Rishan Chen
Peking University
13 Papers
266 Citations
Rishan Chen is an academic researcher from Peking University. The author has contributed to research in topics: Cloud computing & Distributed File System. The author has an hindex of 11, co-authored 13 publications. Previous affiliations of Rishan Chen include University of California, San Diego & Microsoft.
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Papers
Comet: batched stream processing for data intensive distributed computing
Bingsheng He,Mao Yang,Zhenyu Guo,Rishan Chen,Bing Su,Wei Lin,Lidong Zhou +6 more
- 10 Jun 2010
TL;DR: A query processing system called Comet is developed that embraces batched stream processing and integrates with DryadLINQ, and when applied to a real production trace covering over 19 million machine-hours shows an estimated I/O saving of over 50%.
•Proceedings Article
Optimizing data shuffling in data-parallel computation by understanding user-defined functions
Jiaxing Zhang,Hucheng Zhou,Rishan Chen,Xuepeng Fan,Zhenyu Guo,Haoxiang Lin,Jack Li,Wei Lin,Jingren Zhou,Lidong Zhou +9 more
- 25 Apr 2012
TL;DR: This work identifies useful functional properties for user-defined functions, and proposes SUDO, an optimization framework that reasons about data-partition properties, functional properties, and data shuffling.
Spotting code optimizations in data-parallel pipelines through PeriSCOPE
Zhenyu Guo,Xuepeng Fan,Rishan Chen,Jiaxing Zhang,Hucheng Zhou,Sean McDirmid,Chang Liu,Wei Lin,Jingren Zhou,Lidong Zhou +9 more
- 08 Oct 2012
TL;DR: PeriScope as mentioned in this paper automatically optimizes a data-parallel program's procedural code in the context of data flow that is reconstructed from the program's pipeline topology, so that less data is transferred between pipeline stages.
•Proceedings Article
A Novel Burst-based Text Representation Model for Scalable Event Detection
Xin Zhao,Rishan Chen,Kai Fan,Hongfei Yan,Xiaoming Li +4 more
- 08 Jul 2012
TL;DR: A novel burst-based text representation model, denoted as BurstVSM, which corresponds dimensions to bursty features instead of terms, which can capture semantic and temporal information and significantly reduces the number of non-zero entries in the representation.
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EventSearch: a system for event discovery and retrieval on multi-type historical data
Dongdong Shan,Wayne Xin Zhao,Rishan Chen,Baihan Shu,Ziqi Wang,Junjie Yao,Hongfei Yan,Xiaoming Li +7 more
- 12 Aug 2012
TL;DR: EventSearch, a system for event extraction and retrieval on four types of news-related historical data, i.e., Web news articles, newspapers, TV news program, and micro-blog short messages, provides meaningful analytics that synthesize an accurate description of events.
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