Peregrine is a workload optimization platform for self-tuning cloud query engines. Please see the Peregrine paper for more details:

Peregrine: Workload Optimization for Cloud Query Engines. Alekh Jindal, Hiren Patel, Abhishek Roy, Shi Qiao, Zhicheng Yin, Rathijit Sen, Subru Krishnan. Symposium on Cloud Computing (SoCC), 2019.

Currently, we are releasing a dataset simulator for resource allocation in 9,561 production big data pipelines. Stay tuned for more to come.

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

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This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.

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MIT License