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A Case for Partitioned Bloom Filters
[article]
2020
arXiv
pre-print
In a partitioned Bloom Filter the m bit vector is split into k disjoint m/k sized parts, one per hash function. Contrary to hardware designs, where they prevail, software implementations mostly adopt standard Bloom filters, considering partitioned filters slightly worse, due to the slightly larger false positive rate (FPR). In this paper, by performing an in-depth analysis, first we show that the FPR advantage of standard Bloom filters is smaller than thought; more importantly, by studying the
arXiv:2009.11789v1
fatcat:x2gwrrjzxfgldkzgt7bs2g6mju