Morpheus: Towards automated {SLOs} for enterprise clusters SA Jyothi, C Curino, I Menache, SM Narayanamurthy, A Tumanov, ... 12th USENIX symposium on operating systems design and implementation (OSDI …, 2016 | 342 | 2016 |
Reservation-based scheduling: If you're late don't blame us! C Curino, DE Difallah, C Douglas, S Krishnan, R Ramakrishnan, S Rao Proceedings of the ACM Symposium on Cloud Computing, 1-14, 2014 | 198 | 2014 |
Hydra: a federated resource manager for data-center scale analytics C Curino, S Krishnan, K Karanasos, S Rao, GM Fumarola, B Huang, ... 16th USENIX Symposium on Networked Systems Design and Implementation (NSDI …, 2019 | 90 | 2019 |
Extending relational query processing with ML inference K Karanasos, M Interlandi, D Xin, F Psallidas, R Sen, K Park, I Popivanov, ... arXiv preprint arXiv:1911.00231, 2019 | 89 | 2019 |
Perforator: eloquent performance models for resource optimization K Rajan, D Kakadia, C Curino, S Krishnan Proceedings of the Seventh ACM Symposium on Cloud Computing, 415-427, 2016 | 81 | 2016 |
Data science through the looking glass: Analysis of millions of github notebooks and ml. net pipelines F Psallidas, Y Zhu, B Karlas, J Henkel, M Interlandi, S Krishnan, B Kroth, ... ACM SIGMOD Record 51 (2), 30-37, 2022 | 65 | 2022 |
Vamsa: Automated provenance tracking in data science scripts MH Namaki, A Floratou, F Psallidas, S Krishnan, A Agrawal, Y Wu, Y Zhu, ... Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 62 | 2020 |
Method and system for building an elastic cloud web server farm SV Krishnan, A Jaiswal, R Meka, JC Counio, A Abdelnur, RR Shah US Patent 8,954,568, 2015 | 48 | 2015 |
Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML A Agrawal, R Chatterjee, C Curino, A Floratou, N Gowdal, M Interlandi, ... arXiv preprint arXiv:1909.00084, 2019 | 39 | 2019 |
Peregrine: Workload optimization for cloud query engines A Jindal, H Patel, A Roy, S Qiao, Z Yin, R Sen, S Krishnan Proceedings of the ACM Symposium on Cloud Computing, 416-427, 2019 | 34 | 2019 |
Unearthing inter-job dependencies for better cluster scheduling A Chung, S Krishnan, K Karanasos, C Curino, GR Ganger 14th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2020 | 32 | 2020 |
Schema matching using pre-trained language models Y Zhang, A Floratou, J Cahoon, S Krishnan, AC Müller, D Banda, ... 2023 IEEE 39th International Conference on Data Engineering (ICDE), 1558-1571, 2023 | 26 | 2023 |
Kea: Tuning an exabyte-scale data infrastructure Y Zhu, S Krishnan, K Karanasos, I Tarte, C Power, A Modi, M Kumar, ... Proceedings of the 2021 International Conference on Management of Data, 2667 …, 2021 | 21 | 2021 |
Vamsa: Tracking provenance in data science scripts MH Namaki, A Floratou, F Psallidas, S Krishnan, A Agrawal, Y Wu arXiv preprint arXiv:2001.01861, 2020 | 15 | 2020 |
Griffon: Reasoning about job anomalies with unlabeled data in cloud-based platforms L Shao, Y Zhu, S Liu, A Eswaran, K Lieber, J Mahajan, M Thigpen, ... Proceedings of the ACM Symposium on Cloud Computing, 441-452, 2019 | 13 | 2019 |
Sparkcruise: Handsfree computation reuse in spark A Roy, A Jindal, H Patel, A Gosalia, S Krishnan, C Curino Proceedings of the VLDB Endowment 12 (12), 1850-1853, 2019 | 13 | 2019 |
Seamless cluster servicing K Chaliparambil, C Curino, K Karanam, SV Krishnan, CW Douglas, S Rao, ... US Patent 9,578,091, 2017 | 11 | 2017 |
Doppler: automated SKU recommendation in migrating SQL workloads to the cloud J Cahoon, W Wang, Y Zhu, K Lin, S Liu, R Truong, N Singh, C Wan, ... arXiv preprint arXiv:2208.04978, 2022 | 9 | 2022 |
Data Science through the looking glass and what we found there. CoRR abs/1912.09536 (2019) F Psallidas, Y Zhu, B Karlas, M Interlandi, A Floratou, K Karanasos, W Wu, ... arXiv preprint arXiv:1912.09536, 2019 | 8 | 2019 |
Query Processing with Machine Learning K Karanasos, M Interlandi, F Psallidas, R Sen, K Park, I Popivanov, ... US Patent App. 16/990,506, 2021 | 7 | 2021 |