Fractal Prefetching B+-Trees: Optimizing Both Cache and Disk Performance

B+-Trees have been traditionally optimized for I/O performance with disk pages as tree nodes. Recently, researchers have proposed new types of B+-Trees optimized for CPU cache performance in main memory environments, where the tree node sizes are one or a few cache lines. Unfortunately, due primarily to this large discrepancy in optimal node sizes, existing disk-optimized B+-Trees suffer from poor cache performance while cache-optimized B+-Trees exhibit poor disk performance. In this paper, we propose fractal prefetching -Trees), which embed "cache-optimized" trees within "disk-optimized" trees, in order to optimize both cache and I/O performance. We design and evaluate two approaches to breaking disk pages into cache-optimized nodes: disk-first and cache-first. These approaches are somewhat biased in favor of maximizing disk and cache performance, respectively, as demonstrated by our results. Both implementations of fpB+-Trees achieve dramatically better cache performance than disk-optimized B+-Trees: a factor of 1.1-1.8 improvement for search, up to a factor of 4.2 improvement for range scans, and up to a 20-fold improvement for updates, all without significant degradation of I/O performance. In addition, fpB+-Trees accelerate I/O performance for range scans by using jump-pointer arrays to prefetch leaf pages, thereby achieving a speed-up of 2.5-5 on IBM's DB2 Universal Database