Cardinality estimation and dynamic length adaptation for Bloom filters

Abstract Bloom filters are extensively used in distributed applications, especially in distributed databases and distributed information systems, to reduce network requirements and to increase performance. In this work, we propose two novel Bloom filter features that are important for distributed databases and information systems. First, we present a new approach to encode a Bloom filter such that its length can be adapted to the cardinality of the set it represents, with negligible overhead with respect to computation and false positive probability. The proposed encoding allows for significant network savings in distributed databases, as it enables the participating nodes to optimize the length of each Bloom filter before sending it over the network, for example, when executing Bloom joins. Second, we show how to estimate the number of distinct elements in a Bloom filter, for situations where the represented set is not materialized. These situations frequently arise in distributed dat...

• Type: Journal
• Year: 2010
• Where: DPD
• Authors: Odysseas Papapetrou, Wolf Siberski, Wolfgang Nejdl
• Keywords: Bloom Filter, Databases, DPD 2010, Information Systems, Information Technology