com/ShuhaoZhangTony/ProfilingStudy)
- [SIGMOD] Shuhao Zhang, Jiong He, Chi Zhou (Amelie), Bingsheng He. BriskStream: Scaling Stream Processing on Multicore Architectures, SIGMOD, 2019 (code: https://github.com/Xtra-Computing/briskstream)
- [ICDE] Shuhao Zhang, Yingjun Wu, Feng Zhang, Bingsheng He. Towards Concurrent Stateful Stream Processing on Multicore Processors, ICDE, 2020
- [xxx] We have an anonymized submission under review. Stay tuned.
@INPROCEEDINGS{9101749,
author={Zhang, Shuhao and Wu, Yingjun and Zhang, Feng and He, Bingsheng},
booktitle={2020 IEEE 36th International Conference on Data Engineering (ICDE)},
title={Towards Concurrent Stateful Stream Processing on Multicore Processors},
year={2020},
volume={},
number={},
pages={1537-1548},
doi={10.1109/ICDE48307.2020.00136}
}