20 citations · 35 across the 3 of their papers we have counts for
3 papers
cs.DB2022★ 20 cited
Deploying a Steered Query Optimizer in Production at Microsoft
Wangda Zhang, Matteo Interlandi, Paul Mineiro +6
Modern analytical workloads are highly heterogeneous and massively complex, making generic query optimizers untenable for many customers and scenarios. As a result, it is important…
cs.DB2021★ 11 cited
Optimal Resource Allocation for Serverless Queries
Anish Pimpley, Shuo Li, Anubha Srivastava +7
Optimizing resource allocation for analytical workloads is vital for reducing costs of cloud-data services. At the same time, it is incredibly hard for users to allocate resources…
cs.DB2020★ 4 cited
Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings
Tarique Siddiqui, Alekh Jindal, Shi Qiao +2
Query processing over big data is ubiquitous in modern clouds, where the system takes care of picking both the physical query execution plans and the resources needed to run those…