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Practical and Effective Re-Pair Compression

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abstract

Re-Pair is an efficient grammar compressor that operates by recursively replacing high-frequency character pairs with new grammar symbols. The most space-efficient linear-time algorithm computing Re-Pair uses $(1+\epsilon)n+\sqrt n$ words on top of the re-writable text (of length $n$ and stored in $n$ words), for any constant $\epsilon>0$; in practice however, this solution uses complex sub-procedures preventing it from being practical. In this paper, we present an implementation of the above-mentioned result making use of more practical solutions; our tool further improves the working space to $(1.5+\epsilon)n$ words (text included), for some small constant $\epsilon$. As a second contribution, we focus on compact representations of the output grammar. The lower bound for storing a grammar with $d$ rules is $\log(d!)+2d\approx d\log d+0.557 d$ bits, and the most efficient encoding algorithm in the literature uses at most $d\log d + 2d$ bits and runs in $\mathcal O(d^{1.5})$ time. We describe a linear-time heuristic maximizing the compressibility of the output Re-Pair grammar. On real datasets, our grammar encoding uses---on average---only $2.8\%$ more bits than the information-theoretic minimum. In half of the tested cases, our compressor improves the output size of 7-Zip with maximum compression rate turned on.

fields

cs.DS 1

years

2019 1

verdicts

REJECT 1

representative citing papers

Re-Pair In Small Space

cs.DS · 2019-08-14 · reject · novelty 7.0

A new algorithm computes Re-Pair, a grammar-based compression method, in O(n^2) time using roughly text-sized working space, but the core frequency-counting proof appears to overcount repeated-character bigrams.

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  • Re-Pair In Small Space cs.DS · 2019-08-14 · reject · none · ref 4 · internal anchor

    A new algorithm computes Re-Pair, a grammar-based compression method, in O(n^2) time using roughly text-sized working space, but the core frequency-counting proof appears to overcount repeated-character bigrams.