On Optimally Partitioning Variable-Byte Codes

TL;DR

This paper demonstrates that partitioning Variable-Byte codes significantly improves their compression ratio, making them competitive with advanced encoders while maintaining fast query processing and minimal indexing overhead.

Contribution

It introduces an optimal partitioning algorithm for Variable-Byte codes that doubles compression efficiency without impacting indexing speed.

Findings

Compression ratio of Variable-Byte improved by 2x with partitioning.

Partitioned Variable-Byte matches space efficiency of bit-aligned encoders.

Query processing speed remains unaffected by the partitioning approach.

Abstract

The ubiquitous Variable-Byte encoding is one of the fastest compressed representation for integer sequences. However, its compression ratio is usually not competitive with other more sophisticated encoders, especially when the integers to be compressed are small that is the typical case for inverted indexes. This paper shows that the compression ratio of Variable-Byte can be improved by 2x by adopting a partitioned representation of the inverted lists. This makes Variable-Byte surprisingly competitive in space with the best bit-aligned encoders, hence disproving the folklore belief that Variable-Byte is space-inefficient for inverted index compression. Despite the significant space savings, we show that our optimization almost comes for free, given that: we introduce an optimal partitioning algorithm that does not affect indexing time because of its linear-time complexity; we show that the query processing speed of Variable-Byte is preserved, with an extensive experimental analysis and comparison with several other state-of-the-art encoders.