Title
Kineograph: taking the pulse of a fast-changing and connected world
Abstract
Kineograph is a distributed system that takes a stream of incoming data to construct a continuously changing graph, which captures the relationships that exist in the data feed. As a computing platform, Kineograph further supports graph-mining algorithms to extract timely insights from the fast-changing graph structure. To accommodate graph-mining algorithms that assume a static underlying graph, Kineograph creates a series of consistent snapshots, using a novel and efficient epoch commit protocol. To keep up with continuous updates on the graph, Kineograph includes an incremental graph-computation engine. We have developed three applications on top of Kineograph to analyze Twitter data: user ranking, approximate shortest paths, and controversial topic detection. For these applications, Kineograph takes a live Twitter data feed and maintains a graph of edges between all users and hashtags. Our evaluation shows that with 40 machines processing 100K tweets per second, Kineograph is able to continuously compute global properties, such as user ranks, with less than 2.5-minute timeliness guarantees. This rate of traffic is more than 10 times the reported peak rate of Twitter as of October 2011.
Year
DOI
Venue
2012
10.1145/2168836.2168846
EuroSys
Keywords
Field
DocType
live twitter data feed,twitter data,data feed,connected world,graph-mining algorithm,reported peak rate,user rank,static underlying graph,incoming data,fast-changing graph structure,user ranking,distributed storage,shortest path,distributed system
Graph,Graph database,Ranking,Commit,Computer science,Distributed data store,Theoretical computer science,Real-time computing,Snapshot (computer storage),Data feed,Distributed computing
Conference
Citations 
PageRank 
References 
107
4.52
24
Authors
10
Search Limit
100107
Name
Order
Citations
PageRank
Raymond Cheng11409.46
Ji Hong21074.52
Aapo Kyrola3104933.52
Youshan Miao41969.97
Xuetian Weng52228.93
Ming Wu690162.61
Fan Yang71939.85
Lidong Zhou82136147.82
Feng Zhao94593455.17
Enhong Chen102106165.57