SkyEngine: Efficient Skyline search engine for Continuous Skyline computations

  • Authors:
  • Yu-Ling Hsueh;Roger Zimmermann;Wei-Shinn Ku;Yifan Jin

  • Affiliations:
  • Teradata, San Diego, CA, USA;Computer Science Department, National University of Singapore, Singapore;Dept. of Computer Science and Software Engineering, Auburn University, USA;Dept. of Computer Science, University of Hong Kong, China

  • Venue:
  • ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
  • Year:
  • 2011

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Abstract

Skyline query processing has become an important feature in multi-dimensional, data-intensive applications. Such computations are especially challenging under dynamic conditions, when either snapshot queries need to be answered with short user response times or when continuous skyline queries need to be maintained efficiently over a set of objects that are frequently updated. To achieve high performance, we have recently designed the ESC algorithm, an Efficient update approach for Skyline Computations. ESC creates a pre-computed candidate skyline set behind the first skyline (a "second line of defense," so to speak) that facilitates an incremental, two-stage skyline update strategy which results in a quicker query response time for the user. Our demonstration presents the two-threaded SkyEngine system that builds upon and extends the base-features of the ESC algorithm with innovative, user-oriented functionalities that are termed SkyAlert and AutoAdjust. These functions enable a data or service provider to be informed about and gain the opportunity of automatically promoting its data records to remain part of the skyline, if so desired. The SkyEngine demonstration includes both a server and a web browser based client. Finally, the SkyEngine system also provides visualizations that reveal its internal performance statistics.