重新排序索引以获得更好的压缩：超越词典顺序
Reordering Rows for Better Compression: Beyond the Lexicographic Order
摘要：
在压缩数据库表之前对其进行排序可以提高压缩率。我们能做得比字典顺序更好吗？为了使行程长度编码压缩方案中的行程数最小化，行排序的最佳方法来自旅行推销员算法，尽管在运行时间和压缩之间存在显著的折衷。一种新的启发式方法，MultipleLists，它是最近邻的一个变体，它在压缩和运行时加速之间进行权衡，对于非常大的表来说是一个很好的选择。然而，对于某些压缩方案，生成长运行比生成少运行更重要。在这种情况下，另一种新的启发式算法Vortex很有前途。我们发现，我们可以提高行程长度编码高达3倍，而我们可以提高前缀编码高达80%：这些收益是由于字典排序表的收益之上。我们证明了新的行重新排序是最佳的（在10%以内），在列内相同值的运行最小化，在少数情况下。
英文摘要：
Sorting database tables before compressing them improves the compression rate. Can we do better than the lexicographical order? For minimizing the number of runs in a run-length encoding compression scheme, the best approaches to row-ordering are derived from traveling salesman heuristics, although there is a significant trade-off between running time and compression. A new heuristic, Multiple Lists, which is a variant on Nearest Neighbor that trades off compression for a major running-time speedup, is a good option for very large tables. However, for some compression schemes, it is more important to generate long runs rather than few runs. For this case, another novel heuristic, Vortex, is promising. We find that we can improve run-length encoding up to a factor of 3 whereas we can improve prefix coding by up to 80%: these gains are on top of the gains due to lexicographically sorting the table. We prove that the new row reordering is optimal (within 10%) at minimizing the runs of identical values within columns, in a few cases.
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