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Building OLAP Cubes from Columnar NoSQL Data Warehouses

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Model and Data Engineering (MEDI 2016)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 9893))

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Abstract

The work presented in this paper aims to build OLAP cubes from big data warehouses implemented by using the columnar NoSQL model. The use of NoSQL models is motivated by the inability of the relational model, usually used to implement data warehousing, to allow data scalability easily. Indeed, the columnar NoSQL model is suitable for storing and managing massive data, especially for decisional queries. However, the column-oriented NoSQL DBMS do not offer online analysis operators (OLAP). Our main contribution is to define a new cube operator called MC-CUBE (MapReduce Columnar CUBE), which allows building columnar NoSQL cubes by taking into account the no relational and distributed aspects when data warehouses are stored.

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Notes

  1. 1.

    http://www.cs.umb.edu/~poneil/StarSchemaB.PDF.

  2. 2.

    https://hbase.apache.org/.

  3. 3.

    http://hadoop.apache.org/.

  4. 4.

    http://hbase.apache.org/0.94/book/zookeeper.html.

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Author information

Authors and Affiliations

  1. ERIC Laboratory/University of Lyon 2, 5 avenue Pierre Mendes-France, 69676, Bron Cedex, France

    Khaled Dehdouh

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  1. Khaled Dehdouh
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Correspondence to Khaled Dehdouh .

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Editors and Affiliations

  1. LIAS/ISAE-ENSMA , Futuroscope Chasseneuil, France

    Ladjel Bellatreche

  2. Department of Information Systems and Computation, Universitat Politècnica de València, Valencia, Spain

    Óscar Pastor

  3. University of Almería , Almería, Spain

    Jesús M. Almendros Jiménez

  4. IRIT / ENSEIHT , Toulouse, France

    Yamine Aït-Ameur

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Dehdouh, K. (2016). Building OLAP Cubes from Columnar NoSQL Data Warehouses. In: Bellatreche, L., Pastor, Ó., Almendros Jiménez, J., Aït-Ameur, Y. (eds) Model and Data Engineering. MEDI 2016. Lecture Notes in Computer Science(), vol 9893. Springer, Cham. https://doi.org/10.1007/978-3-319-45547-1_14

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  • DOI: https://doi.org/10.1007/978-3-319-45547-1_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45546-4

  • Online ISBN: 978-3-319-45547-1

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