Ryan Marcus

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 60

Top Topics

Index Structure

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)
Chenyuan Wu, Mohammad Javad Amiri, Haoyun Qin, Bhavana Mehta, Ryan Marcus, Boon Thau Loo
Towards Full Stack Adaptivity in Permissioned Blockchains. Proc. VLDB Endow. 17 (5) (2024)
Zixuan Yi, Yao Tian, Zachary G. Ives, Ryan Marcus
Low Rank Approximation for Learned Query Optimization. aiDM@SIGMOD (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)
Gaurav Saxena, Mohammad Rahman, Naresh Chainani, Chunbin Lin, George Caragea, Fahim Chowdhury, Ryan Marcus, Tim Kraska, Ippokratis Pandis, Balakrishnan (Murali) Narayanaswamy
Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift. SIGMOD Conference Companion (2023)
Christoph Anneser, Nesime Tatbul, David E. Cohen, Zhenggang Xu, Prithviraj Pandian, Nikolay Laptev, Ryan Marcus
AutoSteer: Learned Query Optimization for Any SQL Database. Proc. VLDB Endow. 16 (12) (2023)
Ryan Marcus
Learned Query Superoptimization. CoRR (2023)
Bhavana Mehta, Neelesh C. A, Prashanth S. Iyer, Mohammad Javad Amiri, Boon Thau Loo, Ryan Marcus
Towards Adaptive Fault-Tolerant Sharded Databases. VLDB Workshops (2023)
Ryan Marcus
Learned Query Superoptimization. VLDB Workshops (2023)
Lyric Doshi, Vincent Zhuang, Gaurav Jain, Ryan Marcus, Haoyu Huang, Deniz Altinbüken, Eugene Brevdo, Campbell Fraser
Kepler: Robust Learning for Parametric Query Optimization. Proc. ACM Manag. Data 1 (1) (2023)
Chenyuan Wu, Bhavana Mehta, Mohammad Javad Amiri, Ryan Marcus, Boon Thau Loo
AdaChain: A Learned Adaptive Blockchain. Proc. VLDB Endow. 16 (8) (2023)
Peizhi Wu, Ryan Marcus, Zachary G. Ives
Adding Domain Knowledge to Query-Driven Learned Databases. CoRR (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)
Christoph Anneser, Mario Petruccelli, Nesime Tatbul, David E. Cohen, Zhenggang Xu, Prithviraj Pandian, Nikolay Laptev, Ryan Marcus, Alfons Kemper
QO-Insight: Inspecting Steered Query Optimizers. Proc. VLDB Endow. 16 (12) (2023)
Lyric Doshi, Vincent Zhuang, Gaurav Jain, Ryan Marcus, Haoyu Huang, Deniz Altinbüken, Eugene Brevdo, Campbell Fraser
Kepler: Robust Learning for Faster Parametric Query Optimization. CoRR (2023)
Ryan Marcus, Parimarjan Negi, Hongzi Mao, Nesime Tatbul, Mohammad Alizadeh, Tim Kraska
Bao: Making Learned Query Optimization Practical. SIGMOD Rec. 51 (1) (2022)
Rajesh Bordawekar, Yael Amsterdamer, Donatella Firmani, Ryan Marcus, Oded Shmueli
aiDM'22: Fifth International Workshop on Exploiting Artificial Intelligence Techniques for Data Management. SIGMOD Conference (2022)
Andreas Kipf, Dominik Horn, Pascal Pfeil, Ryan Marcus, Tim Kraska
LSI: a learned secondary index structure. aiDM@SIGMOD (2022)
Andreas Kipf, Dominik Horn, Pascal Pfeil, Ryan Marcus, Tim Kraska
LSI: A Learned Secondary Index Structure. CoRR (2022)
Chenyuan Wu, Bhavana Mehta, Mohammad Javad Amiri, Ryan Marcus, Boon Thau Loo
AdaChain: A Learned Adaptive Blockchain. CoRR (2022)
Mihail Stoian, Andreas Kipf, Ryan Marcus, Tim Kraska
PLEX: Towards Practical Learned Indexing. CoRR (2021)
Lujing Cen, Andreas Kipf, Ryan Marcus, Tim Kraska
LEA: A Learned Encoding Advisor for Column Stores. aiDM@SIGMOD (2021)
Lujing Cen, Andreas Kipf, Ryan Marcus, Tim Kraska
LEA: A Learned Encoding Advisor for Column Stores. CoRR (2021)
Laurent Bindschaedler, Andreas Kipf, Tim Kraska, Ryan Marcus, Umar Farooq Minhas
Towards a Benchmark for Learned Systems. ICDE Workshops (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)
Nadiia Chepurko, Ryan Marcus, Emanuel Zgraggen, Raul Castro Fernandez, Tim Kraska, David R. Karger
ARDA: Automatic Relational Data Augmentation for Machine Learning. Proc. VLDB Endow. 13 (9) (2020)
Parimarjan Negi, Ryan Marcus, Hongzi Mao, Nesime Tatbul, Tim Kraska, Mohammad Alizadeh
Cost-Guided Cardinality Estimation: Focus Where it Matters. ICDE Workshops (2020)
Fangke Ye, Shengtian Zhou, Anand Venkat, Ryan Marcus, Nesime Tatbul, Jesmin Jahan Tithi, Paul Petersen, Timothy G. Mattson, Tim Kraska, Pradeep Dubey, Vivek Sarkar, Justin Gottschlich
MISIM: An End-to-End Neural Code Similarity System. CoRR (2020)
Fangke Ye, Shengtian Zhou, Anand Venkat, Ryan Marcus, Paul Petersen, Jesmin Jahan Tithi, Tim Mattson, Tim Kraska, Pradeep Dubey, Vivek Sarkar, Justin Gottschlich
Context-Aware Parse Trees. CoRR (2020)
Ryan Marcus, Emily Zhang, Tim Kraska
CDFShop: Exploring and Optimizing Learned Index Structures. SIGMOD Conference (2020)
Andreas Kipf, Ryan Marcus, Alexander van Renen, Mihail Stoian, Alfons Kemper, Tim Kraska, Thomas Neumann
RadixSpline: a single-pass learned index. aiDM@SIGMOD (2020)
Chi Zhang, Ryan Marcus, Anat Kleiman, Olga Papaemmanouil
Buffer Pool Aware Query Scheduling via Deep Reinforcement Learning. CoRR (2020)
Solomon Garber, Ryan Marcus, Antonella DiLillo, James A. Storer
Low Rate Compression of Video with Dynamic Backgrounds. DCC (2020)
Akhilesh Gupta, Nesime Tatbul, Ryan Marcus, Shengtian Zhou, Insup Lee, Justin Gottschlich
Class-Weighted Evaluation Metrics for Imbalanced Data Classification. CoRR (2020)
Ryan Marcus, Andreas Kipf, Alexander van Renen, Mihail Stoian, Sanchit Misra, Alfons Kemper, Thomas Neumann, Tim Kraska
Benchmarking Learned Indexes. CoRR (2020)
Lujing Cen, Ryan Marcus, Hongzi Mao, Justin Gottschlich, Mohammad Alizadeh, Tim Kraska
Learned Garbage Collection. CoRR (2020)
Andreas Kipf, Ryan Marcus, Alexander van Renen, Mihail Stoian, Alfons Kemper, Tim Kraska, Thomas Neumann
RadixSpline: A Single-Pass Learned Index. CoRR (2020)
Lujing Cen, Ryan Marcus, Hongzi Mao, Justin Gottschlich, Mohammad Alizadeh, Tim Kraska
Learned garbage collection. MAPL@PLDI (2020)
Nadiia Chepurko, Ryan Marcus, Emanuel Zgraggen, Raul Castro Fernandez, Tim Kraska, David R. Karger
ARDA: Automatic Relational Data Augmentation for Machine Learning. CoRR (2020)
Ryan Marcus, Parimarjan Negi, Hongzi Mao, Nesime Tatbul, Mohammad Alizadeh, Tim Kraska
Bao: Learning to Steer Query Optimizers. CoRR (2020)
Ryan Marcus, Andreas Kipf, Alexander van Renen, Mihail Stoian, Sanchit Misra, Alfons Kemper, Thomas Neumann, Tim Kraska
Benchmarking Learned Indexes. Proc. VLDB Endow. 14 (1) (2020)
Ryan Marcus, Olga Papaemmanouil
Flexible Operator Embeddings via Deep Learning. CoRR (2019)
Ryan Marcus, Chi Zhang, Shuai Yu, Geoffrey Kao, Olga Papaemmanouil
NashDB: Fragmentation, Replication, and Provisioning using Economic Methods. Proc. VLDB Endow. 12 (12) (2019)
Bailu Ding, Sudipto Das, Ryan Marcus, Wentao Wu, Surajit Chaudhuri, Vivek R. Narasayya
AI Meets AI: Leveraging Query Executions to Improve Index Recommendations. SIGMOD Conference (2019)
Ryan Marcus, Olga Papaemmanouil
Plan-Structured Deep Neural Network Models for Query Performance Prediction. CoRR (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)
Ryan Marcus, Olga Papaemmanouil
Towards a Hands-Free Query Optimizer through Deep Learning. CIDR (2019)
Andreas Kipf, Ryan Marcus, Alexander van Renen, Mihail Stoian, Alfons Kemper, Tim Kraska, Thomas Neumann
SOSD: A Benchmark for Learned Indexes. CoRR (2019)
Ryan Marcus, Olga Papaemmanouil
Deep Reinforcement Learning for Join Order Enumeration. CoRR (2018)
Ryan Marcus, Olga Papaemmanouil, Sofiya Semenova, Solomon Garber
NashDB: An End-to-End Economic Method for Elastic Database Fragmentation, Replication, and Provisioning. SIGMOD Conference (2018)
Ryan Marcus, Olga Papaemmanouil
Deep Reinforcement Learning for Join Order Enumeration. aiDM@SIGMOD (2018)
Ryan Marcus, Olga Papaemmanouil
Towards a Hands-Free Query Optimizer through Deep Learning. CoRR (2018)
Ryan Marcus, Olga Papaemmanouil
Releasing Cloud Databases for the Chains of Performance Prediction Models. CIDR (2017)
Ryan Marcus, Sofiya Semenova, Olga Papaemmanouil
A Learning-Based Service for Cost and Performance Management of Cloud Databases. ICDE (2017)
Ryan Marcus, Olga Papaemmanouil
WiSeDB: A Learning-based Workload Management Advisor for Cloud Databases. CoRR (2016)
Ryan Marcus, Olga Papaemmanouil
WiSeDB: A Learning-based Workload Management Advisor for Cloud Databases. Proc. VLDB Endow. 9 (10) (2016)
Ryan Marcus, Olga Papaemmanouil
Workload management for cloud databases via machine learning. ICDE Workshops (2016)