克服后缀树结构中的内存瓶颈

Martín Farach-Colton, P. Ferragina, S. Muthukrishnan
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引用次数: 73

摘要

字符串的后缀树是字符串处理的基本数据结构。最近对大规模数据集的关注激发了人们对克服构建后缀树的已知算法的内存瓶颈的兴趣。我们的主要贡献是一个用于后缀树构造的新算法,在该算法中,我们将几乎所有磁盘访问都编排为通过排序和扫描原语。该算法在各种顺序和并行计算模型下均能获得最优结果。我们的两个结果是:在传统的外部内存模型中,只计算磁盘访问的次数,我们实现了一个最优算法,对于单个和多个磁盘情况。这是已知的两个模型的第一个最优算法。传统的磁盘页面访问计数不区分随机页面访问和涉及多个连续页面的块传输。专业程序员经常利用这种差异在真实机器上获得快速算法。我们采用了一个简单的记帐方案,并表明我们的算法在块与随机页面访问方面实现了与我们为排序建立的算法相同的最佳权衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Overcoming the memory bottleneck in suffix tree construction
The suffix tree of a string is the fundamental data structure of string processing. Recent focus on massive data sets has sparked interest in overcoming the memory bottlenecks of known algorithms for building suffix trees. Our main contribution is a new algorithm for suffix tree construction in which we choreograph almost all disk accesses to be via the sort and scan primitives. This algorithm achieves optimal results in a variety of sequential and parallel computational models. Two of our results are: In the traditional external memory model, in which only the number of disk accesses is counted, we achieve an optimal algorithm, both for single and multiple disk cases. This is the first optimal algorithm known for either model. Traditional disk page access counting does not differentiate between random page accesses and block transfers involving several consecutive pages. This difference is routinely exploited by expert programmers to get fast algorithms on real machines. We adopt a simple accounting scheme and show that our algorithm achieves the same optimal tradeoff for block versus random page accesses as the one we establish for sorting.
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