Optimizing Quotient Filters using Graveyard Hashing

TL;DR

This paper introduces the Graveyard Filter, a variation of the Quotient Filter that uses tombstones to reduce clustering and improve performance at high load factors, with promising experimental results.

Contribution

It presents a novel Graveyard Hashing technique for quotient filters, including implementation details and redistribution strategies to enhance performance under high load conditions.

Findings

Competitive insertion and query performance at high load factors

Certain redistribution schemes outperform others

Potential for adaptive load-based redistribution strategies

Abstract

We aim to improve the performance of the Quotient Filter at high load factors. Our Graveyard Filter is a variation of the Quotient Filter which incorporates Graveyard Hashing, a technique that uses tombstones to counteract the effects of primary clustering. We summarize our implementation of the graveyard filter and detail approaches to redistributing tombstones. Evaluating these variations under conditions similar to the original quotient filter paper, we found the performance of the graveyard filter to be competitive for insertion and query operations, with certain redistribution schemes showing stronger performance at high load factors. We discuss potential further improvements, such as using the current load factor to determine the employed redistribution approach.