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论文与出版物
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Autotuning Systems: Techniques, Challenges, and Opportunities
Brian Kroth, Sergiy Matusevych, Yiwen Zhu
SIGMOD 2025 | June 2025
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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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TUNA: Tuning Unstable and Noisy Cloud Applications
Johannes Freischuetz, Konstantinos Kanellis, Brian Kroth, Shivaram Venkataraman
Eurosys 2025 | March 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, 第 17 卷: pp. 4269-4272
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LST-Bench: Benchmarking Log-Structured Tables in the Cloud
Jesús Camacho-Rodríguez, Ashvin Agrawal, Anja Gruenheid, Ashit Gosalia, Cristian Petculescu, Josep Aguilar-Saborit, Avrilia Floratou, Carlo Curino, Raghu Ramakrishnan
ACM SIGMOD | June 2024
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Sibyl: Forecasting Time-Evolving Query Workloads
Hanxian Huang, Tarique Siddiqui, Rana Alotaibi, Carlo Curino, Jyoti Leeka, Alekh Jindal, Jishen Zhao, Jesús Camacho-Rodríguez, Yuanyuan Tian
SIGMOD | June 2024
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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
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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, 第 2 卷: 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
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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, 第 17 卷: pp. 1618-1627
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Performance Roulette: How Cloud Weather Affects ML-Based System Optimization
Johannes Freischuetz, Konstantinos Kanellis, Brian Kroth, Shivaram Venkataraman
ML for Systems Workshop at NeurIPS 2023 | December 2023
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GEqO: ML-Accelerated Semantic Equivalence Detection
Brandon Haynes, Rana Alotaibi, Anna Pavlenko, Jyoti Leeka, Alekh Jindal, Yuanyuan Tian
Proceedings of the ACM on Management of Data | December 2023
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Optimizing Data Pipelines for Machine Learning in Feature Stores
Rui Liu, Kwanghyun Park, Fotis Psallidas, Xiaoyong Zhu, Jinghui Mo, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos, Yuanyuan Tian, Jesús Camacho-Rodríguez
Proc. VLDB Endow. | August 2023, 第 16 卷: pp. 4230-4239
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PolySem: Efficient Polyglot Analytics on Semantic Data
Xinyu Liu, Venkatesh Emani, Avrilia Floratou, Joyce Cahoon, Philip Seamark, Carlo Curino
Poly’23: Polystore systems for heterogeneous data in multiple databases with privacy and security assurances | August 2023
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PyFroid: Scaling Data Analysis on a Commodity Workstation
Venkatesh Emani, Avrilia Floratou, Carlo Curino
EDBT 2024 | August 2023
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OneProvenance: Efficient Extraction of Dynamic Coarse-Grained Provenance From Database Query Event Logs
Fotis Psallidas, Ashvin Agrawal, Chandru Sugunan, Khaled Ibrahim, Konstantinos Karanasos, Jesus Camacho-Rodriguez, A. Floratou, C. Curino, R. Ramakrishnan
Proc. VLDB Endow. | August 2023, 第 16 卷: pp. 3662-3675
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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
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A Deep Dive into Common Open Formats for Analytical DBMSs
Chunwei Liu, Anna Pavlenko, Matteo Interlandi, Brandon Haynes
Proc. VLDB Endow. | June 2023, 第 16 卷: pp. 3044-3056
Best Paper Runner-Up
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Query Processing on Gaming Consoles
Wei Cui, Qianxi Zhang, Jesús Camacho-Rodríguez, Spyros Blanas, Brandon Haynes, Yinan Li, Peng Cheng, Ravishankar Ramamurthy, Rathijit Sen, Matteo Interlandi
June 2023
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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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Schema Matching using Pre-Trained Language Models
Yunjia Zhang, Avrilia Floratou, Joyce Cahoon, Subru Krishnan, Andreas C. Müller, Dalitso Banda, Fotis Psallidas, Jignesh M. Patel
ICDE | January 2023
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The Fine-Grained Complexity of CFL Reachability
Paraschos Koutris, Shaleen Deep
Principles of Programming Languages (POPL 2023) | January 2023
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The Tensor Data Platform: Towards an AI-centric Database System
Apurva Gandhi, Yuki Asada, Victor Fu, Advitya Gemawat, Lihao Zhang, Rathijit Sen, Carlo Curino, Jesús Camacho-Rodríguez, Matteo Interlandi
CIDR | January 2023
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DIAMETRICS: Benchmarking Query Engines at Scale
Shaleen Deep, Anja Gruenheid, Kruthi Nagaraj, Hiro Naito, Jeffrey Naughton, Stratis Viglas
Communications of The ACM | December 2022, 第 65 卷(12): pp. 105-112
Research Highlight
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Comprehensive and Efficient Workload Summarization
Shaleen Deep, Anja Gruenheid, Paraschos Koutris, Stratis Viglas, Jeffrey Naughton
Datenbank-Spektrum | November 2022
Research Highlight
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Diversity and Inclusion Activities in Database Conferences: A 2021 Report.
Sihem Amer-Yahia, Yael Amsterdamer, Sourav S. Bhowmick,, Angela Bonifati, Philippe Bonnet, Renata Borovica-Gajic, Barbara Catania, Tania Cerquitelli, Silvia Chiusano, Panos K. Chrysanthis, Carlo Curino, Jérôme Darmont, Amr El Abbadi, Avrilia Floratou, Juliana Freire, Alekh Jindal, Vana Kalogeraki, Georgia Koutrika, Arun Kumar, Sujaya Maiyya, Alexandra Meliou, Madhulika Mohanty, Felix Naumann, Nele Sina Noack, Liat Peterfreund, Fatma Özcan, Wenny Rahayu, Wang-Chiew Tan, Yuanyuan Tian, Pinar Tözün, Genoveva Vargas-Solar, Neeraja J. Yadwadkar, Meihui Zhang
SIGMOD Record | November 2022
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Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem
Yuki Asada, Victor Fu, Apurva Gandhi, Advitya Gemawat, Lihao Zhang, Dong He, Vivek Gupta, Ehi Nosakhare, Dalitso Banda, Rathijit Sen, Matteo Interlandi
VLDB | September 2022, 第 15 卷(12): pp. 3598-3601
Best demo award
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Containerized Execution of UDFs: An Experimental Evaluation
Karla Saur, Tara Mirmira, Konstantinos Karanasos, Jesús Camacho-Rodríguez
VLDB 2022 | September 2022
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Pipemizer: An Optimizer for Analytics Data Pipelines
Sunny Gakhar, Joyce Cahoon, Wangchao Le, Xiangnan Li, Kaushik Ravichandran, Hiren Patel, Marc Friedman, Brandon Haynes, Shi Qiao, Alekh Jindal, Jyoti Leeka
PVLDB | September 2022
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Query Processing on Tensor Computation Runtimes
Dong He, Supun Nakandala, Dalitso Banda, Rathijit Sen, Karla Saur, Kwanghyun Park, Carlo Curino, Jesús Camacho-Rodríguez, Konstantinos Karanasos, Matteo Interlandi
VLDB 2022 | September 2022
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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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Deploying a Steered Query Optimizer in Production at Microsoft
Wangda Zhang, Matteo Interlandi, Paul Mineiro, Shi Qiao, Nasim Ghazanfari, Karlen Lie, Marc Friedman, Rafah Hosn, Hiren Patel, Alekh Jindal
2022 International Conference on Management of Data | July 2022
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VIP Hashing — Adapting to Skew in Popularity of Data on the Fly
Aarati Kakaraparthy, Jignesh M. Patel, Brian Kroth, Kwanghyun Park
VLDB 2022 | June 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, 第 51 卷(2): pp. 30-37
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End-to-end Optimization of Machine Learning Prediction Queries
Kwanghyun Park, Karla Saur, Dalitso Banda, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos
SIGMOD | June 2022
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LlamaTune: Sample-Efficient DBMS Configuration Tuning
Konstantinos Kanellis, Cong Ding, Brian Kroth, Andreas C. Müller, Carlo Curino, Shivaram Venkataraman
VLDB 2022 | March 2022
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NyxCache: Flexible and Efficient Multi-tenant Persistent Memory Caching
Kan Wu, Kaiwei Tu, Yuvraj Patel, Rathijit Sen, Kwanghyun Park, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
20th USENIX Conference on File and Storage Technologies | February 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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Steering Query Optimizers: A Practical Take on Big Data Workloads
Parimarjan Negi, Matteo Interlandi, Ryan Marcus, Mohammad Alizadeh, Tim Kraska, Marc Friedman, Alekh Jindal
2021 International Conference on Management of Data | June 2021
Honorable mention for the Industry Track
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HADAD: A Lightweight Approach for Optimizing Hybrid Complex Analytics Queries
Rana Alotaibi, Bogdan Cautis, Alin Deutsch, Ioana Manolescu
2021 International Conference on Management of Data | June 2021
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HADAD: A Lightweight Approach for Optimizing Hybrid Complex Analytics Queries
Rana Alotaibi, Bogdan Cautis, Alin Deutsch, Ioana Manolescu
SIGMOD | June 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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Microlearner: A fine-grained Learning Optimizer for Big Data Workloads at Microsoft
Alekh Jindal, Shi Qiao, Rathijit Sen, Hiren Patel
2021 International Conference on Data Engineering | April 2021
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Property Graph Schema Optimization for Domain-Specific Knowledge Graphs
Rana Alotaibi, Chuan Lei, Abdul Quamar, Vasilis Efthymiou, Fatma Ozcan
ICDE | April 2021
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FPGA for Aggregate Processing: The Good, The Bad, and The Ugly
Zubeyr F. Eryilmaz, Aarati Kakaraparthy, Jignesh M. Patel, Rathijit Sen, Kwanghyun Park
International Conference on Data Engineering (ICDE) | April 2021
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Production Experiences from Computation Reuse at Microsoft
Alekh Jindal, Shi Qiao, Hiren Patel, Abhishek Roy, Jyoti Leeka, Brandon Haynes
2021 Extending Database Technology | March 2021
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Hardware Acceleration for DBMS Machine Learning Scoring: Is It Worth the Overheads?
Zahra Azad, Rathijit Sen, Kwanghyun Park, Ajay Joshi
International Symposium on Performance Analysis of Systems and Software (ISPASS) | March 2021
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The Storage Hierarchy is Not a Hierarchy: Optimizing Caching on Modern Storage Devices with Orthus
Kan Wu, Zhihan Guo, Guanzhou Hu, Kaiwei Tu, Ramnatthan Alagappan, Rathijit Sen, Kwanghyun Park, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
19th USENIX Conference on File and Storage Technologies | February 2021
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Magpie: Python at Speed and Scale using Cloud Backends
Alekh Jindal, Venkatesh Emani, Maureen Daum, Olga Poppe, Brandon Haynes, Anna Pavlenko, Ayushi Gupta, Karthik Ramachandra, Carlo Curino, Andreas C. Müller, Wentao Wu, Hiren Patel
Conference on Innovative Data Systems Research (CIDR 2021) | February 2021
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Applied Research Lessons from CloudViews Project
Alekh Jindal
Sigmod Record | December 2020, 第 49 卷(3): pp. 37-42
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A Tensor Compiler for Unified Machine Learning Prediction Serving
Supun Nakandala, Karla Saur, Gyeong-In Yu, Konstantinos Karanasos, Carlo Curino, Markus Weimer, Matteo Interlandi
Symposium on Operating Systems Design and Implementation (OSDI) | November 2020
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Unearthing inter-job dependencies for better cluster scheduling
Andrew Chung, Subru Krishnan, Konstantinos Karanasos, Carlo Curino, Gregory R. Ganger
Symposium on Operating Systems Design and Implementation (OSDI) | November 2020
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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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AutoToken: predicting peak parallelism for big data analytics at Microsoft
Rathijit Sen, Alekh Jindal, Hiren Patel, Shi Qiao
Very Large Data Bases | July 2020
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ESTOCADA: Towards Scalable Polystore Systems
Rana Alotaibi, Bogdan Cautis, Alin Deutsch, M. Latrache, Ioana Manolescu, Y. Yang
VLDB | July 2020
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Towards Plan-aware Resource Allocation in Serverless Query Processing
Malay Bag, Alekh Jindal, Hiren Patel
USENIX conference on Hot Topics in Cloud Ccomputing | July 2020
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Lessons learned from the early performance evaluation of Intel Optane DC persistent memory in DBMS
Yinjun Wu, Kwanghyun Park, Rathijit Sen, Brian Kroth, Jae Young Do
2020 Data Management on New Hardware | June 2020
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Automated Tuning of Query Degree of Parallelism via Machine Learning
Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi
2020 International Conference on Management of Data | June 2020
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A Comparative Exploration of ML Techniques for Tuning Query Degree of Parallelism.
Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi
May 2020
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Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings
Tarique Siddiqui, Alekh Jindal, Shi Qiao, Hiren Patel, Wangchao le
SIGMOD 2020: International Conference on Management of Data | February 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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Extending Relational Query Processing with ML Inference
Konstantinos Karanasos, Matteo Interlandi, Doris Xin, Fotis Psallidas, Rathijit Sen, Kwanghyun Park, Ivan Popivanov, Supun Nakandal, Subru Krishnan, Markus Weimer, Yuan Yu, Raghu Ramakrishnan, Carlo Curino
Conference on Innovative Data Systems Research (CIDR) | January 2020
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Optimizing databases by learning hidden parameters of solid state drives
Aarati Kakaraparthy, Jignesh M. Patel, Kwanghyun Park, Brian Kroth
Proceedings of VLDB | December 2019
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Big Data Processing at Microsoft: Hyper Scale, Massive Complexity, and Minimal Cost
Hiren Patel, Alekh Jindal, Clemens Szyperski
Symposium on Cloud Computing | November 2019
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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 | November 2019
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Neptune: Scheduling Suspendable Tasks for Unified Stream/Batch Applications
Panagiotis Garefalakis, Konstantinos Karanasos, Peter Pietzuch
Symposium on Cloud Computing (SoCC) | November 2019
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BlackMagic: Automatic Inlining of Scalar UDFs into SQL Queries with Froid
Karthik Ramachandra, Kwanghyun Park
Proceedings of VLDB | August 2019, 第 12 卷(12): pp. 1810-1813
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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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SparkCruise: handsfree computation reuse in Spark
Abhishek Roy, Alekh Jindal, Hiren Patel, Ashit Gosalia, Subru Krishnan, Carlo Curino
Very Large Data Bases | July 2019
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Exploiting Intel Optane SSD for Microsoft SQL Server
Kan Wu, Andrea Arpaci-Dusseau, Remzi Arpaci-Dusseau, Rathijit Sen, Kwanghyun Park
DaMoN 2019 | July 2019
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Peering through the Dark: An Owl’s View of Inter-job Dependencies and Jobs’ Impact in Shared Clusters
Andrew Chung, Carlo Curino, Subru Krishnan, Konstantinos Karanasos, Panagiotis Garefalakis, Gregory R. Ganger
International Conference on Management of Data (SIGMOD) | June 2019
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Towards Scalable Hybrid Stores: Constraint-Based Rewriting to the Rescue
Rana Alotaibi, Damian Bursztyn, Alin Deutsch, Ioana Manolescu, Stamatis Zampetakis
SIGMOD | June 2019
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Query and Resource Optimizations: A Case for Breaking the Wall in Big Data Systems
Alekh Jindal, Lalitha Viswanathan, Konstantinos Karanasos
MSR-TR-2019-44 | June 2019
作者：Microsoft
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Constant Time Recovery in Azure SQL Database
Panagiotis Antonopoulos, Peter Byrne, Wayne Chen, Cristian Diaconu, Raghavendra Thallam Kodandaramaih, Hanuma Kodavalla, Prashanth Purnananda, Adrian-Leonard Radu, Chaitanya Sreenivas Ravella, Girish Mittur Venkataramanappa
June 2019
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Hydra: a federated resource manager for data-center scale analytics
Carlo Curino, Subru Krishnan, Konstantinos Karanasos, Sriram Rao, Giovanni M. Fumarola, Botong Huang, Kishore Chaliparambil, Arun Suresh, Young Chen, Solom Heddaya, Roni Burd, Sarvesh Sakalanaga, Chris Douglas, Bill Ramsey, Raghu Ramakrishnan
Symposium on Networked Systems Design and Implementation (NSDI) | February 2019
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SOCK: Serverless-Optimized Containers.
Edward Oakes, Leon Yang, Dennis Zhou, Kevin Houck, Tyler Caraza-Harter, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
;login: | December 2018, 第 43 卷(3)
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Towards a learning optimizer for shared clouds
Chenggang Wu, Alekh Jindal, Saeed Amizadeh, Hiren Patel, Wangchao Le, Shi Qiao, Sriram Rao
Very Large Data Bases | October 2018
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PRETZEL: opening the black box of machine learning prediction serving systems
Yunseong Lee, Alberto Scolari, Byung-Gon Chun, Marco Domenico Santambrogio, Matteo Interlandi, Markus Weimer
Operating Systems Design and Implementation | October 2018
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Netco: Cache and I/O Management for Analytics over Disaggregated Stores
Virajith Jalaparti, Chris Douglas, Mainak Ghosh, Ashvin Agrawal, Avrilia Floratou, Srikanth Kandula, Ishai Menache, Joseph (Seffi) Naor, Sriram Rao
ACM Symposium on Cloud Computing (SOCC) | October 2018
Best Paper Award
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Dhalion in action: automatic management of streaming applications
Avrilia Floratou, Ashvin Agrawal
Proceedings of the VLDB Endowment | August 2018, 第 11 卷(12)
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SOCK: rapid task provisioning with serverless-optimized containers
Edward Oakes, Leon Yang, Dennis Zhou, Kevin Houck, Tyler Harter, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
USENIX Annual Technical Conference | July 2018
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Challenges and Opportunities in Transportation Data
Kristin Tufte, Kushal Datta, Alekh Jindal, David Maier, Robert L. Bertini
June 2018
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Computation Reuse in Analytics Job Service at Microsoft
Alekh Jindal, Shi Qiao, Hiren Patel, Zhicheng Yin, Jieming Di, Malay Bag, Marc Friedman, Yifung Lin, Konstantinos Karanasos, Sriram Rao
2018 International Conference on Management of Data | May 2018
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Survivability of Cloud Databases – Factors and Prediction
Jose Picado, Willis Lang, Edward C. Thayer
International Conference on Management of Data | May 2018
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Columnar Storage Formats
Encyclopedia of Big Data Technologies | 作者：Springer | 2018
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Query and Resource Optimization: Bridging the Gap
Lalitha Viswanathan, Alekh Jindal, Konstantinos Karanasos
International Conference on Data Engineering (ICDE) | April 2018
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Selecting subexpressions to materialize at datacenter scale
Alekh Jindal, Konstantinos Karanasos, Sriram Rao, Hiren Patel
Very Large Data Bases (VLDB) | February 2018
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Batch-Expansion Training: An Efficient Optimization Framework
Michał Dereziński, Dhruv Mahajan, S. Sathiya Keerthi, S. V. N. Vishwanathan, Markus Weimer
International Conference on Artificial Intelligence and Statistics | February 2018
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Advancements in YARN Resource Manager
Konstantinos Karanasos, Arun Suresh, Chris Douglas
Encyclopedia of Big Data Technologies | February 2018
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Robust Data Partitioning.
Alekh Jindal, Anil Shanbhag, Yi Lu
February 2018
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Characterizing Resource Sensitivity of Database Workloads
Rathijit Sen, Karthik Ramachandra
High-Performance Computer Architecture | January 2018
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Medea: Scheduling of Long Running Applications in Shared Production Clusters
Panagiotis Garefalakis, Konstantinos Karanasos, Peter Pietzuch, Arun Suresh, Sriram Rao
European Conference on Computer Systems (EuroSys) | January 2018
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Towards High-Performance Prediction Serving Systems
Yunseong Lee, Alberto Scolari, Byung-Gon Chun, Matteo Interlandi, Markus Weimer
31st Conference on Neural Information Processing Systems | December 2017
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Froid: Optimization of Imperative Programs in a Relational Database
Karthik Ramachandra, Kwanghyun Park, K. Venkatesh Emani, Alan Halverson, Cesar Galindo-Legaria, Conor Cunningham
Proceedings of VLDB | December 2017, 第 11 卷(4)
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Apache REEF: Retainable Evaluator Execution Framework
Byung-Gon Chun, Tyson Condie, Yingda Chen, Brian Cho, Andrew Chung, Carlo Curino, Chris Douglas, Beomyeol Jeon, Joo Seong Jeong, Gyewon Lee, Yunseong Lee, Tony Majestro, Dahlia Malkhi, Sergiy Matusevych, Brandon Myers, Mariia Mykhailova, Shravan Narayanamurthy, Joseph Noor, Raghu Ramakrishnan, Sriram Rao, Russell Sears, Beysim Sezgin, Taegeon Um, Julia Wang, Youngseok Yang, Raghu Ramakrishnan, Carlo Curino, Matteo Interlandi
ACM Transactions on Computer Systems | October 2017, 第 35 卷(2): pp. 5
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No data left behind: real-time insights from a complex data ecosystem
Manos Karpathiotakis, Avrilia Floratou, Fatma Ozcan, Anastasia Ailamaki
SOCC | September 2017
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A robust partitioning scheme for ad-hoc query workloads
Anil Shanbhag, Alekh Jindal, Samuel Madden, Jorge Quiane, Aaron J. Elmore
Symposium on Cloud Computing | September 2017
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Self-Regulating Streaming Systems: Challenges and Opportunities
Avrilia Floratou, Ashvin Agrawal
BIRTE | August 2017
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Dhalion: Self-Regulating Stream Processing in Heron
Avrilia Floratou, Ashvin Agrawal, Bill Graham, Sriram Rao, Karthik Ramasamy
Proceedings of the VLDB Endowment | August 2017
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Energy-Proportional Computing: A New Definition
Rathijit Sen, David A. Wood
IEEE Computer | July 2017, 第 50 卷(8): pp. 26-33
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Frequency governors for cloud database OLTP workloads
Rathijit Sen, Alan Halverson
International Symposium on Low Power Electronics and Design | July 2017
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Pipsqueak: Lean Lambdas with Large Libraries
Edward Oakes, Leon Yang, Kevin Houck, Tyler Harter, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
International Conference on Distributed Computing Systems Workshops | July 2017
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ROSA: R Optimizations with Static Analysis
Rathijit Sen, Jianqiao Zhu, Jignesh M. Patel, Somesh Jha
RIOT 2017 | July 2017
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Twitter Heron: Towards Extensible Streaming Engines
Maosong Fu, Ashvin Agrawal, Avrilia Floratou, Bill Graham, Andrew Jorgensen, Mark Li, Neng Lu, Karthik Ramasamy, Sriram Rao, Cong Wang
ICDE | May 2017
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Pareto Governors for Energy-Optimal Computing
Rathijit Sen, David A. Wood
ACM Transactions on Architecture and Code Optimization | April 2017, 第 14 卷(1): pp. 6
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Resource bricolage and resource selection for parallel database systems
Jiexing Li, Jeffrey F. Naughton, Rimma V. Nehme
Very Large Data Bases | January 2017
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INGESTBASE: A Declarative Data Ingestion System.
Alekh Jindal, Jorge-Arnulfo Quiané-Ruiz, Samuel Madden
MSR-TR-2017-62 | January 2017
作者：Microsoft
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AdaptDB: adaptive partitioning for distributed joins
Yi Lu, Anil Shanbhag, Alekh Jindal, Samuel Madden
Very Large Data Bases | January 2017
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Morpheus: Towards Automated SLOs for Enterprise Clusters
Sangeetha Abdu Jyothi, Carlo Curino, Ishai Menache, Shravan Matthur Narayanamurthy, Alexey Tumanov, Jonathan Yaniv, Ruslan Mavlyutov, Íñigo Goiri, Subru Krishnan, Janardhan (Jana) Kulkarni, Sriram Rao
2016 International Symposium on Operating Systems Design and Implementation (OSDI) | November 2016
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PerfOrator: Eloquent Performance Models for Resource Optimization
Dharmesh Kakadia, Kaushik Rajan, Carlo Curino, Subru Krishnan
ACM Symposium on Cloud Computing 2016 (SoCC’16) | October 2016
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A moeba : a shape changing storage system for big data
Anil Shanbhag, Alekh Jindal, Yi Lu, Samuel Madden
Very Large Data Bases | August 2016
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GraphFrames: an integrated API for mixing graph and relational queries
Ankur Dave, Alekh Jindal, Li Erran Li, Reynold Xin, Joseph Gonzalez, Matei Zaharia
GRADES | June 2016
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Efficient Queue Management for Cluster Scheduling
Jeff Rasley, Konstantinos Karanasos, Srikanth Kandula, Rodrigo Fonseca, Sriram Rao, Milan Vojnovic
European Conference on Computer Systems (EuroSys) | April 2016
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Do the Hard Stuff First: Scheduling Dependent Computations in Data Analytics Clusters
Robert Grandl, Srikanth Kandula, Sriram Rao, Aditya Akella, Janardhan (Jana) Kulkarni
MSR-TR-2016-19 | February 2016
作者：Microsoft
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Towards Geo-Distributed Machine Learning.
Ignacio Cano, Dhruv Mahajan, Giovanni Matteo Fumarola, Arvind Krishnamurthy, Markus Weimer, Carlo Curino
IEEE Data(base) Engineering Bulletin | December 2015, 第 40 卷: pp. 41-59
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Mercury: Hybrid Centralized and Distributed Scheduling in Large Shared Clusters
Konstantinos Karanasos, Sriram Rao, Carlo Curino, Chris Douglas, Kishore Chaliparambil, Giovanni Matteo Fumarola, Solom Heddaya, Raghu Ramakrishnan, Sarvesh Sakalanaga
USENIX Annual Technical Conference (USENIX ATC’2015) | July 2015
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Apache Tez: A Unifying Framework for Modeling and Building Data Processing Applications
Bikas Saha, Hitesh Shah, Siddharth Seth, Gopal Vijayaraghavan, Arun Murthy, Carlo Curino
SIGMOD ’15: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data | May 2015
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WANalytics: Geo-Distributed Analytics for a Data Intensive World
Ashish Vulimiri, Carlo Curino, Philip Brighten Godfrey, Thomas Jungblut, Konstantinos Karanasos, Jitendra Padhye, George Varghese
International Conference on Management of Data (SIGMOD) | May 2015
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Global Analytics in the Face of Bandwidth and Regulatory Constraints
Ashish Vulimiri, Carlo Curino, P. Brighten Godfrey, Thomas Jungblut, Jitu Padhye, George Varghese
12th USENIX Symposium on Networked Systems Design and Implementation (NSDI ’15) | May 2015
ISBN: 978-1-931971-218
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Blind men and an elephant coalescing open-source, academic, and industrial perspectives on BigData
Chris Douglas, Carlo Curino
International Conference on Data Engineering | April 2015
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WANalytics: Analytics for a Geo-Distributed Data-Intensive World
Ashish Vulimiri, Carlo Curino, Brighten Godfrey, Konstantinos Karanasos, George Varghese
Conference on Innovative Data Systems Research (CIDR) | January 2015
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Multi-resource Packing for Cluster Schedulers
Robert Grandl, Ganesh Ananthanarayanan, Srikanth Kandula, Sriram Rao, Aditya Akella
ACM SIGCOMM | August 2014
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Indexing HDFS data in PDW: splitting the data from the index
Vinitha Reddy Gankidi, Nikhil Teletia, Jignesh M. Patel, Alan Halverson, David J. DeWitt
Very Large Data Bases | July 2014
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Partial results in database systems
Willis Lang, Rimma V. Nehme, Eric Robinson, Jeffrey F. Naughton
International Conference on Management of Data | June 2014
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Dynamically Optimizing Queries over Large Scale Data Platforms
Konstantinos Karanasos, Andrey Balmin, Marcel Kutsch, Fatma Ozcan, Vuk Ercegovac, Chunyang Xia, Jesse Jackson
International Conference on Management of Data (SIGMOD) | June 2014
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Towards Multi-Tenant Performance SLOs
Willis Lang, Srinath Shankar, Jignesh M. Patel, Ajay Kalhan
IEEE Transactions on Knowledge and Data Engineering | May 2014, 第 26 卷(6): pp. 1447-1463
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Distributed and Scalable PCA in the Cloud
Arun Kumar, Vijay Narayanan, Nikos Karampatziakis, Paul Mineiro, Markus Weimer
MSR-TR-2014-165 | January 2014
作者：Microsoft
Apache Reef Research Paper
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Elastic Distributed Bayesian Collaborative Filtering
Alex Beutel, Markus Weimer, Tom Minka, Yordan Zaykov, Vijay Narayanan
January 2014
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Delta: Scalable Data Dissemination under Capacity Constraints
Konstantinos Karanasos, Asterios Katsifodimos, Ioana Manolescu
Very Large Data Bases (PVLDB) | December 2013
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Reservation-based Scheduling: If You’re Late Don’t Blame Us!
Carlo Curino, Djellel E Difallah, Chris Douglas, Subru Krishnan, Rahgu Ramakrishnan, Sriram Rao
MSR-TR-2013-108 | October 2013
Published in SoCC 2014
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Split query processing in polybase
David J. DeWitt, Rimma Nehme, Srinath Shankar, Josep Aguilar-Saborit, Artin Avanes, Miro Flasza, Jim Gramling, Alan Halverson
2013 ACM SIGMOD International Conference on Management of Data | June 2013
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Fact Checking and Analyzing the Web
Francois Goasdoue, Konstantinos Karanasos, Yannis Katsis, Julien Leblay, Ioana Manolescu, Stamatis Zampetakis
International Conference on Management of Data (SIGMOD) | June 2013
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Growing Triples on Trees: an XML-RDF Hybrid Model for Annotated Documents
Francois Goasdoue, Konstantinos Karanasos, Yannis Katsis, Julien Leblay, Ioana Manolescu, Stamatis Zampetakis
Very Large Data Bases Journal (VLDB J.) | June 2013, 第 22 卷: pp. 589-613
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Fast peak-to-peak behavior with SSD buffer pool
Jaeyoung Do, Donghui Zhang, J. M. Patel, D. J. DeWitt
International Conference on Data Engineering | April 2013
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Towards Resource-Elastic Machine Learning
Dhruv Mahajan, Sundararajan Sellamanickam, Markus Weimer, Keerthi Selvaraj
January 2013
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Towards energy-efficient database cluster design
Willis Lang, Stavros Harizopoulos, Jignesh M. Patel, Mehul A. Shah, Dimitris Tsirogiannis
2012 Very Large Data Bases | August 2012, 第 5 卷(11): pp. 1684-1695
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Robust Estimation of Resource Consumption for SQL Queries using Statistical Techniques
Jiexing Li, Arnd Christian König, Arnd Christian König, Vivek Narasayya, Surajit Chaudhuri
38th International Conference on Very Large Databases | August 2012
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Declarative Systems for Large-Scale Machine Learning.
Vinayak R. Borkar, Yingyi Bu, Michael J. Carey, Joshua Rosen, Neoklis Polyzotis, Tyson Condie, Markus Weimer, Raghu Ramakrishnan
IEEE Data(base) Engineering Bulletin | July 2012, 第 35 卷: pp. 24-32
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Query optimization in Microsoft SQL Server PDW
Srinath Shankar, Rimma Nehme, Josep Aguilar-Saborit, Andrew Chung, Mostafa Elhemali, Eric Robinson, Mahadevan Sankara Subramanian, David DeWitt, César Galindo-Legaria, Alan Halverson
International Conference on Management of Data | May 2012
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WWW 2012 Tutorial: New Templates for Scalable Data Analysis
Amr Ahmed, Alexander J. Smola, Markus Weimer
25th International World Wide Web Conference | April 2012
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GSLPI: A Cost-Based Query Progress Indicator
Jiexing Li, Rimma V. Nehme, Jeffrey Naughton
International Conference on Data Engineering | March 2012
DOI PDF Publication Publication Publication Publication Publication
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Toward Progress Indicators on Steroids for Big Data Systems.
Jiexing Li, Rimma V. Nehme, Jeffrey F. Naughton
Conference on Innovative Data Systems Research | January 2012
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Rethinking Query Processing for Energy Efficiency: Slowing Down to Win the Race.
Nicolas Bruno, Surajit Chaudhuri, Arnd Christian König, Vivek Narasayya, Ravi Ramamurthy, Manoj Syamala
IEEE Data(base) Engineering Bulletin | November 2011, 第 34 卷: pp. 12-19
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View Selection in Semantic Web Databases
Francois Goasdoue, Konstantinos Karanasos, Julien Leblay, Ioana Manolescu
Very Large Data Bases (PVLDB) | October 2011, 第 5 卷: pp. 97-108
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Automated partitioning design in parallel database systems
Rimma Nehme, Nicolas Bruno
International Conference on Management of Data | June 2011
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Turbocharging DBMS buffer pool using SSDs
Jaeyoung Do, Donghui Zhang, Jignesh M. Patel, David J. DeWitt, Jeffrey F. Naughton, Alan Halverson
International Conference on Management of Data | June 2011
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The Mimicking Octopus: Towards a one-size-fits-all Database Architecture
Alekh Jindal
36th International Conference on VLDB | September 2010
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Energy management for MapReduce clusters
Willis Lang, Jignesh M. Patel
Very Large Data Bases | August 2010
DOI PDF PDF Publication Publication Publication Publication Publication
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On energy management, load balancing and replication
Willis Lang, Jignesh M. Patel, Jeffrey F. Naughton
International Conference on Management of Data | June 2010
DOI PDF Publication Publication Publication Publication Publication
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Wimpy node clusters: what about non-wimpy workloads?
Willis Lang, Jignesh M. Patel, Srinath Shankar
Data Management on New Hardware | June 2010
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Towards Eco-friendly Database Management Systems
Willis Lang, Jignesh M. Patel
Conference on Innovative Data Systems Research | December 2009
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Autotuning Systems: Techniques, Challenges, and Opportunities
Brian Kroth, Sergiy Matusevych, Yiwen Zhu
SIGMOD 2025 | June 2025
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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, 第 17 卷: pp. 4269-4272
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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, 第 2 卷: pp. 149
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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, 第 17 卷: pp. 1618-1627
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Performance Roulette: How Cloud Weather Affects ML-Based System Optimization
Johannes Freischuetz, Konstantinos Kanellis, Brian Kroth, Shivaram Venkataraman
ML for Systems Workshop at NeurIPS 2023 | December 2023
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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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The Tensor Data Platform: Towards an AI-centric Database System
Apurva Gandhi, Yuki Asada, Victor Fu, Advitya Gemawat, Lihao Zhang, Rathijit Sen, Carlo Curino, Jesús Camacho-Rodríguez, Matteo Interlandi
CIDR | January 2023
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Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem
Yuki Asada, Victor Fu, Apurva Gandhi, Advitya Gemawat, Lihao Zhang, Dong He, Vivek Gupta, Ehi Nosakhare, Dalitso Banda, Rathijit Sen, Matteo Interlandi
VLDB | September 2022, 第 15 卷(12): pp. 3598-3601
Best demo award
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Query Processing on Tensor Computation Runtimes
Dong He, Supun Nakandala, Dalitso Banda, Rathijit Sen, Karla Saur, Kwanghyun Park, Carlo Curino, Jesús Camacho-Rodríguez, Konstantinos Karanasos, Matteo Interlandi
VLDB 2022 | September 2022
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Deploying a Steered Query Optimizer in Production at Microsoft
Wangda Zhang, Matteo Interlandi, Paul Mineiro, Shi Qiao, Nasim Ghazanfari, Karlen Lie, Marc Friedman, Rafah Hosn, Hiren Patel, Alekh Jindal
2022 International Conference on Management of Data | July 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, 第 51 卷(2): pp. 30-37
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End-to-end Optimization of Machine Learning Prediction Queries
Kwanghyun Park, Karla Saur, Dalitso Banda, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos
SIGMOD | June 2022
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A Tensor Compiler for Unified Machine Learning Prediction Serving
Supun Nakandala, Karla Saur, Gyeong-In Yu, Konstantinos Karanasos, Carlo Curino, Markus Weimer, Matteo Interlandi
Symposium on Operating Systems Design and Implementation (OSDI) | November 2020
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AutoToken: predicting peak parallelism for big data analytics at Microsoft
Rathijit Sen, Alekh Jindal, Hiren Patel, Shi Qiao
Very Large Data Bases | July 2020
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Automated Tuning of Query Degree of Parallelism via Machine Learning
Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi
2020 International Conference on Management of Data | June 2020
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A Comparative Exploration of ML Techniques for Tuning Query Degree of Parallelism.
Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi
May 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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Extending Relational Query Processing with ML Inference
Konstantinos Karanasos, Matteo Interlandi, Doris Xin, Fotis Psallidas, Rathijit Sen, Kwanghyun Park, Ivan Popivanov, Supun Nakandal, Subru Krishnan, Markus Weimer, Yuan Yu, Raghu Ramakrishnan, Carlo Curino
Conference on Innovative Data Systems Research (CIDR) | January 2020
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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 | November 2019
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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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Towards a learning optimizer for shared clouds
Chenggang Wu, Alekh Jindal, Saeed Amizadeh, Hiren Patel, Wangchao Le, Shi Qiao, Sriram Rao
Very Large Data Bases | October 2018
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Query and Resource Optimization: Bridging the Gap
Lalitha Viswanathan, Alekh Jindal, Konstantinos Karanasos
International Conference on Data Engineering (ICDE) | April 2018
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Elastic Distributed Bayesian Collaborative Filtering
Alex Beutel, Markus Weimer, Tom Minka, Yordan Zaykov, Vijay Narayanan
January 2014
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Towards Resource-Elastic Machine Learning
Dhruv Mahajan, Sundararajan Sellamanickam, Markus Weimer, Keerthi Selvaraj
January 2013
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Autotuning Systems: Techniques, Challenges, and Opportunities
Brian Kroth, Sergiy Matusevych, Yiwen Zhu
SIGMOD 2025 | June 2025
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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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LST-Bench: Benchmarking Log-Structured Tables in the Cloud
Jesús Camacho-Rodríguez, Ashvin Agrawal, Anja Gruenheid, Ashit Gosalia, Cristian Petculescu, Josep Aguilar-Saborit, Avrilia Floratou, Carlo Curino, Raghu Ramakrishnan
ACM SIGMOD | June 2024
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Sibyl: Forecasting Time-Evolving Query Workloads
Hanxian Huang, Tarique Siddiqui, Rana Alotaibi, Carlo Curino, Jyoti Leeka, Alekh Jindal, Jishen Zhao, Jesús Camacho-Rodríguez, Yuanyuan Tian
SIGMOD | June 2024
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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
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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, 第 2 卷: 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
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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, 第 17 卷: pp. 1618-1627
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GEqO: ML-Accelerated Semantic Equivalence Detection
Brandon Haynes, Rana Alotaibi, Anna Pavlenko, Jyoti Leeka, Alekh Jindal, Yuanyuan Tian
Proceedings of the ACM on Management of Data | December 2023
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Optimizing Data Pipelines for Machine Learning in Feature Stores
Rui Liu, Kwanghyun Park, Fotis Psallidas, Xiaoyong Zhu, Jinghui Mo, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos, Yuanyuan Tian, Jesús Camacho-Rodríguez
Proc. VLDB Endow. | August 2023, 第 16 卷: pp. 4230-4239
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PolySem: Efficient Polyglot Analytics on Semantic Data
Xinyu Liu, Venkatesh Emani, Avrilia Floratou, Joyce Cahoon, Philip Seamark, Carlo Curino
Poly’23: Polystore systems for heterogeneous data in multiple databases with privacy and security assurances | August 2023
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PyFroid: Scaling Data Analysis on a Commodity Workstation
Venkatesh Emani, Avrilia Floratou, Carlo Curino
EDBT 2024 | August 2023
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OneProvenance: Efficient Extraction of Dynamic Coarse-Grained Provenance From Database Query Event Logs
Fotis Psallidas, Ashvin Agrawal, Chandru Sugunan, Khaled Ibrahim, Konstantinos Karanasos, Jesus Camacho-Rodriguez, A. Floratou, C. Curino, R. Ramakrishnan
Proc. VLDB Endow. | August 2023, 第 16 卷: pp. 3662-3675
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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
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A Deep Dive into Common Open Formats for Analytical DBMSs
Chunwei Liu, Anna Pavlenko, Matteo Interlandi, Brandon Haynes
Proc. VLDB Endow. | June 2023, 第 16 卷: pp. 3044-3056
Best Paper Runner-Up
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Query Processing on Gaming Consoles
Wei Cui, Qianxi Zhang, Jesús Camacho-Rodríguez, Spyros Blanas, Brandon Haynes, Yinan Li, Peng Cheng, Ravishankar Ramamurthy, Rathijit Sen, Matteo Interlandi
June 2023
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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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Schema Matching using Pre-Trained Language Models
Yunjia Zhang, Avrilia Floratou, Joyce Cahoon, Subru Krishnan, Andreas C. Müller, Dalitso Banda, Fotis Psallidas, Jignesh M. Patel
ICDE | January 2023
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The Fine-Grained Complexity of CFL Reachability
Paraschos Koutris, Shaleen Deep
Principles of Programming Languages (POPL 2023) | January 2023
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The Tensor Data Platform: Towards an AI-centric Database System
Apurva Gandhi, Yuki Asada, Victor Fu, Advitya Gemawat, Lihao Zhang, Rathijit Sen, Carlo Curino, Jesús Camacho-Rodríguez, Matteo Interlandi
CIDR | January 2023
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DIAMETRICS: Benchmarking Query Engines at Scale
Shaleen Deep, Anja Gruenheid, Kruthi Nagaraj, Hiro Naito, Jeffrey Naughton, Stratis Viglas
Communications of The ACM | December 2022, 第 65 卷(12): pp. 105-112
Research Highlight
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Comprehensive and Efficient Workload Summarization
Shaleen Deep, Anja Gruenheid, Paraschos Koutris, Stratis Viglas, Jeffrey Naughton
Datenbank-Spektrum | November 2022
Research Highlight
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Diversity and Inclusion Activities in Database Conferences: A 2021 Report.
Sihem Amer-Yahia, Yael Amsterdamer, Sourav S. Bhowmick,, Angela Bonifati, Philippe Bonnet, Renata Borovica-Gajic, Barbara Catania, Tania Cerquitelli, Silvia Chiusano, Panos K. Chrysanthis, Carlo Curino, Jérôme Darmont, Amr El Abbadi, Avrilia Floratou, Juliana Freire, Alekh Jindal, Vana Kalogeraki, Georgia Koutrika, Arun Kumar, Sujaya Maiyya, Alexandra Meliou, Madhulika Mohanty, Felix Naumann, Nele Sina Noack, Liat Peterfreund, Fatma Özcan, Wenny Rahayu, Wang-Chiew Tan, Yuanyuan Tian, Pinar Tözün, Genoveva Vargas-Solar, Neeraja J. Yadwadkar, Meihui Zhang
SIGMOD Record | November 2022
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Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem
Yuki Asada, Victor Fu, Apurva Gandhi, Advitya Gemawat, Lihao Zhang, Dong He, Vivek Gupta, Ehi Nosakhare, Dalitso Banda, Rathijit Sen, Matteo Interlandi
VLDB | September 2022, 第 15 卷(12): pp. 3598-3601
Best demo award
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Query Processing on Tensor Computation Runtimes
Dong He, Supun Nakandala, Dalitso Banda, Rathijit Sen, Karla Saur, Kwanghyun Park, Carlo Curino, Jesús Camacho-Rodríguez, Konstantinos Karanasos, Matteo Interlandi
VLDB 2022 | September 2022
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Pipemizer: An Optimizer for Analytics Data Pipelines
Sunny Gakhar, Joyce Cahoon, Wangchao Le, Xiangnan Li, Kaushik Ravichandran, Hiren Patel, Marc Friedman, Brandon Haynes, Shi Qiao, Alekh Jindal, Jyoti Leeka
PVLDB | September 2022
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Containerized Execution of UDFs: An Experimental Evaluation
Karla Saur, Tara Mirmira, Konstantinos Karanasos, Jesús Camacho-Rodríguez
VLDB 2022 | September 2022
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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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Deploying a Steered Query Optimizer in Production at Microsoft
Wangda Zhang, Matteo Interlandi, Paul Mineiro, Shi Qiao, Nasim Ghazanfari, Karlen Lie, Marc Friedman, Rafah Hosn, Hiren Patel, Alekh Jindal
2022 International Conference on Management of Data | July 2022
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VIP Hashing — Adapting to Skew in Popularity of Data on the Fly
Aarati Kakaraparthy, Jignesh M. Patel, Brian Kroth, Kwanghyun Park
VLDB 2022 | June 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, 第 51 卷(2): pp. 30-37
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End-to-end Optimization of Machine Learning Prediction Queries
Kwanghyun Park, Karla Saur, Dalitso Banda, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos
SIGMOD | June 2022
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LlamaTune: Sample-Efficient DBMS Configuration Tuning
Konstantinos Kanellis, Cong Ding, Brian Kroth, Andreas C. Müller, Carlo Curino, Shivaram Venkataraman
VLDB 2022 | 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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Steering Query Optimizers: A Practical Take on Big Data Workloads
Parimarjan Negi, Matteo Interlandi, Ryan Marcus, Mohammad Alizadeh, Tim Kraska, Marc Friedman, Alekh Jindal
2021 International Conference on Management of Data | June 2021
Honorable mention for the Industry Track
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HADAD: A Lightweight Approach for Optimizing Hybrid Complex Analytics Queries
Rana Alotaibi, Bogdan Cautis, Alin Deutsch, Ioana Manolescu
2021 International Conference on Management of Data | June 2021
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HADAD: A Lightweight Approach for Optimizing Hybrid Complex Analytics Queries
Rana Alotaibi, Bogdan Cautis, Alin Deutsch, Ioana Manolescu
SIGMOD | June 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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Microlearner: A fine-grained Learning Optimizer for Big Data Workloads at Microsoft
Alekh Jindal, Shi Qiao, Rathijit Sen, Hiren Patel
2021 International Conference on Data Engineering | April 2021
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Property Graph Schema Optimization for Domain-Specific Knowledge Graphs
Rana Alotaibi, Chuan Lei, Abdul Quamar, Vasilis Efthymiou, Fatma Ozcan
ICDE | April 2021
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FPGA for Aggregate Processing: The Good, The Bad, and The Ugly
Zubeyr F. Eryilmaz, Aarati Kakaraparthy, Jignesh M. Patel, Rathijit Sen, Kwanghyun Park
International Conference on Data Engineering (ICDE) | April 2021
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Production Experiences from Computation Reuse at Microsoft
Alekh Jindal, Shi Qiao, Hiren Patel, Abhishek Roy, Jyoti Leeka, Brandon Haynes
2021 Extending Database Technology | March 2021
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Hardware Acceleration for DBMS Machine Learning Scoring: Is It Worth the Overheads?
Zahra Azad, Rathijit Sen, Kwanghyun Park, Ajay Joshi
International Symposium on Performance Analysis of Systems and Software (ISPASS) | March 2021
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Magpie: Python at Speed and Scale using Cloud Backends
Alekh Jindal, Venkatesh Emani, Maureen Daum, Olga Poppe, Brandon Haynes, Anna Pavlenko, Ayushi Gupta, Karthik Ramachandra, Carlo Curino, Andreas C. Müller, Wentao Wu, Hiren Patel
Conference on Innovative Data Systems Research (CIDR 2021) | February 2021
-
Applied Research Lessons from CloudViews Project
Alekh Jindal
Sigmod Record | December 2020, 第 49 卷(3): pp. 37-42
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Unearthing inter-job dependencies for better cluster scheduling
Andrew Chung, Subru Krishnan, Konstantinos Karanasos, Carlo Curino, Gregory R. Ganger
Symposium on Operating Systems Design and Implementation (OSDI) | November 2020
-
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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ESTOCADA: Towards Scalable Polystore Systems
Rana Alotaibi, Bogdan Cautis, Alin Deutsch, M. Latrache, Ioana Manolescu, Y. Yang
VLDB | July 2020
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AutoToken: predicting peak parallelism for big data analytics at Microsoft
Rathijit Sen, Alekh Jindal, Hiren Patel, Shi Qiao
Very Large Data Bases | July 2020
-
Towards Plan-aware Resource Allocation in Serverless Query Processing
Malay Bag, Alekh Jindal, Hiren Patel
USENIX conference on Hot Topics in Cloud Ccomputing | July 2020
-
Lessons learned from the early performance evaluation of Intel Optane DC persistent memory in DBMS
Yinjun Wu, Kwanghyun Park, Rathijit Sen, Brian Kroth, Jae Young Do
2020 Data Management on New Hardware | June 2020
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Automated Tuning of Query Degree of Parallelism via Machine Learning
Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi
2020 International Conference on Management of Data | June 2020
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A Comparative Exploration of ML Techniques for Tuning Query Degree of Parallelism.
Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi
May 2020
-
Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings
Tarique Siddiqui, Alekh Jindal, Shi Qiao, Hiren Patel, Wangchao le
SIGMOD 2020: International Conference on Management of Data | February 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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Extending Relational Query Processing with ML Inference
Konstantinos Karanasos, Matteo Interlandi, Doris Xin, Fotis Psallidas, Rathijit Sen, Kwanghyun Park, Ivan Popivanov, Supun Nakandal, Subru Krishnan, Markus Weimer, Yuan Yu, Raghu Ramakrishnan, Carlo Curino
Conference on Innovative Data Systems Research (CIDR) | January 2020
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Optimizing databases by learning hidden parameters of solid state drives
Aarati Kakaraparthy, Jignesh M. Patel, Kwanghyun Park, Brian Kroth
Proceedings of VLDB | December 2019
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Big Data Processing at Microsoft: Hyper Scale, Massive Complexity, and Minimal Cost
Hiren Patel, Alekh Jindal, Clemens Szyperski
Symposium on Cloud Computing | November 2019
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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 | November 2019
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BlackMagic: Automatic Inlining of Scalar UDFs into SQL Queries with Froid
Karthik Ramachandra, Kwanghyun Park
Proceedings of VLDB | August 2019, 第 12 卷(12): pp. 1810-1813
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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
-
SparkCruise: handsfree computation reuse in Spark
Abhishek Roy, Alekh Jindal, Hiren Patel, Ashit Gosalia, Subru Krishnan, Carlo Curino
Very Large Data Bases | July 2019
-
Exploiting Intel Optane SSD for Microsoft SQL Server
Kan Wu, Andrea Arpaci-Dusseau, Remzi Arpaci-Dusseau, Rathijit Sen, Kwanghyun Park
DaMoN 2019 | July 2019
-
Towards Scalable Hybrid Stores: Constraint-Based Rewriting to the Rescue
Rana Alotaibi, Damian Bursztyn, Alin Deutsch, Ioana Manolescu, Stamatis Zampetakis
SIGMOD | June 2019
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Peering through the Dark: An Owl’s View of Inter-job Dependencies and Jobs’ Impact in Shared Clusters
Andrew Chung, Carlo Curino, Subru Krishnan, Konstantinos Karanasos, Panagiotis Garefalakis, Gregory R. Ganger
International Conference on Management of Data (SIGMOD) | June 2019
-
Query and Resource Optimizations: A Case for Breaking the Wall in Big Data Systems
Alekh Jindal, Lalitha Viswanathan, Konstantinos Karanasos
MSR-TR-2019-44 | June 2019
作者：Microsoft
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Constant Time Recovery in Azure SQL Database
Panagiotis Antonopoulos, Peter Byrne, Wayne Chen, Cristian Diaconu, Raghavendra Thallam Kodandaramaih, Hanuma Kodavalla, Prashanth Purnananda, Adrian-Leonard Radu, Chaitanya Sreenivas Ravella, Girish Mittur Venkataramanappa
June 2019
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Hydra: a federated resource manager for data-center scale analytics
Carlo Curino, Subru Krishnan, Konstantinos Karanasos, Sriram Rao, Giovanni M. Fumarola, Botong Huang, Kishore Chaliparambil, Arun Suresh, Young Chen, Solom Heddaya, Roni Burd, Sarvesh Sakalanaga, Chris Douglas, Bill Ramsey, Raghu Ramakrishnan
Symposium on Networked Systems Design and Implementation (NSDI) | February 2019
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Towards a learning optimizer for shared clouds
Chenggang Wu, Alekh Jindal, Saeed Amizadeh, Hiren Patel, Wangchao Le, Shi Qiao, Sriram Rao
Very Large Data Bases | October 2018
-
Dhalion in action: automatic management of streaming applications
Avrilia Floratou, Ashvin Agrawal
Proceedings of the VLDB Endowment | August 2018, 第 11 卷(12)
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Challenges and Opportunities in Transportation Data
Kristin Tufte, Kushal Datta, Alekh Jindal, David Maier, Robert L. Bertini
June 2018
-
Computation Reuse in Analytics Job Service at Microsoft
Alekh Jindal, Shi Qiao, Hiren Patel, Zhicheng Yin, Jieming Di, Malay Bag, Marc Friedman, Yifung Lin, Konstantinos Karanasos, Sriram Rao
2018 International Conference on Management of Data | May 2018
-
Columnar Storage Formats
Encyclopedia of Big Data Technologies | 作者：Springer | 2018
-
Query and Resource Optimization: Bridging the Gap
Lalitha Viswanathan, Alekh Jindal, Konstantinos Karanasos
International Conference on Data Engineering (ICDE) | April 2018
-
Selecting subexpressions to materialize at datacenter scale
Alekh Jindal, Konstantinos Karanasos, Sriram Rao, Hiren Patel
Very Large Data Bases (VLDB) | February 2018
-
Robust Data Partitioning.
Alekh Jindal, Anil Shanbhag, Yi Lu
February 2018
-
Characterizing Resource Sensitivity of Database Workloads
Rathijit Sen, Karthik Ramachandra
High-Performance Computer Architecture | January 2018
-
Froid: Optimization of Imperative Programs in a Relational Database
Karthik Ramachandra, Kwanghyun Park, K. Venkatesh Emani, Alan Halverson, Cesar Galindo-Legaria, Conor Cunningham
Proceedings of VLDB | December 2017, 第 11 卷(4)
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No data left behind: real-time insights from a complex data ecosystem
Manos Karpathiotakis, Avrilia Floratou, Fatma Ozcan, Anastasia Ailamaki
SOCC | September 2017
-
A robust partitioning scheme for ad-hoc query workloads
Anil Shanbhag, Alekh Jindal, Samuel Madden, Jorge Quiane, Aaron J. Elmore
Symposium on Cloud Computing | September 2017
-
Self-Regulating Streaming Systems: Challenges and Opportunities
Avrilia Floratou, Ashvin Agrawal
BIRTE | August 2017
-
Dhalion: Self-Regulating Stream Processing in Heron
Avrilia Floratou, Ashvin Agrawal, Bill Graham, Sriram Rao, Karthik Ramasamy
Proceedings of the VLDB Endowment | August 2017
-
Frequency governors for cloud database OLTP workloads
Rathijit Sen, Alan Halverson
International Symposium on Low Power Electronics and Design | July 2017
-
Pipsqueak: Lean Lambdas with Large Libraries
Edward Oakes, Leon Yang, Kevin Houck, Tyler Harter, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
International Conference on Distributed Computing Systems Workshops | July 2017
-
ROSA: R Optimizations with Static Analysis
Rathijit Sen, Jianqiao Zhu, Jignesh M. Patel, Somesh Jha
RIOT 2017 | July 2017
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Twitter Heron: Towards Extensible Streaming Engines
Maosong Fu, Ashvin Agrawal, Avrilia Floratou, Bill Graham, Andrew Jorgensen, Mark Li, Neng Lu, Karthik Ramasamy, Sriram Rao, Cong Wang
ICDE | May 2017
-
Pareto Governors for Energy-Optimal Computing
Rathijit Sen, David A. Wood
ACM Transactions on Architecture and Code Optimization | April 2017, 第 14 卷(1): pp. 6
-
INGESTBASE: A Declarative Data Ingestion System.
Alekh Jindal, Jorge-Arnulfo Quiané-Ruiz, Samuel Madden
MSR-TR-2017-62 | January 2017
作者：Microsoft
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AdaptDB: adaptive partitioning for distributed joins
Yi Lu, Anil Shanbhag, Alekh Jindal, Samuel Madden
Very Large Data Bases | January 2017
-
A moeba : a shape changing storage system for big data
Anil Shanbhag, Alekh Jindal, Yi Lu, Samuel Madden
Very Large Data Bases | August 2016
-
GraphFrames: an integrated API for mixing graph and relational queries
Ankur Dave, Alekh Jindal, Li Erran Li, Reynold Xin, Joseph Gonzalez, Matei Zaharia
GRADES | June 2016
-
WANalytics: Geo-Distributed Analytics for a Data Intensive World
Ashish Vulimiri, Carlo Curino, Philip Brighten Godfrey, Thomas Jungblut, Konstantinos Karanasos, Jitendra Padhye, George Varghese
International Conference on Management of Data (SIGMOD) | May 2015
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Apache Tez: A Unifying Framework for Modeling and Building Data Processing Applications
Bikas Saha, Hitesh Shah, Siddharth Seth, Gopal Vijayaraghavan, Arun Murthy, Carlo Curino
SIGMOD ’15: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data | May 2015
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Global Analytics in the Face of Bandwidth and Regulatory Constraints
Ashish Vulimiri, Carlo Curino, P. Brighten Godfrey, Thomas Jungblut, Jitu Padhye, George Varghese
12th USENIX Symposium on Networked Systems Design and Implementation (NSDI ’15) | May 2015
ISBN: 978-1-931971-218
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Dynamically Optimizing Queries over Large Scale Data Platforms
Konstantinos Karanasos, Andrey Balmin, Marcel Kutsch, Fatma Ozcan, Vuk Ercegovac, Chunyang Xia, Jesse Jackson
International Conference on Management of Data (SIGMOD) | June 2014
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Delta: Scalable Data Dissemination under Capacity Constraints
Konstantinos Karanasos, Asterios Katsifodimos, Ioana Manolescu
Very Large Data Bases (PVLDB) | December 2013
-
Reservation-based Scheduling: If You’re Late Don’t Blame Us!
Carlo Curino, Djellel E Difallah, Chris Douglas, Subru Krishnan, Rahgu Ramakrishnan, Sriram Rao
MSR-TR-2013-108 | October 2013
Published in SoCC 2014
-
Growing Triples on Trees: an XML-RDF Hybrid Model for Annotated Documents
Francois Goasdoue, Konstantinos Karanasos, Yannis Katsis, Julien Leblay, Ioana Manolescu, Stamatis Zampetakis
Very Large Data Bases Journal (VLDB J.) | June 2013, 第 22 卷: pp. 589-613
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Fact Checking and Analyzing the Web
Francois Goasdoue, Konstantinos Karanasos, Yannis Katsis, Julien Leblay, Ioana Manolescu, Stamatis Zampetakis
International Conference on Management of Data (SIGMOD) | June 2013
-
Fast peak-to-peak behavior with SSD buffer pool
Jaeyoung Do, Donghui Zhang, J. M. Patel, D. J. DeWitt
International Conference on Data Engineering | April 2013
-
Towards energy-efficient database cluster design
Willis Lang, Stavros Harizopoulos, Jignesh M. Patel, Mehul A. Shah, Dimitris Tsirogiannis
2012 Very Large Data Bases | August 2012, 第 5 卷(11): pp. 1684-1695
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Query optimization in Microsoft SQL Server PDW
Srinath Shankar, Rimma Nehme, Josep Aguilar-Saborit, Andrew Chung, Mostafa Elhemali, Eric Robinson, Mahadevan Sankara Subramanian, David DeWitt, César Galindo-Legaria, Alan Halverson
International Conference on Management of Data | May 2012
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GSLPI: A Cost-Based Query Progress Indicator
Jiexing Li, Rimma V. Nehme, Jeffrey Naughton
International Conference on Data Engineering | March 2012
DOI PDF Publication Publication Publication Publication Publication
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View Selection in Semantic Web Databases
Francois Goasdoue, Konstantinos Karanasos, Julien Leblay, Ioana Manolescu
Very Large Data Bases (PVLDB) | October 2011, 第 5 卷: pp. 97-108
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On energy management, load balancing and replication
Willis Lang, Jignesh M. Patel, Jeffrey F. Naughton
International Conference on Management of Data | June 2010
DOI PDF Publication Publication Publication Publication Publication
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-
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Autotuning Systems: Techniques, Challenges, and Opportunities
Brian Kroth, Sergiy Matusevych, Yiwen Zhu
SIGMOD 2025 | June 2025
-
TUNA: Tuning Unstable and Noisy Cloud Applications
Johannes Freischuetz, Konstantinos Kanellis, Brian Kroth, Shivaram Venkataraman
Eurosys 2025 | March 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, 第 17 卷: pp. 4269-4272
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Performance Roulette: How Cloud Weather Affects ML-Based System Optimization
Johannes Freischuetz, Konstantinos Kanellis, Brian Kroth, Shivaram Venkataraman
ML for Systems Workshop at NeurIPS 2023 | December 2023
-
NyxCache: Flexible and Efficient Multi-tenant Persistent Memory Caching
Kan Wu, Kaiwei Tu, Yuvraj Patel, Rathijit Sen, Kwanghyun Park, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
20th USENIX Conference on File and Storage Technologies | February 2022
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The Storage Hierarchy is Not a Hierarchy: Optimizing Caching on Modern Storage Devices with Orthus
Kan Wu, Zhihan Guo, Guanzhou Hu, Kaiwei Tu, Ramnatthan Alagappan, Rathijit Sen, Kwanghyun Park, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
19th USENIX Conference on File and Storage Technologies | February 2021
-
Unearthing inter-job dependencies for better cluster scheduling
Andrew Chung, Subru Krishnan, Konstantinos Karanasos, Carlo Curino, Gregory R. Ganger
Symposium on Operating Systems Design and Implementation (OSDI) | November 2020
-
Lessons learned from the early performance evaluation of Intel Optane DC persistent memory in DBMS
Yinjun Wu, Kwanghyun Park, Rathijit Sen, Brian Kroth, Jae Young Do
2020 Data Management on New Hardware | June 2020
-
Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings
Tarique Siddiqui, Alekh Jindal, Shi Qiao, Hiren Patel, Wangchao le
SIGMOD 2020: International Conference on Management of Data | February 2020
-
Neptune: Scheduling Suspendable Tasks for Unified Stream/Batch Applications
Panagiotis Garefalakis, Konstantinos Karanasos, Peter Pietzuch
Symposium on Cloud Computing (SoCC) | November 2019
-
Exploiting Intel Optane SSD for Microsoft SQL Server
Kan Wu, Andrea Arpaci-Dusseau, Remzi Arpaci-Dusseau, Rathijit Sen, Kwanghyun Park
DaMoN 2019 | July 2019
-
Hydra: a federated resource manager for data-center scale analytics
Carlo Curino, Subru Krishnan, Konstantinos Karanasos, Sriram Rao, Giovanni M. Fumarola, Botong Huang, Kishore Chaliparambil, Arun Suresh, Young Chen, Solom Heddaya, Roni Burd, Sarvesh Sakalanaga, Chris Douglas, Bill Ramsey, Raghu Ramakrishnan
Symposium on Networked Systems Design and Implementation (NSDI) | February 2019
-
SOCK: Serverless-Optimized Containers.
Edward Oakes, Leon Yang, Dennis Zhou, Kevin Houck, Tyler Caraza-Harter, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
;login: | December 2018, 第 43 卷(3)
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PRETZEL: opening the black box of machine learning prediction serving systems
Yunseong Lee, Alberto Scolari, Byung-Gon Chun, Marco Domenico Santambrogio, Matteo Interlandi, Markus Weimer
Operating Systems Design and Implementation | October 2018
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Netco: Cache and I/O Management for Analytics over Disaggregated Stores
Virajith Jalaparti, Chris Douglas, Mainak Ghosh, Ashvin Agrawal, Avrilia Floratou, Srikanth Kandula, Ishai Menache, Joseph (Seffi) Naor, Sriram Rao
ACM Symposium on Cloud Computing (SOCC) | October 2018
Best Paper Award
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SOCK: rapid task provisioning with serverless-optimized containers
Edward Oakes, Leon Yang, Dennis Zhou, Kevin Houck, Tyler Harter, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
USENIX Annual Technical Conference | July 2018
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Survivability of Cloud Databases – Factors and Prediction
Jose Picado, Willis Lang, Edward C. Thayer
International Conference on Management of Data | May 2018
-
Computation Reuse in Analytics Job Service at Microsoft
Alekh Jindal, Shi Qiao, Hiren Patel, Zhicheng Yin, Jieming Di, Malay Bag, Marc Friedman, Yifung Lin, Konstantinos Karanasos, Sriram Rao
2018 International Conference on Management of Data | May 2018
-
Selecting subexpressions to materialize at datacenter scale
Alekh Jindal, Konstantinos Karanasos, Sriram Rao, Hiren Patel
Very Large Data Bases (VLDB) | February 2018
-
Advancements in YARN Resource Manager
Konstantinos Karanasos, Arun Suresh, Chris Douglas
Encyclopedia of Big Data Technologies | February 2018
-
Characterizing Resource Sensitivity of Database Workloads
Rathijit Sen, Karthik Ramachandra
High-Performance Computer Architecture | January 2018
-
Medea: Scheduling of Long Running Applications in Shared Production Clusters
Panagiotis Garefalakis, Konstantinos Karanasos, Peter Pietzuch, Arun Suresh, Sriram Rao
European Conference on Computer Systems (EuroSys) | January 2018
-
Towards High-Performance Prediction Serving Systems
Yunseong Lee, Alberto Scolari, Byung-Gon Chun, Matteo Interlandi, Markus Weimer
31st Conference on Neural Information Processing Systems | December 2017
-
Apache REEF: Retainable Evaluator Execution Framework
Byung-Gon Chun, Tyson Condie, Yingda Chen, Brian Cho, Andrew Chung, Carlo Curino, Chris Douglas, Beomyeol Jeon, Joo Seong Jeong, Gyewon Lee, Yunseong Lee, Tony Majestro, Dahlia Malkhi, Sergiy Matusevych, Brandon Myers, Mariia Mykhailova, Shravan Narayanamurthy, Joseph Noor, Raghu Ramakrishnan, Sriram Rao, Russell Sears, Beysim Sezgin, Taegeon Um, Julia Wang, Youngseok Yang, Raghu Ramakrishnan, Carlo Curino, Matteo Interlandi
ACM Transactions on Computer Systems | October 2017, 第 35 卷(2): pp. 5
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Energy-Proportional Computing: A New Definition
Rathijit Sen, David A. Wood
IEEE Computer | July 2017, 第 50 卷(8): pp. 26-33
-
Frequency governors for cloud database OLTP workloads
Rathijit Sen, Alan Halverson
International Symposium on Low Power Electronics and Design | July 2017
-
Pareto Governors for Energy-Optimal Computing
Rathijit Sen, David A. Wood
ACM Transactions on Architecture and Code Optimization | April 2017, 第 14 卷(1): pp. 6
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Resource bricolage and resource selection for parallel database systems
Jiexing Li, Jeffrey F. Naughton, Rimma V. Nehme
Very Large Data Bases | January 2017
-
Morpheus: Towards Automated SLOs for Enterprise Clusters
Sangeetha Abdu Jyothi, Carlo Curino, Ishai Menache, Shravan Matthur Narayanamurthy, Alexey Tumanov, Jonathan Yaniv, Ruslan Mavlyutov, Íñigo Goiri, Subru Krishnan, Janardhan (Jana) Kulkarni, Sriram Rao
2016 International Symposium on Operating Systems Design and Implementation (OSDI) | November 2016
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PerfOrator: Eloquent Performance Models for Resource Optimization
Dharmesh Kakadia, Kaushik Rajan, Carlo Curino, Subru Krishnan
ACM Symposium on Cloud Computing 2016 (SoCC’16) | October 2016
-
Efficient Queue Management for Cluster Scheduling
Jeff Rasley, Konstantinos Karanasos, Srikanth Kandula, Rodrigo Fonseca, Sriram Rao, Milan Vojnovic
European Conference on Computer Systems (EuroSys) | April 2016
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Do the Hard Stuff First: Scheduling Dependent Computations in Data Analytics Clusters
Robert Grandl, Srikanth Kandula, Sriram Rao, Aditya Akella, Janardhan (Jana) Kulkarni
MSR-TR-2016-19 | February 2016
作者：Microsoft
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Mercury: Hybrid Centralized and Distributed Scheduling in Large Shared Clusters
Konstantinos Karanasos, Sriram Rao, Carlo Curino, Chris Douglas, Kishore Chaliparambil, Giovanni Matteo Fumarola, Solom Heddaya, Raghu Ramakrishnan, Sarvesh Sakalanaga
USENIX Annual Technical Conference (USENIX ATC’2015) | July 2015
-
Blind men and an elephant coalescing open-source, academic, and industrial perspectives on BigData
Chris Douglas, Carlo Curino
International Conference on Data Engineering | April 2015
-
WANalytics: Analytics for a Geo-Distributed Data-Intensive World
Ashish Vulimiri, Carlo Curino, Brighten Godfrey, Konstantinos Karanasos, George Varghese
Conference on Innovative Data Systems Research (CIDR) | January 2015
-
Multi-resource Packing for Cluster Schedulers
Robert Grandl, Ganesh Ananthanarayanan, Srikanth Kandula, Sriram Rao, Aditya Akella
ACM SIGCOMM | August 2014
-
Indexing HDFS data in PDW: splitting the data from the index
Vinitha Reddy Gankidi, Nikhil Teletia, Jignesh M. Patel, Alan Halverson, David J. DeWitt
Very Large Data Bases | July 2014
-
Partial results in database systems
Willis Lang, Rimma V. Nehme, Eric Robinson, Jeffrey F. Naughton
International Conference on Management of Data | June 2014
-
Distributed and Scalable PCA in the Cloud
Arun Kumar, Vijay Narayanan, Nikos Karampatziakis, Paul Mineiro, Markus Weimer
MSR-TR-2014-165 | January 2014
作者：Microsoft
Apache Reef Research Paper
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Reservation-based Scheduling: If You’re Late Don’t Blame Us!
Carlo Curino, Djellel E Difallah, Chris Douglas, Subru Krishnan, Rahgu Ramakrishnan, Sriram Rao
MSR-TR-2013-108 | October 2013
Published in SoCC 2014
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Split query processing in polybase
David J. DeWitt, Rimma Nehme, Srinath Shankar, Josep Aguilar-Saborit, Artin Avanes, Miro Flasza, Jim Gramling, Alan Halverson
2013 ACM SIGMOD International Conference on Management of Data | June 2013
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Towards energy-efficient database cluster design
Willis Lang, Stavros Harizopoulos, Jignesh M. Patel, Mehul A. Shah, Dimitris Tsirogiannis
2012 Very Large Data Bases | August 2012, 第 5 卷(11): pp. 1684-1695
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Toward Progress Indicators on Steroids for Big Data Systems.
Jiexing Li, Rimma V. Nehme, Jeffrey F. Naughton
Conference on Innovative Data Systems Research | January 2012
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Rethinking Query Processing for Energy Efficiency: Slowing Down to Win the Race.
Nicolas Bruno, Surajit Chaudhuri, Arnd Christian König, Vivek Narasayya, Ravi Ramamurthy, Manoj Syamala
IEEE Data(base) Engineering Bulletin | November 2011, 第 34 卷: pp. 12-19
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The Mimicking Octopus: Towards a one-size-fits-all Database Architecture
Alekh Jindal
36th International Conference on VLDB | September 2010
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Wimpy node clusters: what about non-wimpy workloads?
Willis Lang, Jignesh M. Patel, Srinath Shankar
Data Management on New Hardware | June 2010
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Towards Eco-friendly Database Management Systems
Willis Lang, Jignesh M. Patel
Conference on Innovative Data Systems Research | December 2009
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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, 第 17 卷: pp. 4269-4272
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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
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PolySem: Efficient Polyglot Analytics on Semantic Data
Xinyu Liu, Venkatesh Emani, Avrilia Floratou, Joyce Cahoon, Philip Seamark, Carlo Curino
Poly’23: Polystore systems for heterogeneous data in multiple databases with privacy and security assurances | August 2023
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PyFroid: Scaling Data Analysis on a Commodity Workstation
Venkatesh Emani, Avrilia Floratou, Carlo Curino
EDBT 2024 | August 2023
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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, 第 51 卷(2): pp. 30-37
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Magpie: Python at Speed and Scale using Cloud Backends
Alekh Jindal, Venkatesh Emani, Maureen Daum, Olga Poppe, Brandon Haynes, Anna Pavlenko, Ayushi Gupta, Karthik Ramachandra, Carlo Curino, Andreas C. Müller, Wentao Wu, Hiren Patel
Conference on Innovative Data Systems Research (CIDR 2021) | February 2021
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ROSA: R Optimizations with Static Analysis
Rathijit Sen, Jianqiao Zhu, Jignesh M. Patel, Somesh Jha
RIOT 2017 | July 2017
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OneProvenance: Efficient Extraction of Dynamic Coarse-Grained Provenance From Database Query Event Logs
Fotis Psallidas, Ashvin Agrawal, Chandru Sugunan, Khaled Ibrahim, Konstantinos Karanasos, Jesus Camacho-Rodriguez, A. Floratou, C. Curino, R. Ramakrishnan
Proc. VLDB Endow. | August 2023, 第 16 卷: pp. 3662-3675
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A Tensor Compiler for Unified Machine Learning Prediction Serving
Supun Nakandala, Karla Saur, Gyeong-In Yu, Konstantinos Karanasos, Carlo Curino, Markus Weimer, Matteo Interlandi
Symposium on Operating Systems Design and Implementation (OSDI) | November 2020
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Netco: Cache and I/O Management for Analytics over Disaggregated Stores
Virajith Jalaparti, Chris Douglas, Mainak Ghosh, Ashvin Agrawal, Avrilia Floratou, Srikanth Kandula, Ishai Menache, Joseph (Seffi) Naor, Sriram Rao
ACM Symposium on Cloud Computing (SOCC) | October 2018
Best Paper Award
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Batch-Expansion Training: An Efficient Optimization Framework
Michał Dereziński, Dhruv Mahajan, S. Sathiya Keerthi, S. V. N. Vishwanathan, Markus Weimer
International Conference on Artificial Intelligence and Statistics | February 2018
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Towards Geo-Distributed Machine Learning.
Ignacio Cano, Dhruv Mahajan, Giovanni Matteo Fumarola, Arvind Krishnamurthy, Markus Weimer, Carlo Curino
IEEE Data(base) Engineering Bulletin | December 2015, 第 40 卷: pp. 41-59
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Partial results in database systems
Willis Lang, Rimma V. Nehme, Eric Robinson, Jeffrey F. Naughton
International Conference on Management of Data | June 2014
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Towards Multi-Tenant Performance SLOs
Willis Lang, Srinath Shankar, Jignesh M. Patel, Ajay Kalhan
IEEE Transactions on Knowledge and Data Engineering | May 2014, 第 26 卷(6): pp. 1447-1463
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Declarative Systems for Large-Scale Machine Learning.
Vinayak R. Borkar, Yingyi Bu, Michael J. Carey, Joshua Rosen, Neoklis Polyzotis, Tyson Condie, Markus Weimer, Raghu Ramakrishnan
IEEE Data(base) Engineering Bulletin | July 2012, 第 35 卷: pp. 24-32
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WWW 2012 Tutorial: New Templates for Scalable Data Analysis
Amr Ahmed, Alexander J. Smola, Markus Weimer
25th International World Wide Web Conference | April 2012
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Turbocharging DBMS buffer pool using SSDs
Jaeyoung Do, Donghui Zhang, Jignesh M. Patel, David J. DeWitt, Jeffrey F. Naughton, Alan Halverson
International Conference on Management of Data | June 2011
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Automated partitioning design in parallel database systems
Rimma Nehme, Nicolas Bruno
International Conference on Management of Data | June 2011
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Energy management for MapReduce clusters
Willis Lang, Jignesh M. Patel
Very Large Data Bases | August 2010
DOI PDF PDF Publication Publication Publication Publication Publication
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OneProvenance: Efficient Extraction of Dynamic Coarse-Grained Provenance From Database Query Event Logs
Fotis Psallidas, Ashvin Agrawal, Chandru Sugunan, Khaled Ibrahim, Konstantinos Karanasos, Jesus Camacho-Rodriguez, A. Floratou, C. Curino, R. Ramakrishnan
Proc. VLDB Endow. | August 2023, 第 16 卷: pp. 3662-3675
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Robust Estimation of Resource Consumption for SQL Queries using Statistical Techniques
Jiexing Li, Arnd Christian König, Arnd Christian König, Vivek Narasayya, Surajit Chaudhuri
38th International Conference on Very Large Databases | August 2012
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OneProvenance: Efficient Extraction of Dynamic Coarse-Grained Provenance From Database Query Event Logs
Fotis Psallidas, Ashvin Agrawal, Chandru Sugunan, Khaled Ibrahim, Konstantinos Karanasos, Jesus Camacho-Rodriguez, A. Floratou, C. Curino, R. Ramakrishnan
Proc. VLDB Endow. | August 2023, 第 16 卷: pp. 3662-3675
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FPGA for Aggregate Processing: The Good, The Bad, and The Ugly
Zubeyr F. Eryilmaz, Aarati Kakaraparthy, Jignesh M. Patel, Rathijit Sen, Kwanghyun Park
International Conference on Data Engineering (ICDE) | April 2021
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Hardware Acceleration for DBMS Machine Learning Scoring: Is It Worth the Overheads?
Zahra Azad, Rathijit Sen, Kwanghyun Park, Ajay Joshi
International Symposium on Performance Analysis of Systems and Software (ISPASS) | March 2021
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A Tensor Compiler for Unified Machine Learning Prediction Serving
Supun Nakandala, Karla Saur, Gyeong-In Yu, Konstantinos Karanasos, Carlo Curino, Markus Weimer, Matteo Interlandi
Symposium on Operating Systems Design and Implementation (OSDI) | November 2020
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Optimizing databases by learning hidden parameters of solid state drives
Aarati Kakaraparthy, Jignesh M. Patel, Kwanghyun Park, Brian Kroth
Proceedings of VLDB | December 2019
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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, 第 17 卷: pp. 4269-4272
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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, 第 2 卷: pp. 149
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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, 第 17 卷: pp. 1618-1627
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Optimizing Data Pipelines for Machine Learning in Feature Stores
Rui Liu, Kwanghyun Park, Fotis Psallidas, Xiaoyong Zhu, Jinghui Mo, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos, Yuanyuan Tian, Jesús Camacho-Rodríguez
Proc. VLDB Endow. | August 2023, 第 16 卷: pp. 4230-4239
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OneProvenance: Efficient Extraction of Dynamic Coarse-Grained Provenance From Database Query Event Logs
Fotis Psallidas, Ashvin Agrawal, Chandru Sugunan, Khaled Ibrahim, Konstantinos Karanasos, Jesus Camacho-Rodriguez, A. Floratou, C. Curino, R. Ramakrishnan
Proc. VLDB Endow. | August 2023, 第 16 卷: pp. 3662-3675
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A Deep Dive into Common Open Formats for Analytical DBMSs
Chunwei Liu, Anna Pavlenko, Matteo Interlandi, Brandon Haynes
Proc. VLDB Endow. | June 2023, 第 16 卷: pp. 3044-3056
Best Paper Runner-Up
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DIAMETRICS: Benchmarking Query Engines at Scale
Shaleen Deep, Anja Gruenheid, Kruthi Nagaraj, Hiro Naito, Jeffrey Naughton, Stratis Viglas
Communications of The ACM | December 2022, 第 65 卷(12): pp. 105-112
Research Highlight
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Comprehensive and Efficient Workload Summarization
Shaleen Deep, Anja Gruenheid, Paraschos Koutris, Stratis Viglas, Jeffrey Naughton
Datenbank-Spektrum | November 2022
Research Highlight
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Diversity and Inclusion Activities in Database Conferences: A 2021 Report.
Sihem Amer-Yahia, Yael Amsterdamer, Sourav S. Bhowmick,, Angela Bonifati, Philippe Bonnet, Renata Borovica-Gajic, Barbara Catania, Tania Cerquitelli, Silvia Chiusano, Panos K. Chrysanthis, Carlo Curino, Jérôme Darmont, Amr El Abbadi, Avrilia Floratou, Juliana Freire, Alekh Jindal, Vana Kalogeraki, Georgia Koutrika, Arun Kumar, Sujaya Maiyya, Alexandra Meliou, Madhulika Mohanty, Felix Naumann, Nele Sina Noack, Liat Peterfreund, Fatma Özcan, Wenny Rahayu, Wang-Chiew Tan, Yuanyuan Tian, Pinar Tözün, Genoveva Vargas-Solar, Neeraja J. Yadwadkar, Meihui Zhang
SIGMOD Record | November 2022
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Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem
Yuki Asada, Victor Fu, Apurva Gandhi, Advitya Gemawat, Lihao Zhang, Dong He, Vivek Gupta, Ehi Nosakhare, Dalitso Banda, Rathijit Sen, Matteo Interlandi
VLDB | September 2022, 第 15 卷(12): pp. 3598-3601
Best demo award
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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, 第 51 卷(2): pp. 30-37
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Applied Research Lessons from CloudViews Project
Alekh Jindal
Sigmod Record | December 2020, 第 49 卷(3): pp. 37-42
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BlackMagic: Automatic Inlining of Scalar UDFs into SQL Queries with Froid
Karthik Ramachandra, Kwanghyun Park
Proceedings of VLDB | August 2019, 第 12 卷(12): pp. 1810-1813
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SOCK: Serverless-Optimized Containers.
Edward Oakes, Leon Yang, Dennis Zhou, Kevin Houck, Tyler Caraza-Harter, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
;login: | December 2018, 第 43 卷(3)
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Dhalion in action: automatic management of streaming applications
Avrilia Floratou, Ashvin Agrawal
Proceedings of the VLDB Endowment | August 2018, 第 11 卷(12)
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Advancements in YARN Resource Manager
Konstantinos Karanasos, Arun Suresh, Chris Douglas
Encyclopedia of Big Data Technologies | February 2018
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Froid: Optimization of Imperative Programs in a Relational Database
Karthik Ramachandra, Kwanghyun Park, K. Venkatesh Emani, Alan Halverson, Cesar Galindo-Legaria, Conor Cunningham
Proceedings of VLDB | December 2017, 第 11 卷(4)
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Apache REEF: Retainable Evaluator Execution Framework
Byung-Gon Chun, Tyson Condie, Yingda Chen, Brian Cho, Andrew Chung, Carlo Curino, Chris Douglas, Beomyeol Jeon, Joo Seong Jeong, Gyewon Lee, Yunseong Lee, Tony Majestro, Dahlia Malkhi, Sergiy Matusevych, Brandon Myers, Mariia Mykhailova, Shravan Narayanamurthy, Joseph Noor, Raghu Ramakrishnan, Sriram Rao, Russell Sears, Beysim Sezgin, Taegeon Um, Julia Wang, Youngseok Yang, Raghu Ramakrishnan, Carlo Curino, Matteo Interlandi
ACM Transactions on Computer Systems | October 2017, 第 35 卷(2): pp. 5
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Energy-Proportional Computing: A New Definition
Rathijit Sen, David A. Wood
IEEE Computer | July 2017, 第 50 卷(8): pp. 26-33
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Pareto Governors for Energy-Optimal Computing
Rathijit Sen, David A. Wood
ACM Transactions on Architecture and Code Optimization | April 2017, 第 14 卷(1): pp. 6
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Towards Geo-Distributed Machine Learning.
Ignacio Cano, Dhruv Mahajan, Giovanni Matteo Fumarola, Arvind Krishnamurthy, Markus Weimer, Carlo Curino
IEEE Data(base) Engineering Bulletin | December 2015, 第 40 卷: pp. 41-59
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Towards Multi-Tenant Performance SLOs
Willis Lang, Srinath Shankar, Jignesh M. Patel, Ajay Kalhan
IEEE Transactions on Knowledge and Data Engineering | May 2014, 第 26 卷(6): pp. 1447-1463
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Growing Triples on Trees: an XML-RDF Hybrid Model for Annotated Documents
Francois Goasdoue, Konstantinos Karanasos, Yannis Katsis, Julien Leblay, Ioana Manolescu, Stamatis Zampetakis
Very Large Data Bases Journal (VLDB J.) | June 2013, 第 22 卷: pp. 589-613
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Towards energy-efficient database cluster design
Willis Lang, Stavros Harizopoulos, Jignesh M. Patel, Mehul A. Shah, Dimitris Tsirogiannis
2012 Very Large Data Bases | August 2012, 第 5 卷(11): pp. 1684-1695
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Declarative Systems for Large-Scale Machine Learning.
Vinayak R. Borkar, Yingyi Bu, Michael J. Carey, Joshua Rosen, Neoklis Polyzotis, Tyson Condie, Markus Weimer, Raghu Ramakrishnan
IEEE Data(base) Engineering Bulletin | July 2012, 第 35 卷: pp. 24-32
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Rethinking Query Processing for Energy Efficiency: Slowing Down to Win the Race.
Nicolas Bruno, Surajit Chaudhuri, Arnd Christian König, Vivek Narasayya, Ravi Ramamurthy, Manoj Syamala
IEEE Data(base) Engineering Bulletin | November 2011, 第 34 卷: pp. 12-19
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View Selection in Semantic Web Databases
Francois Goasdoue, Konstantinos Karanasos, Julien Leblay, Ioana Manolescu
Very Large Data Bases (PVLDB) | October 2011, 第 5 卷: pp. 97-108
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Autotuning Systems: Techniques, Challenges, and Opportunities
Brian Kroth, Sergiy Matusevych, Yiwen Zhu
SIGMOD 2025 | June 2025
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TUNA: Tuning Unstable and Noisy Cloud Applications
Johannes Freischuetz, Konstantinos Kanellis, Brian Kroth, Shivaram Venkataraman
Eurosys 2025 | March 2025
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LST-Bench: Benchmarking Log-Structured Tables in the Cloud
Jesús Camacho-Rodríguez, Ashvin Agrawal, Anja Gruenheid, Ashit Gosalia, Cristian Petculescu, Josep Aguilar-Saborit, Avrilia Floratou, Carlo Curino, Raghu Ramakrishnan
ACM SIGMOD | June 2024
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Sibyl: Forecasting Time-Evolving Query Workloads
Hanxian Huang, Tarique Siddiqui, Rana Alotaibi, Carlo Curino, Jyoti Leeka, Alekh Jindal, Jishen Zhao, Jesús Camacho-Rodríguez, Yuanyuan Tian
SIGMOD | June 2024
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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
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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
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Performance Roulette: How Cloud Weather Affects ML-Based System Optimization
Johannes Freischuetz, Konstantinos Kanellis, Brian Kroth, Shivaram Venkataraman
ML for Systems Workshop at NeurIPS 2023 | December 2023
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GEqO: ML-Accelerated Semantic Equivalence Detection
Brandon Haynes, Rana Alotaibi, Anna Pavlenko, Jyoti Leeka, Alekh Jindal, Yuanyuan Tian
Proceedings of the ACM on Management of Data | December 2023
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PolySem: Efficient Polyglot Analytics on Semantic Data
Xinyu Liu, Venkatesh Emani, Avrilia Floratou, Joyce Cahoon, Philip Seamark, Carlo Curino
Poly’23: Polystore systems for heterogeneous data in multiple databases with privacy and security assurances | August 2023
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PyFroid: Scaling Data Analysis on a Commodity Workstation
Venkatesh Emani, Avrilia Floratou, Carlo Curino
EDBT 2024 | August 2023
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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
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Query Processing on Gaming Consoles
Wei Cui, Qianxi Zhang, Jesús Camacho-Rodríguez, Spyros Blanas, Brandon Haynes, Yinan Li, Peng Cheng, Ravishankar Ramamurthy, Rathijit Sen, Matteo Interlandi
June 2023
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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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Schema Matching using Pre-Trained Language Models
Yunjia Zhang, Avrilia Floratou, Joyce Cahoon, Subru Krishnan, Andreas C. Müller, Dalitso Banda, Fotis Psallidas, Jignesh M. Patel
ICDE | January 2023
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The Fine-Grained Complexity of CFL Reachability
Paraschos Koutris, Shaleen Deep
Principles of Programming Languages (POPL 2023) | January 2023
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The Tensor Data Platform: Towards an AI-centric Database System
Apurva Gandhi, Yuki Asada, Victor Fu, Advitya Gemawat, Lihao Zhang, Rathijit Sen, Carlo Curino, Jesús Camacho-Rodríguez, Matteo Interlandi
CIDR | January 2023
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Query Processing on Tensor Computation Runtimes
Dong He, Supun Nakandala, Dalitso Banda, Rathijit Sen, Karla Saur, Kwanghyun Park, Carlo Curino, Jesús Camacho-Rodríguez, Konstantinos Karanasos, Matteo Interlandi
VLDB 2022 | September 2022
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Pipemizer: An Optimizer for Analytics Data Pipelines
Sunny Gakhar, Joyce Cahoon, Wangchao Le, Xiangnan Li, Kaushik Ravichandran, Hiren Patel, Marc Friedman, Brandon Haynes, Shi Qiao, Alekh Jindal, Jyoti Leeka
PVLDB | September 2022
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Containerized Execution of UDFs: An Experimental Evaluation
Karla Saur, Tara Mirmira, Konstantinos Karanasos, Jesús Camacho-Rodríguez
VLDB 2022 | September 2022
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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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Deploying a Steered Query Optimizer in Production at Microsoft
Wangda Zhang, Matteo Interlandi, Paul Mineiro, Shi Qiao, Nasim Ghazanfari, Karlen Lie, Marc Friedman, Rafah Hosn, Hiren Patel, Alekh Jindal
2022 International Conference on Management of Data | July 2022
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VIP Hashing — Adapting to Skew in Popularity of Data on the Fly
Aarati Kakaraparthy, Jignesh M. Patel, Brian Kroth, Kwanghyun Park
VLDB 2022 | June 2022
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End-to-end Optimization of Machine Learning Prediction Queries
Kwanghyun Park, Karla Saur, Dalitso Banda, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos
SIGMOD | June 2022
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LlamaTune: Sample-Efficient DBMS Configuration Tuning
Konstantinos Kanellis, Cong Ding, Brian Kroth, Andreas C. Müller, Carlo Curino, Shivaram Venkataraman
VLDB 2022 | March 2022
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NyxCache: Flexible and Efficient Multi-tenant Persistent Memory Caching
Kan Wu, Kaiwei Tu, Yuvraj Patel, Rathijit Sen, Kwanghyun Park, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
20th USENIX Conference on File and Storage Technologies | February 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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Steering Query Optimizers: A Practical Take on Big Data Workloads
Parimarjan Negi, Matteo Interlandi, Ryan Marcus, Mohammad Alizadeh, Tim Kraska, Marc Friedman, Alekh Jindal
2021 International Conference on Management of Data | June 2021
Honorable mention for the Industry Track
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HADAD: A Lightweight Approach for Optimizing Hybrid Complex Analytics Queries
Rana Alotaibi, Bogdan Cautis, Alin Deutsch, Ioana Manolescu
2021 International Conference on Management of Data | June 2021
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HADAD: A Lightweight Approach for Optimizing Hybrid Complex Analytics Queries
Rana Alotaibi, Bogdan Cautis, Alin Deutsch, Ioana Manolescu
SIGMOD | June 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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Microlearner: A fine-grained Learning Optimizer for Big Data Workloads at Microsoft
Alekh Jindal, Shi Qiao, Rathijit Sen, Hiren Patel
2021 International Conference on Data Engineering | April 2021
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Property Graph Schema Optimization for Domain-Specific Knowledge Graphs
Rana Alotaibi, Chuan Lei, Abdul Quamar, Vasilis Efthymiou, Fatma Ozcan
ICDE | April 2021
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FPGA for Aggregate Processing: The Good, The Bad, and The Ugly
Zubeyr F. Eryilmaz, Aarati Kakaraparthy, Jignesh M. Patel, Rathijit Sen, Kwanghyun Park
International Conference on Data Engineering (ICDE) | April 2021
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Production Experiences from Computation Reuse at Microsoft
Alekh Jindal, Shi Qiao, Hiren Patel, Abhishek Roy, Jyoti Leeka, Brandon Haynes
2021 Extending Database Technology | March 2021
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Hardware Acceleration for DBMS Machine Learning Scoring: Is It Worth the Overheads?
Zahra Azad, Rathijit Sen, Kwanghyun Park, Ajay Joshi
International Symposium on Performance Analysis of Systems and Software (ISPASS) | March 2021
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The Storage Hierarchy is Not a Hierarchy: Optimizing Caching on Modern Storage Devices with Orthus
Kan Wu, Zhihan Guo, Guanzhou Hu, Kaiwei Tu, Ramnatthan Alagappan, Rathijit Sen, Kwanghyun Park, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
19th USENIX Conference on File and Storage Technologies | February 2021
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Magpie: Python at Speed and Scale using Cloud Backends
Alekh Jindal, Venkatesh Emani, Maureen Daum, Olga Poppe, Brandon Haynes, Anna Pavlenko, Ayushi Gupta, Karthik Ramachandra, Carlo Curino, Andreas C. Müller, Wentao Wu, Hiren Patel
Conference on Innovative Data Systems Research (CIDR 2021) | February 2021
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Unearthing inter-job dependencies for better cluster scheduling
Andrew Chung, Subru Krishnan, Konstantinos Karanasos, Carlo Curino, Gregory R. Ganger
Symposium on Operating Systems Design and Implementation (OSDI) | November 2020
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A Tensor Compiler for Unified Machine Learning Prediction Serving
Supun Nakandala, Karla Saur, Gyeong-In Yu, Konstantinos Karanasos, Carlo Curino, Markus Weimer, Matteo Interlandi
Symposium on Operating Systems Design and Implementation (OSDI) | November 2020
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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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ESTOCADA: Towards Scalable Polystore Systems
Rana Alotaibi, Bogdan Cautis, Alin Deutsch, M. Latrache, Ioana Manolescu, Y. Yang
VLDB | July 2020
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AutoToken: predicting peak parallelism for big data analytics at Microsoft
Rathijit Sen, Alekh Jindal, Hiren Patel, Shi Qiao
Very Large Data Bases | July 2020
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Towards Plan-aware Resource Allocation in Serverless Query Processing
Malay Bag, Alekh Jindal, Hiren Patel
USENIX conference on Hot Topics in Cloud Ccomputing | July 2020
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Lessons learned from the early performance evaluation of Intel Optane DC persistent memory in DBMS
Yinjun Wu, Kwanghyun Park, Rathijit Sen, Brian Kroth, Jae Young Do
2020 Data Management on New Hardware | June 2020
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Automated Tuning of Query Degree of Parallelism via Machine Learning
Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi
2020 International Conference on Management of Data | June 2020
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Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings
Tarique Siddiqui, Alekh Jindal, Shi Qiao, Hiren Patel, Wangchao le
SIGMOD 2020: International Conference on Management of Data | February 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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Extending Relational Query Processing with ML Inference
Konstantinos Karanasos, Matteo Interlandi, Doris Xin, Fotis Psallidas, Rathijit Sen, Kwanghyun Park, Ivan Popivanov, Supun Nakandal, Subru Krishnan, Markus Weimer, Yuan Yu, Raghu Ramakrishnan, Carlo Curino
Conference on Innovative Data Systems Research (CIDR) | January 2020
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Optimizing databases by learning hidden parameters of solid state drives
Aarati Kakaraparthy, Jignesh M. Patel, Kwanghyun Park, Brian Kroth
Proceedings of VLDB | December 2019
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Big Data Processing at Microsoft: Hyper Scale, Massive Complexity, and Minimal Cost
Hiren Patel, Alekh Jindal, Clemens Szyperski
Symposium on Cloud Computing | November 2019
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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 | November 2019
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Neptune: Scheduling Suspendable Tasks for Unified Stream/Batch Applications
Panagiotis Garefalakis, Konstantinos Karanasos, Peter Pietzuch
Symposium on Cloud Computing (SoCC) | November 2019
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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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SparkCruise: handsfree computation reuse in Spark
Abhishek Roy, Alekh Jindal, Hiren Patel, Ashit Gosalia, Subru Krishnan, Carlo Curino
Very Large Data Bases | July 2019
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Exploiting Intel Optane SSD for Microsoft SQL Server
Kan Wu, Andrea Arpaci-Dusseau, Remzi Arpaci-Dusseau, Rathijit Sen, Kwanghyun Park
DaMoN 2019 | July 2019
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Towards Scalable Hybrid Stores: Constraint-Based Rewriting to the Rescue
Rana Alotaibi, Damian Bursztyn, Alin Deutsch, Ioana Manolescu, Stamatis Zampetakis
SIGMOD | June 2019
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Peering through the Dark: An Owl’s View of Inter-job Dependencies and Jobs’ Impact in Shared Clusters
Andrew Chung, Carlo Curino, Subru Krishnan, Konstantinos Karanasos, Panagiotis Garefalakis, Gregory R. Ganger
International Conference on Management of Data (SIGMOD) | June 2019
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Hydra: a federated resource manager for data-center scale analytics
Carlo Curino, Subru Krishnan, Konstantinos Karanasos, Sriram Rao, Giovanni M. Fumarola, Botong Huang, Kishore Chaliparambil, Arun Suresh, Young Chen, Solom Heddaya, Roni Burd, Sarvesh Sakalanaga, Chris Douglas, Bill Ramsey, Raghu Ramakrishnan
Symposium on Networked Systems Design and Implementation (NSDI) | February 2019
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Towards a learning optimizer for shared clouds
Chenggang Wu, Alekh Jindal, Saeed Amizadeh, Hiren Patel, Wangchao Le, Shi Qiao, Sriram Rao
Very Large Data Bases | October 2018
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PRETZEL: opening the black box of machine learning prediction serving systems
Yunseong Lee, Alberto Scolari, Byung-Gon Chun, Marco Domenico Santambrogio, Matteo Interlandi, Markus Weimer
Operating Systems Design and Implementation | October 2018
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Netco: Cache and I/O Management for Analytics over Disaggregated Stores
Virajith Jalaparti, Chris Douglas, Mainak Ghosh, Ashvin Agrawal, Avrilia Floratou, Srikanth Kandula, Ishai Menache, Joseph (Seffi) Naor, Sriram Rao
ACM Symposium on Cloud Computing (SOCC) | October 2018
Best Paper Award
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SOCK: rapid task provisioning with serverless-optimized containers
Edward Oakes, Leon Yang, Dennis Zhou, Kevin Houck, Tyler Harter, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
USENIX Annual Technical Conference | July 2018
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Survivability of Cloud Databases – Factors and Prediction
Jose Picado, Willis Lang, Edward C. Thayer
International Conference on Management of Data | May 2018
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Computation Reuse in Analytics Job Service at Microsoft
Alekh Jindal, Shi Qiao, Hiren Patel, Zhicheng Yin, Jieming Di, Malay Bag, Marc Friedman, Yifung Lin, Konstantinos Karanasos, Sriram Rao
2018 International Conference on Management of Data | May 2018
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Query and Resource Optimization: Bridging the Gap
Lalitha Viswanathan, Alekh Jindal, Konstantinos Karanasos
International Conference on Data Engineering (ICDE) | April 2018
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Selecting subexpressions to materialize at datacenter scale
Alekh Jindal, Konstantinos Karanasos, Sriram Rao, Hiren Patel
Very Large Data Bases (VLDB) | February 2018
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Batch-Expansion Training: An Efficient Optimization Framework
Michał Dereziński, Dhruv Mahajan, S. Sathiya Keerthi, S. V. N. Vishwanathan, Markus Weimer
International Conference on Artificial Intelligence and Statistics | February 2018
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Characterizing Resource Sensitivity of Database Workloads
Rathijit Sen, Karthik Ramachandra
High-Performance Computer Architecture | January 2018
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Medea: Scheduling of Long Running Applications in Shared Production Clusters
Panagiotis Garefalakis, Konstantinos Karanasos, Peter Pietzuch, Arun Suresh, Sriram Rao
European Conference on Computer Systems (EuroSys) | January 2018
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Towards High-Performance Prediction Serving Systems
Yunseong Lee, Alberto Scolari, Byung-Gon Chun, Matteo Interlandi, Markus Weimer
31st Conference on Neural Information Processing Systems | December 2017
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No data left behind: real-time insights from a complex data ecosystem
Manos Karpathiotakis, Avrilia Floratou, Fatma Ozcan, Anastasia Ailamaki
SOCC | September 2017
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A robust partitioning scheme for ad-hoc query workloads
Anil Shanbhag, Alekh Jindal, Samuel Madden, Jorge Quiane, Aaron J. Elmore
Symposium on Cloud Computing | September 2017
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Self-Regulating Streaming Systems: Challenges and Opportunities
Avrilia Floratou, Ashvin Agrawal
BIRTE | August 2017
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Dhalion: Self-Regulating Stream Processing in Heron
Avrilia Floratou, Ashvin Agrawal, Bill Graham, Sriram Rao, Karthik Ramasamy
Proceedings of the VLDB Endowment | August 2017
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Frequency governors for cloud database OLTP workloads
Rathijit Sen, Alan Halverson
International Symposium on Low Power Electronics and Design | July 2017
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Pipsqueak: Lean Lambdas with Large Libraries
Edward Oakes, Leon Yang, Kevin Houck, Tyler Harter, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
International Conference on Distributed Computing Systems Workshops | July 2017
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ROSA: R Optimizations with Static Analysis
Rathijit Sen, Jianqiao Zhu, Jignesh M. Patel, Somesh Jha
RIOT 2017 | July 2017
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Twitter Heron: Towards Extensible Streaming Engines
Maosong Fu, Ashvin Agrawal, Avrilia Floratou, Bill Graham, Andrew Jorgensen, Mark Li, Neng Lu, Karthik Ramasamy, Sriram Rao, Cong Wang
ICDE | May 2017
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Resource bricolage and resource selection for parallel database systems
Jiexing Li, Jeffrey F. Naughton, Rimma V. Nehme
Very Large Data Bases | January 2017
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AdaptDB: adaptive partitioning for distributed joins
Yi Lu, Anil Shanbhag, Alekh Jindal, Samuel Madden
Very Large Data Bases | January 2017
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Morpheus: Towards Automated SLOs for Enterprise Clusters
Sangeetha Abdu Jyothi, Carlo Curino, Ishai Menache, Shravan Matthur Narayanamurthy, Alexey Tumanov, Jonathan Yaniv, Ruslan Mavlyutov, Íñigo Goiri, Subru Krishnan, Janardhan (Jana) Kulkarni, Sriram Rao
2016 International Symposium on Operating Systems Design and Implementation (OSDI) | November 2016
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PerfOrator: Eloquent Performance Models for Resource Optimization
Dharmesh Kakadia, Kaushik Rajan, Carlo Curino, Subru Krishnan
ACM Symposium on Cloud Computing 2016 (SoCC’16) | October 2016
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A moeba : a shape changing storage system for big data
Anil Shanbhag, Alekh Jindal, Yi Lu, Samuel Madden
Very Large Data Bases | August 2016
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GraphFrames: an integrated API for mixing graph and relational queries
Ankur Dave, Alekh Jindal, Li Erran Li, Reynold Xin, Joseph Gonzalez, Matei Zaharia
GRADES | June 2016
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Efficient Queue Management for Cluster Scheduling
Jeff Rasley, Konstantinos Karanasos, Srikanth Kandula, Rodrigo Fonseca, Sriram Rao, Milan Vojnovic
European Conference on Computer Systems (EuroSys) | April 2016
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Mercury: Hybrid Centralized and Distributed Scheduling in Large Shared Clusters
Konstantinos Karanasos, Sriram Rao, Carlo Curino, Chris Douglas, Kishore Chaliparambil, Giovanni Matteo Fumarola, Solom Heddaya, Raghu Ramakrishnan, Sarvesh Sakalanaga
USENIX Annual Technical Conference (USENIX ATC’2015) | July 2015
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WANalytics: Geo-Distributed Analytics for a Data Intensive World
Ashish Vulimiri, Carlo Curino, Philip Brighten Godfrey, Thomas Jungblut, Konstantinos Karanasos, Jitendra Padhye, George Varghese
International Conference on Management of Data (SIGMOD) | May 2015
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Apache Tez: A Unifying Framework for Modeling and Building Data Processing Applications
Bikas Saha, Hitesh Shah, Siddharth Seth, Gopal Vijayaraghavan, Arun Murthy, Carlo Curino
SIGMOD ’15: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data | May 2015
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Global Analytics in the Face of Bandwidth and Regulatory Constraints
Ashish Vulimiri, Carlo Curino, P. Brighten Godfrey, Thomas Jungblut, Jitu Padhye, George Varghese
12th USENIX Symposium on Networked Systems Design and Implementation (NSDI ’15) | May 2015
ISBN: 978-1-931971-218
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Blind men and an elephant coalescing open-source, academic, and industrial perspectives on BigData
Chris Douglas, Carlo Curino
International Conference on Data Engineering | April 2015
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WANalytics: Analytics for a Geo-Distributed Data-Intensive World
Ashish Vulimiri, Carlo Curino, Brighten Godfrey, Konstantinos Karanasos, George Varghese
Conference on Innovative Data Systems Research (CIDR) | January 2015
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Multi-resource Packing for Cluster Schedulers
Robert Grandl, Ganesh Ananthanarayanan, Srikanth Kandula, Sriram Rao, Aditya Akella
ACM SIGCOMM | August 2014
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Indexing HDFS data in PDW: splitting the data from the index
Vinitha Reddy Gankidi, Nikhil Teletia, Jignesh M. Patel, Alan Halverson, David J. DeWitt
Very Large Data Bases | July 2014
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Partial results in database systems
Willis Lang, Rimma V. Nehme, Eric Robinson, Jeffrey F. Naughton
International Conference on Management of Data | June 2014
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Dynamically Optimizing Queries over Large Scale Data Platforms
Konstantinos Karanasos, Andrey Balmin, Marcel Kutsch, Fatma Ozcan, Vuk Ercegovac, Chunyang Xia, Jesse Jackson
International Conference on Management of Data (SIGMOD) | June 2014
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Elastic Distributed Bayesian Collaborative Filtering
Alex Beutel, Markus Weimer, Tom Minka, Yordan Zaykov, Vijay Narayanan
January 2014
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Delta: Scalable Data Dissemination under Capacity Constraints
Konstantinos Karanasos, Asterios Katsifodimos, Ioana Manolescu
Very Large Data Bases (PVLDB) | December 2013
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Split query processing in polybase
David J. DeWitt, Rimma Nehme, Srinath Shankar, Josep Aguilar-Saborit, Artin Avanes, Miro Flasza, Jim Gramling, Alan Halverson
2013 ACM SIGMOD International Conference on Management of Data | June 2013
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Fact Checking and Analyzing the Web
Francois Goasdoue, Konstantinos Karanasos, Yannis Katsis, Julien Leblay, Ioana Manolescu, Stamatis Zampetakis
International Conference on Management of Data (SIGMOD) | June 2013
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Fast peak-to-peak behavior with SSD buffer pool
Jaeyoung Do, Donghui Zhang, J. M. Patel, D. J. DeWitt
International Conference on Data Engineering | April 2013
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Robust Estimation of Resource Consumption for SQL Queries using Statistical Techniques
Jiexing Li, Arnd Christian König, Arnd Christian König, Vivek Narasayya, Surajit Chaudhuri
38th International Conference on Very Large Databases | August 2012
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Query optimization in Microsoft SQL Server PDW
Srinath Shankar, Rimma Nehme, Josep Aguilar-Saborit, Andrew Chung, Mostafa Elhemali, Eric Robinson, Mahadevan Sankara Subramanian, David DeWitt, César Galindo-Legaria, Alan Halverson
International Conference on Management of Data | May 2012
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WWW 2012 Tutorial: New Templates for Scalable Data Analysis
Amr Ahmed, Alexander J. Smola, Markus Weimer
25th International World Wide Web Conference | April 2012
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GSLPI: A Cost-Based Query Progress Indicator
Jiexing Li, Rimma V. Nehme, Jeffrey Naughton
International Conference on Data Engineering | March 2012
DOI PDF Publication Publication Publication Publication Publication
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Toward Progress Indicators on Steroids for Big Data Systems.
Jiexing Li, Rimma V. Nehme, Jeffrey F. Naughton
Conference on Innovative Data Systems Research | January 2012
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Turbocharging DBMS buffer pool using SSDs
Jaeyoung Do, Donghui Zhang, Jignesh M. Patel, David J. DeWitt, Jeffrey F. Naughton, Alan Halverson
International Conference on Management of Data | June 2011
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Automated partitioning design in parallel database systems
Rimma Nehme, Nicolas Bruno
International Conference on Management of Data | June 2011
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The Mimicking Octopus: Towards a one-size-fits-all Database Architecture
Alekh Jindal
36th International Conference on VLDB | September 2010
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Energy management for MapReduce clusters
Willis Lang, Jignesh M. Patel
Very Large Data Bases | August 2010
DOI PDF PDF Publication Publication Publication Publication Publication
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On energy management, load balancing and replication
Willis Lang, Jignesh M. Patel, Jeffrey F. Naughton
International Conference on Management of Data | June 2010
DOI PDF Publication Publication Publication Publication Publication
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Wimpy node clusters: what about non-wimpy workloads?
Willis Lang, Jignesh M. Patel, Srinath Shankar
Data Management on New Hardware | June 2010
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Towards Eco-friendly Database Management Systems
Willis Lang, Jignesh M. Patel
Conference on Innovative Data Systems Research | December 2009
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A Comparative Exploration of ML Techniques for Tuning Query Degree of Parallelism.
Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi
May 2020
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Constant Time Recovery in Azure SQL Database
Panagiotis Antonopoulos, Peter Byrne, Wayne Chen, Cristian Diaconu, Raghavendra Thallam Kodandaramaih, Hanuma Kodavalla, Prashanth Purnananda, Adrian-Leonard Radu, Chaitanya Sreenivas Ravella, Girish Mittur Venkataramanappa
June 2019
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Query and Resource Optimizations: A Case for Breaking the Wall in Big Data Systems
Alekh Jindal, Lalitha Viswanathan, Konstantinos Karanasos
MSR-TR-2019-44 | June 2019
作者：Microsoft
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INGESTBASE: A Declarative Data Ingestion System.
Alekh Jindal, Jorge-Arnulfo Quiané-Ruiz, Samuel Madden
MSR-TR-2017-62 | January 2017
作者：Microsoft
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Do the Hard Stuff First: Scheduling Dependent Computations in Data Analytics Clusters
Robert Grandl, Srikanth Kandula, Sriram Rao, Aditya Akella, Janardhan (Jana) Kulkarni
MSR-TR-2016-19 | February 2016
作者：Microsoft
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Distributed and Scalable PCA in the Cloud
Arun Kumar, Vijay Narayanan, Nikos Karampatziakis, Paul Mineiro, Markus Weimer
MSR-TR-2014-165 | January 2014
作者：Microsoft
Apache Reef Research Paper
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Reservation-based Scheduling: If You’re Late Don’t Blame Us!
Carlo Curino, Djellel E Difallah, Chris Douglas, Subru Krishnan, Rahgu Ramakrishnan, Sriram Rao
MSR-TR-2013-108 | October 2013
Published in SoCC 2014
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Columnar Storage Formats
Encyclopedia of Big Data Technologies | 作者：Springer | 2018
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Challenges and Opportunities in Transportation Data
Kristin Tufte, Kushal Datta, Alekh Jindal, David Maier, Robert L. Bertini
June 2018
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Robust Data Partitioning.
Alekh Jindal, Anil Shanbhag, Yi Lu
February 2018
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Towards Resource-Elastic Machine Learning
Dhruv Mahajan, Sundararajan Sellamanickam, Markus Weimer, Keerthi Selvaraj
January 2013
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