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Author Putze, Felix ♦ Sanders, Peter ♦ Singler, Johannes
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2009
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Computer programming, programs & data
Subject Keyword Approximate dictionary ♦ Data compression
Abstract A Bloom filter is a very compact data structure that supports approximate membership queries on a set, allowing false positives. We propose several new variants of Bloom filters and replacements with similar functionality. All of them have a better cache-efficiency and need less hash bits than regular Bloom filters. Some use SIMD functionality, while the others provide an even better space efficiency. As a consequence, we get a more flexible trade-off between false-positive rate, space-efficiency, cache-efficiency, hash-efficiency, and computational effort. We analyze the efficiency of Bloom filters and the proposed replacements in detail, in terms of the false-positive rate, the number of expected cache-misses, and the number of required hash bits. We also describe and experimentally evaluate the performance of highly tuned implementations. For many settings, our alternatives perform better than the methods proposed so far.
ISSN 10846654
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2010-01-05
Publisher Place New York
e-ISSN 10846654
Journal Journal of Experimental Algorithmics (JEA)
Volume Number 14
Page Count 15
Starting Page 4.4
Ending Page 4.18


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Source: ACM Digital Library