We introduce Rosetta, a probabilistic range filter designed specifically for LSM-tree based
key-value stores. The core intuition is that we can sacrifice filter probe time because it is not …

We present Sparse Numerical Array-Based Range Filters (SNARF), a learned range filter
that efficiently supports range queries for numerical data. SNARF creates a model of the …

A range filter is a data structure to answer range membership queries. Range queries are
common in modern applications, and range filters have gained rising attention for improving …

Filter data structures have been used ubiquitously since the 1970s to answer approximate
set-membership queries in various areas of computer science including architecture …

The learning-enhanced data structure has inspired the development of the range filter,
bringing significantly better false positive rate (FPR) than traditional non-learned range …

Mobile radio frequency identification (RFID) systems typically experience the continual
movement of many tags rapidly going in and out of the interrogating range of readers …

Radio frequency identification (RFID) has been widely used in many fields such as object
tracking and inventory management. For RFID systems, grouping is a fundamental issue …

Range filters allow checking whether a query range intersects a given set of keys with a
chance of returning a false positive answer, thus generalising the functionality of Bloom …

Membership testing is the problem of testing whether an element is in a set of elements.
Performing the test exactly is expensive space-wise, requiring the storage of all elements in …

A range filter is a data structure to answer range membership queries. Range queries are
common in modern applications, and range filters have gained rising attention for improving …