Engineering Rank/Select Data Structures for Large-Alphabet Strings
arxiv(2023)
摘要
Large-alphabet strings are common in scenarios such as information retrieval
and natural-language processing. The efficient storage and processing of such
strings usually introduces several challenges that are not witnessed in
small-alphabets strings. This paper studies the efficient implementation of one
of the most effective approaches for dealing with large-alphabet strings,
namely the alphabet-partitioning approach. The main contribution is a
compressed data structure that supports the fundamental operations rank and
select efficiently. We show experimental results that indicate that our
implementation outperforms the current realizations of the
alphabet-partitioning approach. In particular, the time for operation select
can be improved by about 80
alphabet-partitioning schemes. We also show the impact of our data structure on
several applications, like the intersection of inverted lists (where
improvements of up to 60
representation of run-length compressed strings, and the
distributed-computation processing of rank and select operations. In the
particular case of run-length compressed strings, our experiments on the
Burrows-Wheeler transform of highly-repetitive texts indicate that by using
only about 0.98–1.09 times the space of state-of-the-art RLFM-indexes
(depending on the text), the process of counting the number of occurrences of a
pattern in a text can be carried out 1.23–2.33 times faster.
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