Publication details

Towards High Similarity Search Throughput by Dynamic Query Reordering and Parallel Processing

Authors

NÁLEPA Filip BATKO Michal ZEZULA Pavel

Year of publication 2017
Type Article in Proceedings
Conference Advances in Databases and Information Systems : 21st European Conference, ADBIS 2017, Nicosia, Cyprus, September 24-27, 2017, Proceedings
MU Faculty or unit

Faculty of Informatics

Citation
Doi http://dx.doi.org/10.1007/978-3-319-66917-5_18
Field Informatics
Keywords stream processing; similarity search; parallel processing
Description Current era of digital data explosion calls for employment of content-based similarity search techniques since traditional searchable metadata like annotations are not always available. In our work, we focus on a scenario where the similarity search is used in the context of stream processing, which is one of the suitable approaches to deal with huge amounts of data. Our goal is to maximize the throughput of processed queries while a slight delay is acceptable. We extend our previously published technique that dynamically reorders the incoming queries in order to use our caching mechanism more effectively. The extension lies in adoption of a parallel computing environment which allows us to process multiple queries simultaneously.
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