Lightweight Robust Size Aware Cache Management

Gil Einziger, Ohad Eytan, Roy Friedman, Benjamin Manes

Research output: Working paper/PreprintPreprint

53 Downloads (Pure)

Abstract

Modern key-value stores, object stores, Internet proxy caches, as well as Content Delivery Networks (CDN) often manage objects of diverse sizes, e.g., blobs, video files of different lengths, images with varying resolution, and small documents. In such workloads, size-aware cache policies outperform size-oblivious algorithms. Unfortunately, existing size-aware algorithms tend to be overly complicated and computationally~expensive. Our work follows a more approachable pattern; we extend the prevalent (size-oblivious) TinyLFU cache admission policy to handle variable sized items. Implementing our approach inside two popular caching libraries only requires minor changes. We show that our algorithms yield competitive or better hit-ratios and byte hit-ratios compared to the state of the art size-aware algorithms such as AdaptSize, LHD, LRB, and GDSF. Further, a runtime comparison indicates that our implementation is faster by up to x3 compared to the best alternative, i.e., it imposes much lower CPU overhead.
Original languageEnglish GB
StatePublished - 18 May 2021

Publication series

Namearxiv cs.OS

Keywords

  • cs.OS
  • cs.DB

Fingerprint

Dive into the research topics of 'Lightweight Robust Size Aware Cache Management'. Together they form a unique fingerprint.

Cite this