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PARALLEL ALGORITHMS FOR THE EXECUTION OF RELATIONAL DATABASE OPERATIONS REVISITED ON GRIDS

机译:在网格上重新执行关系数据库操作的并行算法

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This paper presents an analytical discussion of algorithms for relational database operations in a grid environment, compares the findings with the classical generalized multiprocessor framework, and describes an optimization algorithm to maximize performance for a heterogeneous environment.rnWe develop a concise but comprehensive analytical model of parallel algorithms for sorting, joining, and aggregation. In our approach we focus on a limited number of characteristic parameters to keep the analytical model clear. It is shown that an expressive model can be built upon just three characteristic parameter sets, namely the node processing performance and the network and the disk bandwidths. These parameters are the input for the optimization process for the orchestration of the execution workflow on the grid. Based on these results the paper proves that using smart enhancement to exploit the heterogeneity of the grid, the performance of the algorithms for database operations can be increased remarkably.
机译:本文对网格环境中的关系数据库操作算法进行了分析性讨论,将研究结果与经典的通用多处理器框架进行了比较,并描述了一种优化算法,以使异构环境的性能最大化。我们开发了一个简洁而全面的并行分析模型排序,联接和聚合的算法。在我们的方法中,我们专注于有限数量的特征参数,以保持清晰的分析模型。结果表明,表达模型可以仅基于三个特征参数集建立,即节点处理性能以及网络和磁盘带宽。这些参数是在网格上执行工作流程的业务流程的优化过程的输入。基于这些结果,本文证明了使用智能增强来利用网格的异构性,可以显着提高数据库操作算法的性能。

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