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1. Document-Oriented Models for Data Warehouses

Author

Chevalier, Max, El Malki, Mohammed, Kopliku, Arlind, Teste, Olivier, Tournier, Ronan, Centre National de la Recherche Scientifique - CNRS (FRANCE), Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Université Toulouse - Jean Jaurès - UT2J (FRANCE), Université Toulouse 1 Capitole - UT1 (FRANCE), and Capgemini (FRANCE)

Subjects
Théorie de l'information, Big data, Data warehouse, Star schema, InformationSystems_DATABASEMANAGEMENT, Recherche d'information, NoSQL, Document-oriented, Multidimensional data model, H- INFORMATIQUE
Abstract

There is an increasing interest in NoSQL (Not Only SQL) systems developed in the area of Big Data as candidates for implementing multidimensional data warehouses due to the capabilities of data structuration/storage they offer. In this paper, we study implementation and modeling issues for data warehousing with document-oriented systems, a class of NoSQL systems. We study four different mappings of the multidimensional conceptual model to document data models. We focus on formalization and cross-model comparison. Experiments go through important features of data warehouses including data loading, OLAP cuboid computation and querying. Document-oriented systems are also compared to relational systems.

Published
2016

2. Benchmark for OLAP on NoSQL Technologies

Author

Max Chevalier, Mohammed El Malki, Arlind Kopliku, Olivier Teste, Ronan Tournier, Systèmes d’Informations Généralisées (IRIT-SIG), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Université Toulouse III - Paul Sabatier (UT3), Capgemini [Toulouse], Capgemini, Université Toulouse - Jean Jaurès (UT2J), Centre National de la Recherche Scientifique - CNRS (FRANCE), Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Université Toulouse - Jean Jaurès - UT2J (FRANCE), Université Toulouse 1 Capitole - UT1 (FRANCE), Capgemini (FRANCE), and Institut National Polytechnique de Toulouse - INPT (FRANCE)

Subjects
Théorie de l'information, OLAP, Recherche d'information, NoSQL, Decision support systems, Data Warehouses, Big data, MongoDB, HBase, [INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT], [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], H- INFORMATIQUE, Computer Science::Databases
Abstract

International audience; The plethora of data warehouse solutions has created a need comparing these solutions using experimental benchmarks. Existing benchmarks rely mostly on the relational data model and do not take into account other models. In this paper, we propose an extension to a popular benchmark (the Star Schema Benchmark or SSB) that considers non-relational NoSQL models. To avoid data post-processing required for using this data with NoSQL systems, the data is generated in different formats. To exploit at best horizontal scaling, data can be produced in a distributed file system, hence removing disk or partition sizes as limit for the generated dataset. Experimental work proves improved performance of our new benchmark.

Published
2015