Microsoft at VLDB 2021

Achieving High Throughput and Elasticity in a Larger-than-Memory Store

Chinmay Kulkarni, Badrish Chandramouli, Ryan Stutsman

COMPARE: Accelerating Groupwise Comparison in Relational Databases for Data Analytics (Extended Version)

Tarique Siddiqui, Surajit Chaudhuri, Vivek Narasayya

Procedural Extensions of SQL: Understanding their usage in the wild

Surabhi Gupta, Karthik Ramachandra

Maximizing Social Welfare in a Competitive Diffusion Model

Prithu Banerjee, Wei Chen, Laks V.S. Lakshmanan

Nearest Neighbor Classifiers over Incomplete Information: From Certain Answers to Certain Predictions

Bojan Karlas, Peng Li, Renzhi Wu, Nezihe Merve Gurel, Xu Chu, Wentao Wu, Ce Zhang

Optimization of threshold functions over streams

Walter Cai, Phil Bernstein, Wentao Wu, Badrish Chandramouli

Phoebe: A Learning-based Checkpoint Optimizer

Yiwen Zhu, Matteo Interlandi, Abhishek Roy, Krishnadhan Das, Hiren Patel, Malay Bag, Hitesh Sharma, Alekh Jindal

Auto-Pipeline: Synthesizing Complex Data Pipelines By-Target Using Reinforcement Learning and Search

Junwen Yang, Yeye He, Surajit Chaudhuri

VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition

Yang Li, Yu Shen, Wentao Zhang, Jiawei Jiang, Yaliang Li, Bolin Ding, Jingren Zhou, Zhi Yang, Wentao Wu, Ce Zhang, Bin Cui

Hyperspace: The Indexing Subsystem of Azure Synapse

Rahul Potharaju, Terry Kim, Eunjin Song, Wentao Wu, Lev Novik, Apoorve Dave, Andrew Fogarty, Pouria Pirzadeh, Vidip Acharya, Gurleen Dhody, Jiying Li, Sinduja Ramanujam, Nicolas Bruno, Cesar Galindo-Legaria, Vivek Narasayya, Surajit Chaudhuri, Anil K. Nori, Tomas Talius, Raghu Ramakrishnan

Analyzing and Mitigating Data Stalls in DNN Training

Jayashree Mohan, Amar Phanishayee, Ashish Raniwala, Vijay Chidambaram

Discovering Related Data At Scale

Sagar Bharadwaj, Praveen Gupta, Ranjita Bhagwan, Saikat Guha

Tensors: An abstraction for general data processing

Dimitrios Koutsoukos, Supun Nakandala, Konstantinos Karanasos, Karla Saur, Gustavo Alonso, Matteo Interlandi

Seagull: An Infrastructure for Load Prediction and Optimized Resource Allocation

Olga Poppe, Tayo Amuneke, Dalitso Banda, Aritra De, Ari Green, Manon Knoertzer, Ehi Nosakhare, Karthik Rajendran, Deepak Shankargouda, Meina Wang, Alan Au, Carlo Curino, Qun Guo, Alekh Jindal, Ajay Kalhan, Morgan Oslake, Sonia Parchani, Vijay Ramani, Raj Sellappan, Saikat Sen, Sheetal Shrotri, Soundararajan Srinivasan, Ping Xia, Shize Xu, Alicia Yang, Yiwen Zhu

Crystal: A Unified Cache Storage System for Analytical Databases

Dominik Durner, Badrish Chandramouli, Yinan Li

The Cosmos Big Data Platform at Microsoft: Over a Decade of Progress and a Decade to Look Forward

Conor Power, Hiren Patel, Alekh Jindal, Jyoti Leeka, Bob Jenkins, Michael Rys, Ed Triou, Dexin Zhu, Lucky Katahanas, Chakrapani Bhat Talapady, Joshua Rowe, Fan Zhang, Rich Draves, Marc Friedman, Ivan Santa Maria Filho, Amrish Kumar

SparkCruise: Workload Optimization in Managed Spark Clusters at Microsoft

Abhishek Roy, Alekh Jindal, Priyanka Gomatam, Xiating Ouyang, Ashit Gosalia, Nishkam Ravi, Swinky Mann, Prakhar Jain

Estimating Spread of Contact-Based Contagions in a Population Through Sub-Sampling

Sepanta Zeighami, Cyrus Shahabi, John Krumm