BAH:一种快速数据检索的位图索引压缩算法

Chenxing Li, Zhen Chen, Wenxun Zheng, Yinjun Wu, Junwei Cao
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引用次数: 4

摘要

高效检索流量档案数据是检测APT(高级持续威胁)等网络攻击的必要技术。为了从互联网流量中获得洞察力,位图索引越来越多地用于对大型数据集进行有效查询。但是,原始位图索引会导致高空间消耗和加载索引的开销。为了在节省存储空间的同时提高查询效率,提出了多种位图索引压缩算法。提出了一种新的位图索引压缩算法BAH (Byte Aligned Hybrid compression coding)。为了提高多个压缩位图的AND运算效率,设计了一种基于SIMD的加速算法。总而言之,与之前的几个作品如WAH、PLWAH、COMPAX、Roaring等相比,BAH具有更好的压缩比和更快的交叉口查询速度。理论分析表明,BAH所需的空间不大于密度大于0.2%的位图信息熵的1.6倍。在实验中,在两个数据集上,BAH比WAH分别节省65%和60%的空间。实验还验证了BAH在Internet流量和网页查询中的应用效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
BAH: A Bitmap Index Compression Algorithm for Fast Data Retrieval
Efficient retrieval of traffic archival data is a must-have technique to detect network attacks, such as APT(advanced persistent threat) attack. In order to take insight from Internet traffic, the bitmap index is increasingly used for efficiently querying over large datasets. However, a raw bitmap index leads to high space consumption and overhead on loading indexes. Various bitmap index compression algorithms are proposed to save storage while improving query efficiency. This paper proposes a new bitmap index compression algorithm called BAH (Byte Aligned Hybrid compression coding). An acceleration algorithm using SIMD is designed to increase the efficiency of AND operation over multiple compressed bitmaps. In all, BAH has a better compression ratio and faster intersection querying speed compared with several previous works such as WAH, PLWAH, COMPAX, Roaring etc. The theoretical analysis shows that the space required by BAH is no larger than 1.6 times the information entropy of the bitmap with density larger than 0.2%. In the experiments, BAH saves about 65% space and 60% space compared with WAH on two datasets. The experiments also demonstrate the query efficiency of BAH with the application in Internet Traffic and Web pages.
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