Scalable Scientific
Stream Query Processing

By Milena Ivanova
Uppsala Dissertations from the Faculty of Science and Technology, No. 66
December 2005
Uppsala University Press
ISBN: 9155463517
148 pages, Illustrated, 6 ½ x 9 ½”
$42.50 Paper Original

This is a Ph.D. dissertation. Scientific applications require processing of high-volume on-line streams of numerical data from instruments and simulations. In order to extract information and detect interesting patterns in these streams scientists need to perform on-line analyses including advanced and often expensive numerical computations.

We present an extensible data stream management system, GSDM (Grid System Data Manager) that supports scalable and flexible continuous queries (CQs) on such streams. Application dependent streams and query functions are defined through an object-relational model. Distributed execution plans for CQs are specified as high-level data flow distribution templates.

A built-in template library provides several common distribution patterns from which complex distribution patterns are constructed. Using a generic template we define two customizable partitioning strategies for scalable parallel execution of expensive stream queries: window split and window distribute. Window split provides parallel execution of expensive query functions by reducing the size of stream data units using application dependent functions as parameters. By contrast, window distribute provides customized distribution of entire data units without reducing their size.

Computer Software

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