Scaling column imprints using advanced vectorization

Abstract

Column Imprints is a pre-filtering secondary index for answering range queries. The main feature of imprints is that they are light-weight and are based on compressed bit-vectors, one per cacheline, that quickly determine if the values in that cacheline satisfy the predicates of a query. The main overhead of the imprints implementation is the many sequential value comparisons against the boundaries of a virtual equi-height histogram. Similarly, during query scans, many sequential value comparisons are performed to identify false positives. In this paper, we speed-up the process of imprints creation and querying by using advanced vectorization techniques. We also experimentally explore the benefits of stretching imprints to larger bit-vector sizes and blocks of data, using 256-bit SIMD registers. Our findings are very promising for both imprints and for future index design research that would employ advanced vectorization techniques and larger (up to 512-bit) and more (from 16 now to 32) SIMD registers.