- 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 , 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 use MorphStream in your paper, please cite our work.
- [Under Review] Jianjun Zhao, Yancan Mao, Zhonghao Yang, Haikun Liu and Shuhao Zhang. Scalable Window-based Transactional Stream Processing with Non-deterministic State Access.
- [VLDBJ] Shuhao Zhang, Soto Juan and Volker Markl. A survey on transactional stream processing. The VLDB Journal, 2024
- [ICDE] Jianjun Zhao, Haikun Liu, Shuhao Zhang, Zhuohui Duan, Xiaofei Liao, Hai Jin, Yu Zhang. Fast Parallel Recovery for Transactional Stream Processing on Multicores. ICDE, 2024
- [ICDE] Siqi Xiang, Zhonghao Yang, Shuhao Zhang, Jianjun Zhao, Yancan Mao. MorphStream: Scalable Processing of Transactions over Streams. ICDE (Demo), 2024
- [SIGMOD] Yancan Mao, Jianjun Zhao, Shuhao Zhang, Haikun Liu and Volker Markl. MorphStream: Adaptive Scheduling for Scalable Transactional Stream Processing on Multicores. SIGMOD, 2023
- [ICDE] Shuhao Zhang, Yingjun Wu, Feng Zhang, Bingsheng He. Towards Concurrent Stateful Stream Processing on Multicore Processors, ICDE, 2020
- [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, 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)
@article{zhang2024survey,
title={A survey on transactional stream processing},
author={Zhang, Shuhao and Soto, Juan and Markl, Volker},
journal={The VLDB Journal},
volume={33},
number={2},
pages={451--479},
year={2024},
publisher={Springer}
}
@inproceedings{zhao2024fast,
title={Fast Parallel Recovery for Transactional Stream Processing on Multicores},
author={Zhao, Jianjun and Liu, Haikun and Zhang, Shuhao and Duan, Zhuohui and Liao, Xiaofei and Jin, Hai and Zhang, Yu},
booktitle={2024 IEEE 40th International Conference on Data Engineering (ICDE)},
pages={1478--1491},
year={2024},
organization={IEEE}
}
@inproceedings{xiang2024morphstream,
title={MorphStream: Scalable Processing of Transactions over Streams},
author={Xiang, Siqi and Yang, Zhonghao and Zhao, Jianjun and Mao, Yancan and Zhang, Shuhao},
booktitle={2024 IEEE 40th International Conference on Data Engineering (ICDE)},
pages={5485--5488},
year={2024},
organization={IEEE}
}
@inproceedings{mao2023morphstream,
title = {MorphStream: Adaptive Scheduling for Scalable Transactional Stream Processing on Multicores},
author = {Yancan Mao and Jianjun Zhao and Shuhao Zhang and Haikun Liu and Volker Markl},
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/MorphStream.pdf},
code = {https://github.com/intellistream/MorphStream},
tag = {full paper}
}
@inproceedings{zhang2020towards,
title = {Towards Concurrent Stateful Stream Processing on Multicore Processors},
author = {Zhang, Shuhao and Wu, Yingjun and Zhang, Feng and He, Bingsheng},
year = 2020,
booktitle = {2020 IEEE 36th International Conference on Data Engineering (ICDE)},
volume = {},
number = {},
pages = {1537--1548},
doi = {10.1109/ICDE48307.2020.00136}
}
@inproceedings{zhang2019briskstream,
title={Briskstream: Scaling data stream processing on shared-memory multicore architectures},
author={Zhang, Shuhao and He, Jiong and Zhou, Amelie Chi and He, Bingsheng},
booktitle={Proceedings of the 2019 International Conference on Management of Data},
pages={705--722},
year={2019}
}
@inproceedings{zhang2017revisiting,
title={Revisiting the design of data stream processing systems on multi-core processors},
author={Zhang, Shuhao and He, Bingsheng and Dahlmeier, Daniel and Zhou, Amelie Chi and Heinze, Thomas},
booktitle={2017 IEEE 33rd International conference on data engineering (ICDE)},
pages={659--670},
year={2017},
organization={IEEE}
}