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arXiv:1705.00997cs.DS

Dynamic Space Efficient Hashing

Tobias Maier, Peter Sanders

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Abstract

We consider space efficient hash tables that can grow and shrink dynamically and are always highly space efficient, i.e., their space consumption is always close to the lower bound even while growing and when taking into account storage that is only needed temporarily. None of the traditionally used hash tables have this property. We show how known approaches like linear probing and bucket cuckoo hashing can be adapted to this scenario by subdividing them into many subtables or using virtual memory overcommitting. However, these rather straightforward solutions suffer from slow amortized insertion times due to frequent reallocation in small increments. Our main result is DySECT ({\bf Dy}namic {\bf S}pace {\bf E}fficient {\bf C}uckoo {\bf T}able) which avoids these problems. DySECT consists of many subtables which grow by doubling their size. The resulting inhomogeneity in subtable sizes is equalized by the flexibility available in bucket cuckoo hashing where each element can go to several buckets each of which containing several cells. Experiments indicate that DySECT works well with load factors up to 98\%. With up to 2.7 times better performance than the next best solution.

arXiv comments
14 pages, 11 figures
Journal reference
DOI
Subjects
cs.DSData Structures and Algorithms

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    • If you're interested in truly space-efficient hash tables—as in "at every point in time, at least 97% of the space of the table is used for elements"—check out this paper by a colleague of mine: https://arxiv.org/pdf/1705.00997.pdf (the relevant plots are on pages 10 and 11).…

      lorenzhsView on HNParent context

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