Conditional Cuckoo Filters

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Abstract

Bloom filters, cuckoo filters, and other approximate set membership sketches have a wide range of applications. Oftentimes, expensive operations can be skipped if an item is not in a data set. These filters provide an inexpensive, memory efficient way to test if an item is in a set and avoid unnecessary operations. Existing sketches only allow membership testing for a single set. However, in some applications such as join processing, the relevant set is not fixed and is determined by a set of predicates. We propose the Conditional Cuckoo Filter, a simple modification of the cuckoo filter that allows for set membership testing given predicates on a pre-computed sketch. This filter also introduces a novel chaining technique that enables cuckoo filters to handle insertion of duplicate keys. We evaluate our methods on a join processing application and show that they significantly reduce the number of tuples that a join must process.

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APA

Ting, D., & Cole, R. (2021). Conditional Cuckoo Filters. In Proceedings of the ACM SIGMOD International Conference on Management of Data (pp. 1838–1850). Association for Computing Machinery. https://doi.org/10.1145/3448016.3452811

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