Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/137731
Title: ONLINE DATA PROCESSING AT SCALE
Authors: LIN QIAN
ORCID iD:   orcid.org/0000-0002-7665-601X
Keywords: data stream, stream join, distributed database, transaction management, concurrency control, OLTP
Issue Date: 18-Aug-2017
Source: LIN QIAN (2017-08-18). ONLINE DATA PROCESSING AT SCALE. ScholarBank@NUS Repository.
Abstract: The ubiquitous online data bring opportunities of insightful analytics, as well as the challenges of system processing at large scale. Online data are generally processed in two fundamental fashions: stream processing to meet the needs of real-time application, and transaction processing to address the coordination of short atomic computations. In this thesis, we look into the problems of scalable online data processing in distributed database systems, and specifically focus on the design and optimization of the key operators and protocols in real-time OLAP (online analytical processing) and OLTP (online transaction processing). In particular, we investigate the techniques for scalable distributed stream join processing, efficient distributed transaction management, and adaptive and speculative concurrency control protocol.
URI: http://scholarbank.nus.edu.sg/handle/10635/137731
Appears in Collections:Ph.D Theses (Open)

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