Autotuning Systems: Techniques, Challenges, and Opportunities
Brian Kroth, Sergiy Matusevych, Yiwen Zhu
SIGMOD 2025 | June 2025
Yiwen Zhu
Principal Scientist
Papiers de Collaboration
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Rockhopper: A Robust Optimizer for Spark Configuration Tuning in Production Environment
Yiwen Zhu, Rathijit Sen, Brian Kroth, Sergiy Matusevych, Andreas Mueller, Tengfei Huang, Rahul Challapalli, Weihan Tang, Xin He, Mo Liu, Estera Kot, Sule Kahraman, Arshdeep Sekhon, Dario Bernal, Aditya Lakra, Shaily Fozdar, Dhruv Relwani, Rui Fang, Long Tian, Karuna Sagar Krishna, Ashit Gosalia, Carlo Curino, Subru Krishnan
Companion of the 2025 International Conference on Management of Data | June 2025
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MLOS in Action: Bridging the Gap Between Experimentation and Auto-Tuning in the Cloud
Brian Kroth, Sergiy Matusevych, Rana Alotaibi, Yiwen Zhu, Anja Gruenheid, Yuanyuan Tian
Proc. VLDB Endow. | October 2024, Vol 17: pp. 4269-4272
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Vertically Autoscaling Monolithic Applications with CaaSPER: Scalable Container-as-a-Service Performance Enhanced Resizing Algorithm for the Cloud
Anna Pavlenko, Joyce Cahoon, Yiwen Zhu, Brian Kroth, Michael Nelson, Andrew Carter, David Liao, Travis Wright, Jesús Camacho-Rodríguez, Karla Saur
SIGMOD | June 2024
to appear
-
Lorentz: Learned SKU Recommendation Using Profile Data
Nick Glaze, Tria McNeely, Yiwen Zhu, Matthew Gleeson, Helen Serr, Rajeev Bhopi, Subru Krishnan, Yiwen Zhu, Subru Krishnan
SIGMOD 2024 | May 2024, Vol 2: pp. 149
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VASIM: Vertical Autoscaling Simulator Toolkit
Anna Pavlenko, Karla Saur, Yiwen Zhu, Brian Kroth, Joyce Cahoon, Jesús Camacho-Rodríguez
IEEE International Conference on Data Engineering (ICDE 2024) | May 2024
-
Intelligent Pooling: Proactive Resource Provisioning in Large-scale Cloud Service
Deepak Ravikumar, Alex Yeo, Yiwen Zhu, Aditya Lakra, Harsha Nagulapalli, Santhosh Ravindran, Steve Suh, Niharika Dutta, Andrew Fogarty, Yoonjae Park, Sumeet Khushalani, Arijit Tarafdar, Kunal Parekh, Subru Krishnan, Yiwen Zhu, Subru Krishnan
Proc. VLDB Endow. | February 2024, Vol 17: pp. 1618-1627
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-
-
Demonstration of Geyser: Provenance Extraction and Applications over Data Science Scripts
Fotis Psallidas, Megan Eileen Leszczynski, Mohammad Hossein Namaki, Avrilia Floratou, Ashvin Agrawal, Konstantinos Karanasos, Subru Krishnan, Pavle Subotić, Markus Weimer, Yinghui Wu, Yiwen Zhu
ACM SIGMOD | July 2023
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Exploiting Structure in Regular Expression Queries
Ling Zhang, Shaleen Deep, Avrilia Floratou, Anja Gruenheid, Jignesh M. Patel, Yiwen Zhu
ACM SIGMOD | July 2023
-
Towards Building Autonomous Data Services on Azure
Yiwen Zhu, Yuanyuan Tian, Joyce Cahoon, Subru Krishnan, Ankita Agarwal, Rana Alotaibi, Jesús Camacho-Rodríguez, Bibin A Chundatt, Andrew Chung, Niharika Dutta, Andrew Fogarty, Anja Gruenheid, Brandon Haynes, Matteo Interlandi, Minu Iyer, Nick Jurgens, Sumeet Khushalani, Brian Kroth, Manoj Kumar, Jyoti Leeka, Sergiy Matusevych, Minni Mittal, Andreas C. Müller, Kartheek Muthyala, Harsha Nagulapalli, Yoonjae Park, Hiren Patel, Anna Pavlenko, Olga Poppe, Santhosh Ravindran, Karla Saur, Rathijit Sen, Steve Suh, Arijit Tarafdar, Kunal Waghray, Demin Wang, Carlo Curino, Raghu Ramakrishnan
ACM SIGMOD | June 2023
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Runtime Variation in Big Data Analytics
Yiwen Zhu, Rathijit Sen, Robert Horton, John Mark Agosta
ACM SIGMOD | May 2023
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-
Doppler: Automated SKU Recommendation in Migrating SQL Workloads to the Cloud
Joyce Cahoon, Wenjing Wang, Yiwen Zhu, Katherine Lin, Sean Liu, Raymond Truong, Neetu Singh, Chengcheng Wan, Alexandra M Ciortea, Sreraman Narasimhan, Subru Krishnan
VLDB 2022 | August 2022
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Data Science Through the Looking Glass
Fotis Psallidas, Yiwen Zhu, Bojan Karlaš, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos
SIGMOD Record | June 2022, Vol 51(2): pp. 30-37
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Data Science Through the Looking Glass: Analysis of Millions of GitHub Notebooks and ML.NET Pipelines
Fotis Psallidas, Yiwen Zhu, Bojan Karlaš, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos
SIGMOD Record | March 2022
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Phoebe: A Learning-based Checkpoint Optimizer
Yiwen Zhu, Matteo Interlandi, Abhishek Roy, Krishnadhan Das, Hiren Patel, Malay Bag, Hitesh Sharma, Alekh Jindal
VLDB 2021 | August 2021
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KEA: Tuning an Exabyte-Scale Data Infrastructure
Yiwen Zhu, Subru Krishnan, Konstantinos Karanasos, Isha Tarte, Conor Power, Abhishek Modi, Manoj Kumar, Deli Zhang, Deli Zhang, Kartheek Muthyala, Nick Jurgens, Sarvesh Sakalanaga, Sudhir Darbha, Minu Iyer, Ankita Agarwal, Carlo Curino
SIGMOD | June 2021
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Seagull: An Infrastructure for Load Prediction and Optimized Resource Allocation
Olga Poppe, Tayo Amuneke, Dalitso Banda, Aritra De, Ari Green, Manon Knoertzer, Ehi Nosakhare, Karthik Rajendran, Deepak Shankargouda, Meina Wang, Alan Au, Carlo Curino, Qun Guo, Alekh Jindal, Ajay Kalhan, Morgan Oslake, Sonia Parchani, Vijay Ramani, Raj Sellappan, Saikat Sen, Sheetal Shrotri, Soundararajan Srinivasan, Ping Xia, Shize Xu, Alicia Yang, Yiwen Zhu
VLDB 2021 | September 2020
Top project in Azure All Hands 2021
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Vamsa: Automated Provenance Tracking in Data Science Scripts
Mohammad Hossein Namaki, Avrilia Floratou, Fotis Psallidas, Subru Krishnan, Ashvin Agrawal, Yiwen Zhu, Markus Weimer, Yinghui Wu
KDD | August 2020
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MLOS: An Infrastructure for Automated Software Performance Engineering
Carlo Curino, Neha Godwal, Brian Kroth, Sergiy Kuryata, Greg Lapinski, Siqi Liu, Slava Oks, Olga Poppe, Adam Smiechowski, Ed Thayer, Markus Weimer, Yiwen Zhu
DEEM 2020 | June 2020
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Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML
Ashvin Agrawal, Rony Chatterjee, Carlo Curino, Avrilia Floratou, Neha Godwal, Matteo Interlandi, Alekh Jindal, Konstantinos Karanasos, Subru Krishnan, Brian Kroth, Jyoti Leeka, Kwanghyun Park, Hiren Patel, Olga Poppe, Fotis Psallidas, Raghu Ramakrishnan, Abhishek Roy, Karla Saur, Rathijit Sen, Markus Weimer, Travis Wright, Yiwen Zhu
Conference on Innovative Data Systems Research (CIDR) | January 2020
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-
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Griffon: Reasoning about Job Anomalies with Unlabeled Data in Cloud-based Platforms
Liqun Shao, Yiwen Zhu, Siqi Liu, Abhiram Eswaran, Kristin Lieber, Janhavi Mahajan, Minsoo Thigpen, Sudhir Darbha, Subru Krishnan, Soundar Srinivasan, Carlo Curino, Konstantinos Karanasos
Symposium on Cloud Computing (SoCC) | August 2019
-
-
-
Autotuning Systems: Techniques, Challenges, and Opportunities
Brian Kroth, Sergiy Matusevych, Yiwen Zhu
SIGMOD 2025 | June 2025
-
Rockhopper: A Robust Optimizer for Spark Configuration Tuning in Production Environment
Yiwen Zhu, Rathijit Sen, Brian Kroth, Sergiy Matusevych, Andreas Mueller, Tengfei Huang, Rahul Challapalli, Weihan Tang, Xin He, Mo Liu, Estera Kot, Sule Kahraman, Arshdeep Sekhon, Dario Bernal, Aditya Lakra, Shaily Fozdar, Dhruv Relwani, Rui Fang, Long Tian, Karuna Sagar Krishna, Ashit Gosalia, Carlo Curino, Subru Krishnan
Companion of the 2025 International Conference on Management of Data | June 2025
-
MLOS in Action: Bridging the Gap Between Experimentation and Auto-Tuning in the Cloud
Brian Kroth, Sergiy Matusevych, Rana Alotaibi, Yiwen Zhu, Anja Gruenheid, Yuanyuan Tian
Proc. VLDB Endow. | October 2024, Vol 17: pp. 4269-4272
-
Lorentz: Learned SKU Recommendation Using Profile Data
Nick Glaze, Tria McNeely, Yiwen Zhu, Matthew Gleeson, Helen Serr, Rajeev Bhopi, Subru Krishnan, Yiwen Zhu, Subru Krishnan
SIGMOD 2024 | May 2024, Vol 2: pp. 149
-
Intelligent Pooling: Proactive Resource Provisioning in Large-scale Cloud Service
Deepak Ravikumar, Alex Yeo, Yiwen Zhu, Aditya Lakra, Harsha Nagulapalli, Santhosh Ravindran, Steve Suh, Niharika Dutta, Andrew Fogarty, Yoonjae Park, Sumeet Khushalani, Arijit Tarafdar, Kunal Parekh, Subru Krishnan, Yiwen Zhu, Subru Krishnan
Proc. VLDB Endow. | February 2024, Vol 17: pp. 1618-1627
-
Towards Building Autonomous Data Services on Azure
Yiwen Zhu, Yuanyuan Tian, Joyce Cahoon, Subru Krishnan, Ankita Agarwal, Rana Alotaibi, Jesús Camacho-Rodríguez, Bibin A Chundatt, Andrew Chung, Niharika Dutta, Andrew Fogarty, Anja Gruenheid, Brandon Haynes, Matteo Interlandi, Minu Iyer, Nick Jurgens, Sumeet Khushalani, Brian Kroth, Manoj Kumar, Jyoti Leeka, Sergiy Matusevych, Minni Mittal, Andreas C. Müller, Kartheek Muthyala, Harsha Nagulapalli, Yoonjae Park, Hiren Patel, Anna Pavlenko, Olga Poppe, Santhosh Ravindran, Karla Saur, Rathijit Sen, Steve Suh, Arijit Tarafdar, Kunal Waghray, Demin Wang, Carlo Curino, Raghu Ramakrishnan
ACM SIGMOD | June 2023
-
Runtime Variation in Big Data Analytics
Yiwen Zhu, Rathijit Sen, Robert Horton, John Mark Agosta
ACM SIGMOD | May 2023
-
Data Science Through the Looking Glass
Fotis Psallidas, Yiwen Zhu, Bojan Karlaš, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos
SIGMOD Record | June 2022, Vol 51(2): pp. 30-37
-
Data Science Through the Looking Glass: Analysis of Millions of GitHub Notebooks and ML.NET Pipelines
Fotis Psallidas, Yiwen Zhu, Bojan Karlaš, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos
SIGMOD Record | March 2022
-
Seagull: An Infrastructure for Load Prediction and Optimized Resource Allocation
Olga Poppe, Tayo Amuneke, Dalitso Banda, Aritra De, Ari Green, Manon Knoertzer, Ehi Nosakhare, Karthik Rajendran, Deepak Shankargouda, Meina Wang, Alan Au, Carlo Curino, Qun Guo, Alekh Jindal, Ajay Kalhan, Morgan Oslake, Sonia Parchani, Vijay Ramani, Raj Sellappan, Saikat Sen, Sheetal Shrotri, Soundararajan Srinivasan, Ping Xia, Shize Xu, Alicia Yang, Yiwen Zhu
VLDB 2021 | September 2020
Top project in Azure All Hands 2021
-
MLOS: An Infrastructure for Automated Software Performance Engineering
Carlo Curino, Neha Godwal, Brian Kroth, Sergiy Kuryata, Greg Lapinski, Siqi Liu, Slava Oks, Olga Poppe, Adam Smiechowski, Ed Thayer, Markus Weimer, Yiwen Zhu
DEEM 2020 | June 2020
-
Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML
Ashvin Agrawal, Rony Chatterjee, Carlo Curino, Avrilia Floratou, Neha Godwal, Matteo Interlandi, Alekh Jindal, Konstantinos Karanasos, Subru Krishnan, Brian Kroth, Jyoti Leeka, Kwanghyun Park, Hiren Patel, Olga Poppe, Fotis Psallidas, Raghu Ramakrishnan, Abhishek Roy, Karla Saur, Rathijit Sen, Markus Weimer, Travis Wright, Yiwen Zhu
Conference on Innovative Data Systems Research (CIDR) | January 2020
-
Griffon: Reasoning about Job Anomalies with Unlabeled Data in Cloud-based Platforms
Liqun Shao, Yiwen Zhu, Siqi Liu, Abhiram Eswaran, Kristin Lieber, Janhavi Mahajan, Minsoo Thigpen, Sudhir Darbha, Subru Krishnan, Soundar Srinivasan, Carlo Curino, Konstantinos Karanasos
Symposium on Cloud Computing (SoCC) | August 2019
-
-
-
Autotuning Systems: Techniques, Challenges, and Opportunities
Brian Kroth, Sergiy Matusevych, Yiwen Zhu
SIGMOD 2025 | June 2025
-
Rockhopper: A Robust Optimizer for Spark Configuration Tuning in Production Environment
Yiwen Zhu, Rathijit Sen, Brian Kroth, Sergiy Matusevych, Andreas Mueller, Tengfei Huang, Rahul Challapalli, Weihan Tang, Xin He, Mo Liu, Estera Kot, Sule Kahraman, Arshdeep Sekhon, Dario Bernal, Aditya Lakra, Shaily Fozdar, Dhruv Relwani, Rui Fang, Long Tian, Karuna Sagar Krishna, Ashit Gosalia, Carlo Curino, Subru Krishnan
Companion of the 2025 International Conference on Management of Data | June 2025
-
Vertically Autoscaling Monolithic Applications with CaaSPER: Scalable Container-as-a-Service Performance Enhanced Resizing Algorithm for the Cloud
Anna Pavlenko, Joyce Cahoon, Yiwen Zhu, Brian Kroth, Michael Nelson, Andrew Carter, David Liao, Travis Wright, Jesús Camacho-Rodríguez, Karla Saur
SIGMOD | June 2024
to appear
-
Lorentz: Learned SKU Recommendation Using Profile Data
Nick Glaze, Tria McNeely, Yiwen Zhu, Matthew Gleeson, Helen Serr, Rajeev Bhopi, Subru Krishnan, Yiwen Zhu, Subru Krishnan
SIGMOD 2024 | May 2024, Vol 2: pp. 149
-
VASIM: Vertical Autoscaling Simulator Toolkit
Anna Pavlenko, Karla Saur, Yiwen Zhu, Brian Kroth, Joyce Cahoon, Jesús Camacho-Rodríguez
IEEE International Conference on Data Engineering (ICDE 2024) | May 2024
-
Intelligent Pooling: Proactive Resource Provisioning in Large-scale Cloud Service
Deepak Ravikumar, Alex Yeo, Yiwen Zhu, Aditya Lakra, Harsha Nagulapalli, Santhosh Ravindran, Steve Suh, Niharika Dutta, Andrew Fogarty, Yoonjae Park, Sumeet Khushalani, Arijit Tarafdar, Kunal Parekh, Subru Krishnan, Yiwen Zhu, Subru Krishnan
Proc. VLDB Endow. | February 2024, Vol 17: pp. 1618-1627
-
Demonstration of Geyser: Provenance Extraction and Applications over Data Science Scripts
Fotis Psallidas, Megan Eileen Leszczynski, Mohammad Hossein Namaki, Avrilia Floratou, Ashvin Agrawal, Konstantinos Karanasos, Subru Krishnan, Pavle Subotić, Markus Weimer, Yinghui Wu, Yiwen Zhu
ACM SIGMOD | July 2023
-
Exploiting Structure in Regular Expression Queries
Ling Zhang, Shaleen Deep, Avrilia Floratou, Anja Gruenheid, Jignesh M. Patel, Yiwen Zhu
ACM SIGMOD | July 2023
-
Towards Building Autonomous Data Services on Azure
Yiwen Zhu, Yuanyuan Tian, Joyce Cahoon, Subru Krishnan, Ankita Agarwal, Rana Alotaibi, Jesús Camacho-Rodríguez, Bibin A Chundatt, Andrew Chung, Niharika Dutta, Andrew Fogarty, Anja Gruenheid, Brandon Haynes, Matteo Interlandi, Minu Iyer, Nick Jurgens, Sumeet Khushalani, Brian Kroth, Manoj Kumar, Jyoti Leeka, Sergiy Matusevych, Minni Mittal, Andreas C. Müller, Kartheek Muthyala, Harsha Nagulapalli, Yoonjae Park, Hiren Patel, Anna Pavlenko, Olga Poppe, Santhosh Ravindran, Karla Saur, Rathijit Sen, Steve Suh, Arijit Tarafdar, Kunal Waghray, Demin Wang, Carlo Curino, Raghu Ramakrishnan
ACM SIGMOD | June 2023
-
Runtime Variation in Big Data Analytics
Yiwen Zhu, Rathijit Sen, Robert Horton, John Mark Agosta
ACM SIGMOD | May 2023
-
Doppler: Automated SKU Recommendation in Migrating SQL Workloads to the Cloud
Joyce Cahoon, Wenjing Wang, Yiwen Zhu, Katherine Lin, Sean Liu, Raymond Truong, Neetu Singh, Chengcheng Wan, Alexandra M Ciortea, Sreraman Narasimhan, Subru Krishnan
VLDB 2022 | August 2022
-
Data Science Through the Looking Glass
Fotis Psallidas, Yiwen Zhu, Bojan Karlaš, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos
SIGMOD Record | June 2022, Vol 51(2): pp. 30-37
-
Data Science Through the Looking Glass: Analysis of Millions of GitHub Notebooks and ML.NET Pipelines
Fotis Psallidas, Yiwen Zhu, Bojan Karlaš, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos
SIGMOD Record | March 2022
-
Phoebe: A Learning-based Checkpoint Optimizer
Yiwen Zhu, Matteo Interlandi, Abhishek Roy, Krishnadhan Das, Hiren Patel, Malay Bag, Hitesh Sharma, Alekh Jindal
VLDB 2021 | August 2021
-
KEA: Tuning an Exabyte-Scale Data Infrastructure
Yiwen Zhu, Subru Krishnan, Konstantinos Karanasos, Isha Tarte, Conor Power, Abhishek Modi, Manoj Kumar, Deli Zhang, Deli Zhang, Kartheek Muthyala, Nick Jurgens, Sarvesh Sakalanaga, Sudhir Darbha, Minu Iyer, Ankita Agarwal, Carlo Curino
SIGMOD | June 2021
-
Seagull: An Infrastructure for Load Prediction and Optimized Resource Allocation
Olga Poppe, Tayo Amuneke, Dalitso Banda, Aritra De, Ari Green, Manon Knoertzer, Ehi Nosakhare, Karthik Rajendran, Deepak Shankargouda, Meina Wang, Alan Au, Carlo Curino, Qun Guo, Alekh Jindal, Ajay Kalhan, Morgan Oslake, Sonia Parchani, Vijay Ramani, Raj Sellappan, Saikat Sen, Sheetal Shrotri, Soundararajan Srinivasan, Ping Xia, Shize Xu, Alicia Yang, Yiwen Zhu
VLDB 2021 | September 2020
Top project in Azure All Hands 2021
-
Vamsa: Automated Provenance Tracking in Data Science Scripts
Mohammad Hossein Namaki, Avrilia Floratou, Fotis Psallidas, Subru Krishnan, Ashvin Agrawal, Yiwen Zhu, Markus Weimer, Yinghui Wu
KDD | August 2020
-
MLOS: An Infrastructure for Automated Software Performance Engineering
Carlo Curino, Neha Godwal, Brian Kroth, Sergiy Kuryata, Greg Lapinski, Siqi Liu, Slava Oks, Olga Poppe, Adam Smiechowski, Ed Thayer, Markus Weimer, Yiwen Zhu
DEEM 2020 | June 2020
-
Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML
Ashvin Agrawal, Rony Chatterjee, Carlo Curino, Avrilia Floratou, Neha Godwal, Matteo Interlandi, Alekh Jindal, Konstantinos Karanasos, Subru Krishnan, Brian Kroth, Jyoti Leeka, Kwanghyun Park, Hiren Patel, Olga Poppe, Fotis Psallidas, Raghu Ramakrishnan, Abhishek Roy, Karla Saur, Rathijit Sen, Markus Weimer, Travis Wright, Yiwen Zhu
Conference on Innovative Data Systems Research (CIDR) | January 2020
-
Griffon: Reasoning about Job Anomalies with Unlabeled Data in Cloud-based Platforms
Liqun Shao, Yiwen Zhu, Siqi Liu, Abhiram Eswaran, Kristin Lieber, Janhavi Mahajan, Minsoo Thigpen, Sudhir Darbha, Subru Krishnan, Soundar Srinivasan, Carlo Curino, Konstantinos Karanasos
Symposium on Cloud Computing (SoCC) | August 2019
-
-
-
Autotuning Systems: Techniques, Challenges, and Opportunities
Brian Kroth, Sergiy Matusevych, Yiwen Zhu
SIGMOD 2025 | June 2025
-
MLOS in Action: Bridging the Gap Between Experimentation and Auto-Tuning in the Cloud
Brian Kroth, Sergiy Matusevych, Rana Alotaibi, Yiwen Zhu, Anja Gruenheid, Yuanyuan Tian
Proc. VLDB Endow. | October 2024, Vol 17: pp. 4269-4272
-
-
-
MLOS in Action: Bridging the Gap Between Experimentation and Auto-Tuning in the Cloud
Brian Kroth, Sergiy Matusevych, Rana Alotaibi, Yiwen Zhu, Anja Gruenheid, Yuanyuan Tian
Proc. VLDB Endow. | October 2024, Vol 17: pp. 4269-4272
-
VASIM: Vertical Autoscaling Simulator Toolkit
Anna Pavlenko, Karla Saur, Yiwen Zhu, Brian Kroth, Joyce Cahoon, Jesús Camacho-Rodríguez
IEEE International Conference on Data Engineering (ICDE 2024) | May 2024
-
Data Science Through the Looking Glass
Fotis Psallidas, Yiwen Zhu, Bojan Karlaš, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos
SIGMOD Record | June 2022, Vol 51(2): pp. 30-37
-
MLOS: An Infrastructure for Automated Software Performance Engineering
Carlo Curino, Neha Godwal, Brian Kroth, Sergiy Kuryata, Greg Lapinski, Siqi Liu, Slava Oks, Olga Poppe, Adam Smiechowski, Ed Thayer, Markus Weimer, Yiwen Zhu
DEEM 2020 | June 2020
-
-
-
Rockhopper: A Robust Optimizer for Spark Configuration Tuning in Production Environment
Yiwen Zhu, Rathijit Sen, Brian Kroth, Sergiy Matusevych, Andreas Mueller, Tengfei Huang, Rahul Challapalli, Weihan Tang, Xin He, Mo Liu, Estera Kot, Sule Kahraman, Arshdeep Sekhon, Dario Bernal, Aditya Lakra, Shaily Fozdar, Dhruv Relwani, Rui Fang, Long Tian, Karuna Sagar Krishna, Ashit Gosalia, Carlo Curino, Subru Krishnan
Companion of the 2025 International Conference on Management of Data | June 2025
-
MLOS in Action: Bridging the Gap Between Experimentation and Auto-Tuning in the Cloud
Brian Kroth, Sergiy Matusevych, Rana Alotaibi, Yiwen Zhu, Anja Gruenheid, Yuanyuan Tian
Proc. VLDB Endow. | October 2024, Vol 17: pp. 4269-4272
-
Lorentz: Learned SKU Recommendation Using Profile Data
Nick Glaze, Tria McNeely, Yiwen Zhu, Matthew Gleeson, Helen Serr, Rajeev Bhopi, Subru Krishnan, Yiwen Zhu, Subru Krishnan
SIGMOD 2024 | May 2024, Vol 2: pp. 149
-
Intelligent Pooling: Proactive Resource Provisioning in Large-scale Cloud Service
Deepak Ravikumar, Alex Yeo, Yiwen Zhu, Aditya Lakra, Harsha Nagulapalli, Santhosh Ravindran, Steve Suh, Niharika Dutta, Andrew Fogarty, Yoonjae Park, Sumeet Khushalani, Arijit Tarafdar, Kunal Parekh, Subru Krishnan, Yiwen Zhu, Subru Krishnan
Proc. VLDB Endow. | February 2024, Vol 17: pp. 1618-1627
-
Data Science Through the Looking Glass
Fotis Psallidas, Yiwen Zhu, Bojan Karlaš, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos
SIGMOD Record | June 2022, Vol 51(2): pp. 30-37
-
Data Science Through the Looking Glass: Analysis of Millions of GitHub Notebooks and ML.NET Pipelines
Fotis Psallidas, Yiwen Zhu, Bojan Karlaš, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos
SIGMOD Record | March 2022
-
-
-
Autotuning Systems: Techniques, Challenges, and Opportunities
Brian Kroth, Sergiy Matusevych, Yiwen Zhu
SIGMOD 2025 | June 2025
-
Vertically Autoscaling Monolithic Applications with CaaSPER: Scalable Container-as-a-Service Performance Enhanced Resizing Algorithm for the Cloud
Anna Pavlenko, Joyce Cahoon, Yiwen Zhu, Brian Kroth, Michael Nelson, Andrew Carter, David Liao, Travis Wright, Jesús Camacho-Rodríguez, Karla Saur
SIGMOD | June 2024
to appear
-
VASIM: Vertical Autoscaling Simulator Toolkit
Anna Pavlenko, Karla Saur, Yiwen Zhu, Brian Kroth, Joyce Cahoon, Jesús Camacho-Rodríguez
IEEE International Conference on Data Engineering (ICDE 2024) | May 2024
-
Demonstration of Geyser: Provenance Extraction and Applications over Data Science Scripts
Fotis Psallidas, Megan Eileen Leszczynski, Mohammad Hossein Namaki, Avrilia Floratou, Ashvin Agrawal, Konstantinos Karanasos, Subru Krishnan, Pavle Subotić, Markus Weimer, Yinghui Wu, Yiwen Zhu
ACM SIGMOD | July 2023
-
Exploiting Structure in Regular Expression Queries
Ling Zhang, Shaleen Deep, Avrilia Floratou, Anja Gruenheid, Jignesh M. Patel, Yiwen Zhu
ACM SIGMOD | July 2023
-
Towards Building Autonomous Data Services on Azure
Yiwen Zhu, Yuanyuan Tian, Joyce Cahoon, Subru Krishnan, Ankita Agarwal, Rana Alotaibi, Jesús Camacho-Rodríguez, Bibin A Chundatt, Andrew Chung, Niharika Dutta, Andrew Fogarty, Anja Gruenheid, Brandon Haynes, Matteo Interlandi, Minu Iyer, Nick Jurgens, Sumeet Khushalani, Brian Kroth, Manoj Kumar, Jyoti Leeka, Sergiy Matusevych, Minni Mittal, Andreas C. Müller, Kartheek Muthyala, Harsha Nagulapalli, Yoonjae Park, Hiren Patel, Anna Pavlenko, Olga Poppe, Santhosh Ravindran, Karla Saur, Rathijit Sen, Steve Suh, Arijit Tarafdar, Kunal Waghray, Demin Wang, Carlo Curino, Raghu Ramakrishnan
ACM SIGMOD | June 2023
-
Runtime Variation in Big Data Analytics
Yiwen Zhu, Rathijit Sen, Robert Horton, John Mark Agosta
ACM SIGMOD | May 2023
-
Doppler: Automated SKU Recommendation in Migrating SQL Workloads to the Cloud
Joyce Cahoon, Wenjing Wang, Yiwen Zhu, Katherine Lin, Sean Liu, Raymond Truong, Neetu Singh, Chengcheng Wan, Alexandra M Ciortea, Sreraman Narasimhan, Subru Krishnan
VLDB 2022 | August 2022
-
Phoebe: A Learning-based Checkpoint Optimizer
Yiwen Zhu, Matteo Interlandi, Abhishek Roy, Krishnadhan Das, Hiren Patel, Malay Bag, Hitesh Sharma, Alekh Jindal
VLDB 2021 | August 2021
-
KEA: Tuning an Exabyte-Scale Data Infrastructure
Yiwen Zhu, Subru Krishnan, Konstantinos Karanasos, Isha Tarte, Conor Power, Abhishek Modi, Manoj Kumar, Deli Zhang, Deli Zhang, Kartheek Muthyala, Nick Jurgens, Sarvesh Sakalanaga, Sudhir Darbha, Minu Iyer, Ankita Agarwal, Carlo Curino
SIGMOD | June 2021
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Seagull: An Infrastructure for Load Prediction and Optimized Resource Allocation
Olga Poppe, Tayo Amuneke, Dalitso Banda, Aritra De, Ari Green, Manon Knoertzer, Ehi Nosakhare, Karthik Rajendran, Deepak Shankargouda, Meina Wang, Alan Au, Carlo Curino, Qun Guo, Alekh Jindal, Ajay Kalhan, Morgan Oslake, Sonia Parchani, Vijay Ramani, Raj Sellappan, Saikat Sen, Sheetal Shrotri, Soundararajan Srinivasan, Ping Xia, Shize Xu, Alicia Yang, Yiwen Zhu
VLDB 2021 | September 2020
Top project in Azure All Hands 2021
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Vamsa: Automated Provenance Tracking in Data Science Scripts
Mohammad Hossein Namaki, Avrilia Floratou, Fotis Psallidas, Subru Krishnan, Ashvin Agrawal, Yiwen Zhu, Markus Weimer, Yinghui Wu
KDD | August 2020
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MLOS: An Infrastructure for Automated Software Performance Engineering
Carlo Curino, Neha Godwal, Brian Kroth, Sergiy Kuryata, Greg Lapinski, Siqi Liu, Slava Oks, Olga Poppe, Adam Smiechowski, Ed Thayer, Markus Weimer, Yiwen Zhu
DEEM 2020 | June 2020
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Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML
Ashvin Agrawal, Rony Chatterjee, Carlo Curino, Avrilia Floratou, Neha Godwal, Matteo Interlandi, Alekh Jindal, Konstantinos Karanasos, Subru Krishnan, Brian Kroth, Jyoti Leeka, Kwanghyun Park, Hiren Patel, Olga Poppe, Fotis Psallidas, Raghu Ramakrishnan, Abhishek Roy, Karla Saur, Rathijit Sen, Markus Weimer, Travis Wright, Yiwen Zhu
Conference on Innovative Data Systems Research (CIDR) | January 2020
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Griffon: Reasoning about Job Anomalies with Unlabeled Data in Cloud-based Platforms
Liqun Shao, Yiwen Zhu, Siqi Liu, Abhiram Eswaran, Kristin Lieber, Janhavi Mahajan, Minsoo Thigpen, Sudhir Darbha, Subru Krishnan, Soundar Srinivasan, Carlo Curino, Konstantinos Karanasos
Symposium on Cloud Computing (SoCC) | August 2019
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