Hypergraphs in the Service of Very Large Scale Query Optimization. Application : Data Warehousing

Abstract : The emergence of the phenomenon Big-Data conducts to the introduction of new increased and urgent needs to share data between users and communities, which has engender a large number of queries that DBMS must handle. This problem has been compounded by other needs of recommendation and exploration of queries. Since data processing is still possible through solutions of query optimization, physical design and deployment architectures, in which these solutions are the results of combinatorial problems based on queries, it is essential to review traditional methods to respond to new needs of scalability. This thesis focuses on the problem of numerous queries and proposes a scalable approach implemented on framework called Big-queries and based on the hypergraph, a flexible data structure, which bas a larger modeling power and may allow accurate formulation of many problems of combinatorial scientific computing. This approach is the result of collaboration with the company Mentor Graphies. It aims to capture the queries interaction in an unified query plan and to use partitioning algorithms to ensure scalability and to optimal optimization structures (materialized views and data partitioning). Also, the unified plan is used in the deploymemt phase of parallel data warehouses, by allowing data partitioning in fragments and allocating these fragments in the correspond processing nodes. Intensive experimental study sbowed the interest of our approach in terms of scaling algorithms and minimization of query response time.
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Ahcène Boukorca. Hypergraphs in the Service of Very Large Scale Query Optimization. Application : Data Warehousing. Other [cs.OH]. ISAE-ENSMA Ecole Nationale Supérieure de Mécanique et d'Aérotechique - Poitiers, 2016. English. ⟨NNT : 2016ESMA0026⟩. ⟨tel-01488961⟩

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