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A New Parallel Data Cube Construction Scheme

机译:一种新的并行数据多维数据集构建方案

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摘要

The pre-computation of data cubes is critical for improving the response time of OLAP (On-Line Analytical Processing) systems. To meet the need for improved performance created by growing data sizes, parallel solutions for data cube construction are becoming increasingly important. This paper presents a new parallel data cube construction scheme based on an extendible multidimensional array, which is dynamically extendible along any dimension without relocating any existing data. The authors have implemented and evaluated their parallel data cube construction methods on shared-memory multiprocessors. Given the performance limit, the methods achieve close to linear speedup with load balance. The authors 'experiments also indicate that their parallel methods can be more scalable on higher dimensional data cube construction.
机译:数据多维数据集的预计算对于提高OLAP(在线分析处理)系统的响应时间至关重要。为了满足不断增长的数据大小所带来的对提高性能的需求,用于数据多维数据集构建的并行解决方案变得越来越重要。本文提出了一种基于可扩展多维数组的新并行数据多维数据集构造方案,该方案可沿任何维度动态扩展,而无需重新定位任何现有数据。作者已经在共享内存多处理器上实现并评估了其并行数据多维数据集构造方法。在给定性能极限的情况下,这些方法可以在负载平衡的情况下接近线性加速。作者的实验还表明,他们的并行方法在更高维度的数据多维数据集构造上可以更具可伸缩性。

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