Aug 2012 to 2000 Member of Technical StaffAPPLIED MICRO Sunnyvale, CA May 2011 to Aug 2011 Validation Engineer Intern
Education:
North Carolina State University Raleigh, NC May 2012 MASTERS in COMPUTER SCIENCEThiagarajar College of Engineering (Anna University) Cary, NC May 2010 BACHELORS in ELECTRONICS & COMMUNICATION
- Bozeman MT, US Igor Demura - San Mateo CA, US Varun Ganesh - San Bruno CA, US Prasanna Rajaperumal - San Mateo CA, US Libo Wang - Foster City CA, US Jiaqi Yan - Menlo Park CA, US
International Classification:
G06F 16/2453
Abstract:
Embodiments of the present disclosure may provide a dynamic query execution model. This query execution model may provide acceleration by scaling out parallel parts of a query (also referred to as a fragment) to additional computing resources, for example computing resources leased from a pool of computing resources. Execution of the parts of the query may be coordinated by a parent query coordinator, where the query originated, and a fragment query coordinator.
- Bozeman MT, US Jiaxing Liang - Bellevue WA, US Scott Ziegler - San Mateo CA, US Haowei Yu - Newark CA, US Benoit Dageville - San Mateo CA, US Varun Ganesh - San Bruno CA, US
International Classification:
G06F 16/23 G06F 16/22 G06F 16/25
Abstract:
Systems, methods, and devices for batch ingestion of data into a table of a database. A method includes determining a notification indicating a presence of a user file received from a client account to be ingested into a database. The method includes identifying data in the user file and identifying a target table of the database to receive the data in the user file. The method includes generating an ingest task indicating the data and the target table. The method includes assigning the ingest task to an execution node of an execution platform, wherein the execution platform comprises a plurality of execution nodes operating independent of a plurality of shared storage devices collectively storing database data. The method includes registering metadata concerning the target table in a metadata store after the data has been fully committed to the target table by the execution node.
- Bozeman MT, US Igor Demura - San Mateo CA, US Varun Ganesh - San Bruno CA, US Prasanna Rajaperumal - Bangalore, IN Libo Wang - Foster City CA, US Jiaqi Yan - Menlo Park CA, US
International Classification:
G06F 9/50 G06F 9/54 H04L 67/1001
Abstract:
Embodiments of the present disclosure may provide dynamic and fair assignment techniques for allocating resources on a demand basis. Assignment control may be separated into at least two components: a local component and a global component. Each component may have an active dialog with each other; the dialog may include two aspects: 1) a demand for computing resources, and 2) a total allowed number of computing resources. The global component may allocate resources from a pool of resources to different local components, and the local components in turn may assign their allocated resources to local competing requests. The allocation may also be throttled or limited at various levels.
- Bozeman MT, US Igor Demura - San Mateo CA, US Varun Ganesh - San Bruno CA, US Prasanna Rajaperumal - Bangalore, IN Libo Wang - Foster City CA, US Jiaqi Yan - Menlo Park CA, US
Embodiments of the present disclosure may provide a dynamic query execution model with fault tolerance and failure recovery techniques. Embodiments of the present disclosure may utilize checkpoints to map processed output files to their corresponding input files. Therefore, if an error occurs in processing one or more files, the system may only need to reschedule processing of selected file(s).
- San Mateo CA, US Igor Demura - San Mateo CA, US Varun Ganesh - San Mateo CA, US Prasanna Rajaperumal - San Mateo CA, US Libo Wang - Foster City CA, US Jiaqi Yan - San Mateo CA, US
International Classification:
G06F 16/2453
Abstract:
Embodiments of the present disclosure may provide a dynamic query execution model. This query execution model may provide acceleration by scaling out parallel parts of a query (also referred to as a fragment) to additional computing resources, for example computing resources leased from a pool of computing resources. Execution of the parts of the query may be coordinated by a parent query coordinator, where the query originated, and a fragment query coordinator.
- San Mateo CA, US Igor Demura - San Mateo CA, US Varun Ganesh - San Mateo CA, US Prasanna Rajaperumal - San Mateo CA, US Libo Wang - Foster City CA, US Jiaqi Yan - San Mateo CA, US
Embodiments of the present disclosure may provide a dynamic query execution model with fault tolerance and failure recovery techniques. Embodiments of the present disclosure may utilize checkpoints to map processed output files to their corresponding input files. Therefore, if an error occurs in processing one or more files, the system may only need to reschedule processing of selected file(s).
- Bozeman MT, US Igor Demura - San Mateo CA, US Varun Ganesh - San Mateo CA, US Prasanna Rajaperumal - San Mateo CA, US Libo Wang - Foster City CA, US Jiaqi Yan - San Mateo CA, US
International Classification:
G06F 9/50 H04L 29/08 G06F 9/54
Abstract:
Embodiments of the present disclosure may provide dynamic and fair assignment techniques for allocating resources on a demand basis. Assignment control may be separated into at least two components: a local component and a global component. Each component may have an active dialog with each other; the dialog may include two aspects: 1) a demand for computing resources, and 2) a total allowed number of computing resources. The global component may allocate resources from a pool of resources to different local components, and the local components in turn may assign their allocated resources to local competing requests. The allocation may also be throttled or limited at various levels.
- San Mateo CA, US Varun Ganesh - San Mateo CA, US Jiansheng Huang - San Mateo CA, US Jiaxing Liang - Bellevue WA, US Haowei Yu - Newark CA, US Scott Ziegler - San Mateo CA, US
International Classification:
G06F 16/23 G06F 16/22 G06F 16/25
Abstract:
The subject technology obtains, at a database system, an ingest request to ingest one or more files into a table of a database. The subject technology, after obtaining the ingest request and prior to the ingesting of the one or more files, persists the one or more files in a file queue that corresponds to the table. The subject technology assigns the one or more files to one or more execution nodes to be ingested into the table. The subject technology operates an ingest puller to poll the file queue. The subject technology ingests, by the one or more execution nodes, the one or more files into one or more micro-partitions of the table via one or more pipes.