Inverted Index Compression Using Multi-codes

Decai Sun, Xiaoxia Wang
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引用次数: 2

Abstract

How to decrease the space consumed by index is a key issue in big data processing. In this paper, a new compression method is proposed to decrease the space consumption of inverted index. First, a lot of redundant integers are removed by using the techniques of splitting inverted list, adding tags and making groups. Second, the total number of small integers is increased by using d-gaps in each group. Third, these sub sequences are compressed using different codes. At last, all compressed sub sequences are combined into a long sequence. Experiment results show that our method decreases the compression ratio and its decoding speed is also fast.
使用多代码的倒排索引压缩
如何减少索引占用的空间是大数据处理中的一个关键问题。为了减少倒排索引的空间消耗,本文提出了一种新的压缩方法。首先,通过拆分倒排表、添加标签和分组等技术去除大量冗余整数。其次,在每组中使用d-gap来增加小整数的总数。第三,使用不同的编码对这些子序列进行压缩。最后,将所有压缩子序列组合成一个长序列。实验结果表明,该方法降低了压缩比,且译码速度快。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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