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Query Optimization in NoSQL Databases Using an Enhanced Localized R-tree Index

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Information Integration and Web Intelligence (iiWAS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13635))

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Abstract

Query optimization is a crucial process across data mining and big data analytics. As the size of the data in the modern applications is increasing due to various sources, types and multi-modal records across databases, there is an urge to optimize lookup and search operations. Therefore, indexes can be utilized to solve the matter of rapid data growth as they enhance the performance of the database and subsequently the cloud server where it is stored. In this paper an index on spatial data, i.e. coordinates on the plane or on the map is presented. This index is be based on the R-Tree which is suitable for spatial data and is distributed so that it can scale and adapt to massive amounts of data without losing its performance. The results of the proposed method are encouraging across all experiments and future directions of this work include experiments on skewed data.

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Notes

  1. 1.

    which stores the coordinates in ascending order, beginning with the lower left corner of the rectangle and ending with the top left corner.

  2. 2.

    Even when many users execute the same query at the same time.

  3. 3.

    This indicates that there are no thick or sparse regions within the space covered within the datasets and ensures that the burden is dispersed evenly across the reducers.

  4. 4.

    The distributed index contains Terabytes of records.

  5. 5.

    Because sorting is being done by HBase, PUT functions on a lower table size are substantially quicker than on a much bigger table.

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Author information

Authors and Affiliations

  1. Computer Engineering and Informatics Department, University of Patras, Patras, Greece

    Aristeidis Karras, Christos Karras, Dimitrios Samoladas & Spyros Sioutas

  2. Department of Management Science and Technology, University of Patras, Patras, Greece

    Konstantinos C. Giotopoulos

Authors
  1. Aristeidis Karras
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  2. Christos Karras
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  3. Dimitrios Samoladas
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  4. Konstantinos C. Giotopoulos
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  5. Spyros Sioutas
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Corresponding author

Correspondence to Aristeidis Karras .

Editor information

Editors and Affiliations

  1. La Trobe University, Melbourne, VIC, Australia

    Eric Pardede

  2. Monash University, Melbourne, VIC, Australia

    Pari Delir Haghighi

  3. Johannes Kepler University Linz, Linz, Austria

    Ismail Khalil

  4. Johannes Kepler University Linz, Linz, Austria

    Gabriele Kotsis

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Karras, A., Karras, C., Samoladas, D., Giotopoulos, K.C., Sioutas, S. (2022). Query Optimization in NoSQL Databases Using an Enhanced Localized R-tree Index. In: Pardede, E., Delir Haghighi, P., Khalil, I., Kotsis, G. (eds) Information Integration and Web Intelligence. iiWAS 2022. Lecture Notes in Computer Science, vol 13635. Springer, Cham. https://doi.org/10.1007/978-3-031-21047-1_33

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  • DOI: https://doi.org/10.1007/978-3-031-21047-1_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-21046-4

  • Online ISBN: 978-3-031-21047-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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