Parimarjan Negi

20 papers A* 3Misc 1Journal 11Unranked 4
YearRankTypeTitle / Venue / Authors
2024 — —
Machine Learning for Out of Distribution Database Workloads
Parimarjan Negi
2024 — conf
Stage: Query Execution Time Prediction in Amazon Redshift.
SIGMOD Conference Companion
Ziniu Wu, Ryan Marcus, Zhengchun Liu, Parimarjan Negi, Vikram Nathan, Pascal Pfeil, Gaurav Saxena, Mohammad Rahman, Balakrishnan Narayanaswamy, Tim Kraska
2024 J jnl
Stage: Query Execution Time Prediction in Amazon Redshift.
CoRR
Ziniu Wu, Ryan Marcus, Zhengchun Liu, Parimarjan Negi, Vikram Nathan, Pascal Pfeil, Gaurav Saxena, Mohammad Rahman, Balakrishnan Narayanaswamy, Tim Kraska
2023 J jnl
FactorJoin: A New Cardinality Estimation Framework for Join Queries.
Proc. ACM Manag. Data
Ziniu Wu, Parimarjan Negi, Mohammad Alizadeh, Tim Kraska, Samuel Madden
2023 J jnl
Robust Query Driven Cardinality Estimation under Changing Workloads.
Proc. VLDB Endow.
Parimarjan Negi, Ziniu Wu, Andreas Kipf, Nesime Tatbul, Ryan Marcus, Sam Madden, Tim Kraska, Mohammad Alizadeh
2023 A* conf
Unshackling Database Benchmarking from Synthetic Workloads.
ICDE
Parimarjan Negi, Laurent Bindschaedler, Mohammad Alizadeh, Tim Kraska, Jyoti Leeka, Anja Gruenheid, Matteo Interlandi
2022 J jnl
Bao: Making Learned Query Optimization Practical.
SIGMOD Rec.
Ryan Marcus, Parimarjan Negi, Hongzi Mao, Nesime Tatbul, Mohammad Alizadeh, Tim Kraska
2022 J jnl
FactorJoin: A New Cardinality Estimation Framework for Join Queries.
CoRR
Ziniu Wu, Parimarjan Negi, Mohammad Alizadeh, Tim Kraska, Samuel Madden
2021 — conf
Bao: Making Learned Query Optimization Practical.
SIGMOD Conference
Ryan Marcus, Parimarjan Negi, Hongzi Mao, Nesime Tatbul, Mohammad Alizadeh, Tim Kraska
2021 J jnl
Flow-Loss: Learning Cardinality Estimates That Matter.
CoRR
Parimarjan Negi, Ryan Marcus, Andreas Kipf, Hongzi Mao, Nesime Tatbul, Tim Kraska, Mohammad Alizadeh
2021 J jnl
Flow-Loss: Learning Cardinality Estimates That Matter.
Proc. VLDB Endow.
Parimarjan Negi, Ryan Marcus, Andreas Kipf, Hongzi Mao, Nesime Tatbul, Tim Kraska, Mohammad Alizadeh
2021 — conf
Steering Query Optimizers: A Practical Take on Big Data Workloads.
SIGMOD Conference
Parimarjan Negi, Matteo Interlandi, Ryan Marcus, Mohammad Alizadeh, Tim Kraska, Marc T. Friedman, Alekh Jindal
2020 J jnl
Bao: Learning to Steer Query Optimizers.
CoRR
Ryan Marcus, Parimarjan Negi, Hongzi Mao, Nesime Tatbul, Mohammad Alizadeh, Tim Kraska
2020 — conf
Cost-Guided Cardinality Estimation: Focus Where it Matters.
ICDE Workshops
Parimarjan Negi, Ryan Marcus, Hongzi Mao, Nesime Tatbul, Tim Kraska, Mohammad Alizadeh
2020 Misc conf
High Throughput Cryptocurrency Routing in Payment Channel Networks.
NSDI
Vibhaalakshmi Sivaraman, Shaileshh Bojja Venkatakrishnan, Kathleen Ruan, Parimarjan Negi, Lei Yang, Radhika Mittal, Giulia Fanti, Mohammad Alizadeh
2019 J jnl
Neo: A Learned Query Optimizer.
CoRR
Ryan Marcus, Parimarjan Negi, Hongzi Mao, Chi Zhang, Mohammad Alizadeh, Tim Kraska, Olga Papaemmanouil, Nesime Tatbul
2019 J jnl
Neo: A Learned Query Optimizer.
Proc. VLDB Endow.
Ryan Marcus, Parimarjan Negi, Hongzi Mao, Chi Zhang, Mohammad Alizadeh, Tim Kraska, Olga Papaemmanouil, Nesime Tatbul
2019 A* conf
Park: An Open Platform for Learning-Augmented Computer Systems.
NeurIPS
Hongzi Mao, Parimarjan Negi, Akshay Narayan, Hanrui Wang, Jiacheng Yang, Haonan Wang, Ryan Marcus, Ravichandra Addanki, Mehrdad Khani Shirkoohi, Songtao He, Vikram Nathan, Frank Cangialosi, Shaileshh Bojja Venkatakrishnan, Wei-Hung Weng, Song Han, Tim Kraska, Mohammad Alizadeh
2018 J jnl
Evaluating End-to-End Optimization for Data Analytics Applications in Weld.
Proc. VLDB Endow.
Shoumik Palkar, James Thomas, Deepak Narayanan, Pratiksha Thaker, Rahul Palamuttam, Parimarjan Negi, Anil Shanbhag, Malte Schwarzkopf, Holger Pirk, Saman P. Amarasinghe, Samuel Madden, Matei Zaharia
2018 A* conf
K-means++ vs. Behavioral Biometrics: One Loop to Rule Them All.
NDSS
Parimarjan Negi, Prafull Sharma, Vivek Jain, Bahman Bahmani