Parallel FP-Growth on PC Cluster
Parallel FP-Growth on PC Cluster
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DOI：
10.1007/3-540-36175-8_47
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发表时间：
2003-04
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影响因子：
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通讯作者：
Iko Pramudiono;M. Kitsuregawa
中科院分区：
文献类型：
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作者：
Iko Pramudiono;M. Kitsuregawa
FP-Growth算法已经成为挖掘频繁模式的一种流行算法。它的元数据FP-树比以前报道的算法有了显著的性能改进。然而，特殊数据结构也限制了进一步扩展的能力。当FP-树不能放入内存时，也存在潜在的问题。在本文中，我们报告了FP-Growth的并行执行。我们分析了并行化的瓶颈，并提出了在无共享环境下有效平衡执行的方法。
FP-growth has become a popular algorithm to mine frequent patterns. Its metadata FP-tree has allowed significant performance improvement over previously reported algorithms. However that special data structure also restrict the ability for further extensions. There is also potential problem when FP-tree can not fit into the memory. In this paper, we report parallel execution of FP-growth. We examine the bottlenecks of the parallelization and also method to balance the execution efficiently on shared-nothing environment.