Parimarjan Negi

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 19

Top Topics

Query Execution Plan

Cardinality Estimation

Query Optimizers

Top Venues

Proc. VLDB Endow.

SIGMOD Conference

Publications

Ziniu Wu, Ryan Marcus, Zhengchun Liu, Parimarjan Negi, Vikram Nathan, Pascal Pfeil, Gaurav Saxena, Mohammad Rahman, Balakrishnan Narayanaswamy, Tim Kraska
Stage: Query Execution Time Prediction in Amazon Redshift. SIGMOD Conference Companion (2024)
Ziniu Wu, Ryan Marcus, Zhengchun Liu, Parimarjan Negi, Vikram Nathan, Pascal Pfeil, Gaurav Saxena, Mohammad Rahman, Balakrishnan Narayanaswamy, Tim Kraska
Stage: Query Execution Time Prediction in Amazon Redshift. CoRR (2024)
Ziniu Wu, Parimarjan Negi, Mohammad Alizadeh, Tim Kraska, Samuel Madden
FactorJoin: A New Cardinality Estimation Framework for Join Queries. Proc. ACM Manag. Data 1 (1) (2023)
Parimarjan Negi, Laurent Bindschaedler, Mohammad Alizadeh, Tim Kraska, Jyoti Leeka, Anja Gruenheid, Matteo Interlandi
Unshackling Database Benchmarking from Synthetic Workloads. ICDE (2023)
Parimarjan Negi, Ziniu Wu, Andreas Kipf, Nesime Tatbul, Ryan Marcus, Sam Madden, Tim Kraska, Mohammad Alizadeh
Robust Query Driven Cardinality Estimation under Changing Workloads. Proc. VLDB Endow. 16 (6) (2023)
Ziniu Wu, Parimarjan Negi, Mohammad Alizadeh, Tim Kraska, Samuel Madden
FactorJoin: A New Cardinality Estimation Framework for Join Queries. CoRR (2022)
Ryan Marcus, Parimarjan Negi, Hongzi Mao, Nesime Tatbul, Mohammad Alizadeh, Tim Kraska
Bao: Making Learned Query Optimization Practical. SIGMOD Rec. 51 (1) (2022)
Parimarjan Negi, Ryan C. Marcus, Andreas Kipf, Hongzi Mao, Nesime Tatbul, Tim Kraska, Mohammad Alizadeh
Flow-Loss: Learning Cardinality Estimates That Matter. Proc. VLDB Endow. 14 (11) (2021)
Parimarjan Negi, Matteo Interlandi, Ryan Marcus, Mohammad Alizadeh, Tim Kraska, Marc T. Friedman, Alekh Jindal
Steering Query Optimizers: A Practical Take on Big Data Workloads. SIGMOD Conference (2021)
Ryan Marcus, Parimarjan Negi, Hongzi Mao, Nesime Tatbul, Mohammad Alizadeh, Tim Kraska
Bao: Making Learned Query Optimization Practical. SIGMOD Conference (2021)
Parimarjan Negi, Ryan Marcus, Andreas Kipf, Hongzi Mao, Nesime Tatbul, Tim Kraska, Mohammad Alizadeh
Flow-Loss: Learning Cardinality Estimates That Matter. CoRR (2021)
Parimarjan Negi, Ryan Marcus, Hongzi Mao, Nesime Tatbul, Tim Kraska, Mohammad Alizadeh
Cost-Guided Cardinality Estimation: Focus Where it Matters. ICDE Workshops (2020)
Vibhaalakshmi Sivaraman, Shaileshh Bojja Venkatakrishnan, Kathleen Ruan, Parimarjan Negi, Lei Yang, Radhika Mittal, Giulia C. Fanti, Mohammad Alizadeh
High Throughput Cryptocurrency Routing in Payment Channel Networks. NSDI (2020)
Ryan Marcus, Parimarjan Negi, Hongzi Mao, Nesime Tatbul, Mohammad Alizadeh, Tim Kraska
Bao: Learning to Steer Query Optimizers. CoRR (2020)
Ryan C. Marcus, Parimarjan Negi, Hongzi Mao, Chi Zhang, Mohammad Alizadeh, Tim Kraska, Olga Papaemmanouil, Nesime Tatbul
Neo: A Learned Query Optimizer. Proc. VLDB Endow. 12 (11) (2019)
Ryan Marcus, Parimarjan Negi, Hongzi Mao, Chi Zhang, Mohammad Alizadeh, Tim Kraska, Olga Papaemmanouil, Nesime Tatbul
Neo: A Learned Query Optimizer. CoRR (2019)
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
Park: An Open Platform for Learning-Augmented Computer Systems. NeurIPS (2019)
Shoumik Palkar, James J. Thomas, Deepak Narayanan, Pratiksha Thaker, Rahul Palamuttam, Parimarjan Negi, Anil Shanbhag, Malte Schwarzkopf, Holger Pirk, Saman P. Amarasinghe, Samuel Madden, Matei Zaharia
Evaluating End-to-End Optimization for Data Analytics Applications in Weld. Proc. VLDB Endow. 11 (9) (2018)
Parimarjan Negi, Prafull Sharma, Vivek Jain, Bahman Bahmani
K-means++ vs. Behavioral Biometrics: One Loop to Rule Them All. NDSS (2018)