Skip to main content
USENIX
  • Conferences
  • Students
Sign in
  • Home
  • Attend
    • Registration Information
    • Registration Discounts
    • Venue, Hotel, and Travel
    • Students and Grants
  • Program
    • At a Glance
    • Technical Sessions
    • Training Program
    • Poster Sessions
    • WiPs
  • Activities
    • Birds-of-a-Feather Sessions
    • Poster Sessions
  • Sponsorship
  • Participate
    • Call for Papers
    • Call for Posters and WiPs
    • Instructions for Participants
  • About
    • Conference Organizers
    • Questions
    • Services
    • Help Promote!
    • Past Conferences
  • Home
  • Attend
  • Program
  • Activities
  • Sponsorship
  • Participate
  • About

sponsors

Platinum Sponsor
Gold Sponsor
Gold Sponsor
Gold Sponsor
Gold Sponsor
Silver Sponsor
Silver Sponsor
Silver Sponsor
Silver Sponsor
Silver Sponsor
Bronze Sponsor
Bronze Sponsor
Bronze Sponsor
Bronze Sponsor
Bronze Sponsor
Media Sponsor
Media Sponsor
Media Sponsor
Media Sponsor
Media Sponsor
Media Sponsor
Media Sponsor
Media Sponsor
Industry Partner
Industry Partner

help promote

FAST '17 CFP

Get
Help Promote graphics!

connect with us


  •  Twitter
  •  Facebook
  •  LinkedIn
  •  Google+
  •  YouTube

twitter

Tweets by @usenix

usenix conference policies

  • Event Code of Conduct
  • Conference Network Policy
  • Statement on Environmental Responsibility Policy

You are here

Home » Towards Accurate and Fast Evaluation of Multi-Stage Log-structured Designs
Tweet

connect with us

Towards Accurate and Fast Evaluation of Multi-Stage Log-structured Designs

Authors: 

Hyeontaek Lim and David G. Andersen, Carnegie Mellon University; Michael Kaminsky, Intel Labs

Abstract: 

Multi-stage log-structured (MSLS) designs, such as LevelDB, RocksDB, HBase, and Cassandra, are a family of storage system designs that exploit the high sequential write speeds of hard disks and flash drives by using multiple append-only data structures. As a first step towards accurate and fast evaluation of MSLS, we propose new analytic primitives and MSLS design models that quickly give accurate performance estimates. Our model can almost perfectly estimate the cost of inserts in LevelDB, whereas the conventional worst-case analysis gives 1.8–3.5x higher estimates than the actual cost. A few minutes of offline analysis using our model can find optimized system parameters that decrease LevelDB’s insert cost by up to 9.4–26.2%; our analytic primitives and model also suggest changes to RocksDB that reduce its insert cost by up to 32.0%, without reducing query performance or requiring extra memory.

Hyeontaek Lim, Carnegie Mellon University

David G. Andersen, Carnegie Mellon University

Michael Kaminsky, Intel Labs

Open Access Media

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are posted after the event are also free and open to everyone. Support USENIX and our commitment to Open Access.

BibTeX
@inproceedings {194426,
author = {Hyeontaek Lim and David G. Andersen and Michael Kaminsky},
title = {Towards Accurate and Fast Evaluation of {Multi-Stage} Log-structured Designs},
booktitle = {14th USENIX Conference on File and Storage Technologies (FAST 16)},
year = {2016},
isbn = {978-1-931971-28-7},
address = {Santa Clara, CA},
pages = {149--166},
url = {https://www.usenix.org/conference/fast16/technical-sessions/presentation/lim},
publisher = {USENIX Association},
month = feb,
}
Download
Lim PDF
View the slides

Presentation Audio

MP3 Download

Download Audio

  • Log in or    Register to post comments

Platinum Sponsors

Gold Sponsors

Silver Sponsors

Bronze Sponsors

Media Sponsors & Industry Partners

Open Access Publishing Partner

© USENIX

  • Privacy Policy
  • Contact Us