The time-based data partitioning method for XML query optimization

  • Authors:
  • Majed Abdullah Algarni

  • Affiliations:
  • Kingdom of Saudi Arabia, Technical and Vocational Training Corporation

  • Venue:
  • Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services
  • Year:
  • 2011

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Abstract

With today's technology it is essential that databases operate efficiently and effectively. Temporal databases are a case in point with reference to data and volume of material. This paper proposes an XML temporal database model, and importantly, an intensive partitioning algorithm that improves query performance and manages time intervals. The proposed partitioning approach employs deep data analysis, a variety of scenarios and partitioning of data, based on the data itself and the transactions made on it. Categorizing data into historical and current data using data lifecycle management is the first strategy applied here. Time intervals as time lines are then considered and this refers to locating data in sub-partitions within certain time limits. Several subpartitions are merged into one partition that encapsulates all subpartition limits. All time intervals in all XML data levels represent part of the partitioning approach and updated transactions are vital for starting and ending partitions.