OptFSST：优化的FSST字符串压缩
OptFSST: Optimized FSST String Compression
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中文总结 AI 辅助
研究字符串压缩问题，提出OptFSST优化FSST，通过动态规划、增加频率计数器和修剪策略提高压缩因子，扩展技术到FSST12得OptFSST12，实验表明其提升了压缩效果与解压缩速度。
中文摘要 AI 辅助
在现代分析系统中，字符串占数据的很大比例，因此具有快速随机访问功能的轻量级压缩成为高效查询处理的重要组成部分。快速静态符号表（FSST）通过用紧凑代码替换频繁字节序列来满足这一需求，同时保留单个字符串的独立解压缩。然而，FSST的压缩效果受其贪婪符号选择和贪婪编码策略限制。本文提出OptFSST，一种优化的FSST变体，在保持其静态符号表设计和随机访问解压缩的同时提高压缩因子。OptFSST使用动态规划对给定符号表的文本进行最优编码。此外，当字母表是输入的一部分时，符号表选择问题的广义版本是NP难的，这促使为字段级压缩器构建启发式表。因此，OptFSST增加了一个加速发现更长符号的频率计数器和一个在表构建过程中去除冗余和冲突符号候选的修剪策略。我们还将相同技术扩展到FSST12，得到OptFSST12。对92个真实世界字符串数据集的评估表明，OptFSST分别将FSST和FSST12的压缩因子提高了47.7%和91.5%，平均提高7.3%和17.0%，同时保留细粒度随机访问属性。值得注意的是，OptFSST12平均将FSST12的解压缩速度提高了1.2倍。
英文摘要
Strings account for a substantial fraction of data in modern analytical systems, making lightweight compression with fast random access an important building block for efficient query processing. Fast Static Symbol Table (FSST) addresses this need by replacing frequent byte sequences with compact codes while preserving independent decompression of individual strings. However, FSST's compression effectiveness is limited by its greedy symbol selection and greedy encoding strategy, leaving encoding gains on the table. We present OptFSST, an optimized FSST variant that improves its compression factors while preserving its static-symbol-table design and random-access decompression. OptFSST optimally encodes the text using dynamic programming given a symbol table. Additionally, we show that a generalized version of the symbol-table selection problem is NP-hard when the alphabet is part of the input, motivating heuristic table construction for field-level compressors. Hence, we add in OptFSST (i) an additional frequency counter that accelerates the discovery of longer symbols and (ii) a pruning strategy that removes redundant and conflicting symbol candidates during table construction. We also extend the same techniques to FSST12, yielding OptFSST12. Our evaluation on 92 real-world string datasets shows that OptFSST improves the compression factors of FSST and FSST12 by up to 47.7% and 91.5%, with an average improvement of 7.3% and 17.0%, respectively, while retaining the fine-grained random-access properties. Notably, OptFSST12 improves FSST12's decompression speed by $1.2\times$ on average.
