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Distributed stream processing analysis in high availability context

  • Silesian University of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

Not so long ago data warehouses were used to process data sets loaded periodically during ETL process (Extraction, Transformation and Loading). We could distinguish two kinds of ETL processes: full and incremental. Now we often have to process real-time data and analyse them almost on-the-fly, so the analyses are always up to date. There are many possible applications for real-time data warehouses. In most cases two features are important: delivering data to the warehouse as quick as possible, and not losing any tuple in case of failures. In this paper we propose an architecture for gathering and processing data from geographically distributed data sources. We present theoretical analysis, mathematical model of a data source, some rules of system modules configuration and results of experiments. At the end of the paper our future plans are described briefly.

Original languageEnglish
Title of host publicationProceedings - The Second International Conference on Availability, Reliability and Security, ARES 2007
PublisherIEEE Computer Society
Pages61-68
Number of pages8
ISBN (Print)0769527752, 9780769527758
DOIs
Publication statusPublished - 2007
Event2nd International Conference on Availability, Reliability and Security, ARES 2007 - Vienna, Austria
Duration: 10 Apr 200713 Apr 2007

Publication series

NameProceedings - Second International Conference on Availability, Reliability and Security, ARES 2007

Conference

Conference2nd International Conference on Availability, Reliability and Security, ARES 2007
Country/TerritoryAustria
CityVienna
Period10/04/0713/04/07

ASJC Scopus subject areas

  • Information Systems
  • Electrical and Electronic Engineering
  • Safety, Risk, Reliability and Quality

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