Model and procedure for performance and availability-wise parallel warehouses

Pedro Furtado
<span title="2009-02-20">2009</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/of3bmcozzfddjojxsoxwzys55y" style="color: black;">Distributed and parallel databases</a> </i> &nbsp;
Consider data warehouses as large data repositories queried for analysis and data mining in a variety of application contexts. A query over such data may take a large amount of time to be processed in a regular PC. Consider partitioning the data into a set of PCs (nodes), with either a parallel database server or any database server at each node and an engine-independent middleware. Nodes and network may even not be fully dedicated to the data warehouse. In such a scenario, care must be taken
more &raquo; ... r handling processing heterogeneity and availability, so we study and propose efficient solutions for this. We concentrate on three main contributions: a performance-wise index, measuring relative performance; a replication-degree; a flexible chunkwise organization with on-demand processing. These contributions extend the previous work on de-clustering and replication and are generic in the sense that they can be applied in very different contexts and with different data partitioning approaches. We evaluate their merits with a prototype implementation of the system.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s10619-009-7038-7">doi:10.1007/s10619-009-7038-7</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xibt4s7ernfffdsfaiavsntc6m">fatcat:xibt4s7ernfffdsfaiavsntc6m</a> </span>
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