Conference proceeding
Answering Temporal Analytic Queries over Big Data Based on Precomputing Architecture
Intelligent Information and Database Systems 9th Asian Conference, ACIIDS 2017, Kanazawa, Japan, April 3-5, 2017, Proceedings, Part I, Vol.10191, pp.281-290
Lecture Notes in Artificial Intelligence
ACIIDS: Asian Conference on Intelligent Information and Database Systems (Kanazawa, Japan, 03/04/2017 - 05/04/2017)
01/01/2017
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Source: InCites
Abstract
Big data explosion brings revolutionary changes to many aspects of our lives. Huge volume of data, along with its complexity poses big challenges to data analytic applications. Techniques proposed in data warehousing and online analytical processing (OLAP), such as precomputed multidimensional cubes, dramatically improve the response time of analytic queries based on relational databases. There are some recent works extending similar concepts into NoSQL such as constructing cubes from NoSQL stores and converting existing cubes into NoSQL stores. However, only few works are studying the precomputing structure deliberately within NoSQL databases. In this paper, we present an architecture for answering temporal analytic queries over big data by precomputing the results of granulated chunks of collections which are decomposed from the original large collection. By using the precomputing structure, we are able to answer the drill-down and roll-up temporal queries over large amount of data within reasonable response time.
Details
- Title
- Answering Temporal Analytic Queries over Big Data Based on Precomputing Architecture
- Creators
- Nigel Franciscus - Institute for Integrated and Intelligent Systems (Nathan, QLD, Australia)Xuguang Ren - Institute for Integrated and Intelligent Systems (Nathan, QLD, Australia)Bela Stantic - Institute for Integrated and Intelligent Systems (Nathan, QLD, Australia)
- Contributors
- N T Nguyen (Editor)S Tojo (Editor)L M Nguyen (Editor)B Trawinski (Editor)
- Publication Details
- Intelligent Information and Database Systems 9th Asian Conference, ACIIDS 2017, Kanazawa, Japan, April 3-5, 2017, Proceedings, Part I, Vol.10191, pp.281-290
- Conference
- ACIIDS: Asian Conference on Intelligent Information and Database Systems (Kanazawa, Japan, 03/04/2017 - 05/04/2017)
- Series
- Lecture Notes in Artificial Intelligence
- Publisher
- Springer Nature
- Number of pages
- 10
- Identifiers
- 991013099080202368
- Copyright
- © 2017 Springer International Publishing AG.
- Academic Unit
- Faculty of Science and Engineering
- Language
- English
- Resource Type
- Conference proceeding