Open access
Date
2012-11Type
- Report
ETH Bibliography
yes
Altmetrics
Abstract
The architectural changes introduced with multicore CPUs have triggered a redesign of main-memory join algorithms. In the last few years, two diverging views have appeared. One approach advocates careful tailoring of the algorithm to the architectural parameters (cache sizes, TLB, and memory bandwidth). The other approach argues that modern hardware is good enough at hiding cache and TLB miss latencies and, consequently, the careful tailoring can be omitted without sacrificing performance. In this paper we demonstrate through experimental analysis of different algorithms and architectures that hardware still matters. Join algorithms that are hardware conscious perform better than hardware-oblivious approaches. The analysis and comparisons in the paper show that many of the claims regarding the behavior of join algorithms that have appeared in literature are due to selection effects (relative table sizes, tuple sizes, the underlying architecture, using sorted data, etc.) and are not supported by experiments run under different parameters settings. Through the analysis, we shed light on how modern hardware affects the implementation of data operators and provide the fastest implementation of radix join to date, reaching close to 200 million tuples per second. Show more
Permanent link
https://doi.org/10.3929/ethz-a-007587151Publication status
publishedJournal / series
Technical Report / ETH Zurich, Department of Computer ScienceVolume
Publisher
ETH ZurichSubject
MULTIPLE DATA STREAM ARCHITECTURES + MULTIPROCESSORS (COMPUTER SYSTEMS); MULTIPLE-DATA-STREAM-ARCHITEKTUREN + MULTIPROZESSOREN (COMPUTERSYSTEME); SPEICHERORGANISATION + SPEICHERVERWALTUNG (BETRIEBSSYSTEME); STORAGE MANAGEMENT + MEMORY MANAGEMENT (OPERATING SYSTEMS)Organisational unit
02150 - Dep. Informatik / Dep. of Computer Science03506 - Alonso, Gustavo / Alonso, Gustavo
More
Show all metadata
ETH Bibliography
yes
Altmetrics