- Redmond WA, US Feng LI - Bellevue WA, US Vivek NARASAYYA - Redmond WA, US Arnd Christian KÖNIG - Kirkland WA, US
International Classification:
G06Q 10/06 G06F 11/34 G06F 16/21
Abstract:
Architecture that enables a Database-as-a-Service (DaaS) to auto-scale container sizes on behalf of tenants. An abstraction is provided that enables tenants to reason about monetary budget and query latency, rather than resource provisioning. An auto-scaling module automatically determines a container size for a subsequent billing interval based on telemetry that comprises latencies (e.g., waits), resource utilizations, and available budget, for example. A set of robust signals are derived from database engine telemetry and combined to significantly improve accuracy of resource demand estimation for database workloads. In a more specific implementation, resource demands can be estimated for arbitrary SQL (structured query language) workloads in a relational database management system (RDBMS).
- Redmond WA, US Feng Li - Bellevue WA, US Manoj A. Syamala - Issaquah WA, US Vivek R. Narasayya - Redmond WA, US
International Classification:
G06F 15/173 G06F 12/02 G06F 3/06
Abstract:
A server system may include a cluster of multiple computers that are networked for high-speed data communications. Each of the computers has a remote direct memory access (RDMA) network interface to allow high-speed memory sharing between computers. A relational database engine of each computer is configured to utilize a hierarchy of memory for temporary storage of working data, including in order of decreasing access speed (a) local main memory, (b) remote memory accessed via RDMS, and (c) mass storage. The database engine uses the local main memory for working data, and additionally uses the RDMA accessible memory for working data when the local main memory becomes depleted. The server system may include a memory broker to which individual computers report their available or unused memory, and which leases shared memory to requesting computers.
Automatic Demand-Driven Resource Scaling For Relational Database-As-A-Service
- Redmond WA, US Feng Li - Bellevue WA, US Vivek Narasayya - Redmond WA, US Arnd Christian König - Kirkland WA, US
Assignee:
MICROSOFT CORPORATION - Redmond WA
International Classification:
G06Q 10/06 G06Q 20/14
Abstract:
Architecture that enables a Database-as-a-Service (DaaS) to auto-scale container sizes on behalf of tenants. An abstraction is provided that enables tenants to reason about monetary budget and query latency, rather than resource provisioning. An auto-scaling module automatically determines a container size for a subsequent billing interval based on telemetry that comprises latencies (e.g., waits), resource utilizations, and available budget, for example. A set of robust signals are derived from database engine telemetry and combined to significantly improve accuracy of resource demand estimation for database workloads. In a more specific implementation, resource demands can be estimated for arbitrary SQL (structured query language) workloads in a relational database management system (RDBMS).
Medical School Tufts University School of Medicine Graduated: 2002
Description:
Dr. Li graduated from the Tufts University School of Medicine in 2002. He works in Tyler, TX and specializes in Gastroenterology. Dr. Li is affiliated with Mother Francis Hospital.
Baidu - Sofeware Development Engineer (2011) Alstom China Technology Center - Sofeware Development Engineer (2009-2011) EMC R&D Center - Sofeware Development Engineer Intern (2008-2008)
Education:
Fudan University - Master, Computer Science, National University of Singapore - Research Assistant, Sichuan University - Computer Science
Tagline:
To be or not to be
Feng Li
Work:
Nanyang Technological University - PhD Student
Education:
Nanyang Technological University - Computer Engineering, Shandong University - Computer Science and Technology, Shandong Normal University - Computer Science and Technology