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Scaleable Structured Datastorage for Web 2.0

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Title: X-Trace: A Network Tracing Framework Author: rfonseca Last modified by: David Created Date: 11/7/2006 3:51:18 AM Document presentation format – PowerPoint PPT presentation

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Title: Scaleable Structured Datastorage for Web 2.0


1
Scaleable Structured Datastorage for Web 2.0
  • Michael Armbrust, David Patterson October, 2007

2
RAD Lab 5-year Mission
  • Todays Internet systems complex, fragile,
    manually managed, rapidly evolving
  • To scale Ebay, must build Ebay-sized company
  • Moon shot mission statement
  • Enable a single person to Develop, Assess,
    Deploy, and Operate the next-generation IT
    service
  • The Fortune 1 Million by enabling rapid
    innovation
  • Create core technology to enable vision via
    synergy across systems, networking, and
    Statisical Machine Learning
  • Making datacenter easier to manage enables vision
    of single person to analyze, deploy and operate a
    scalable IT service

3
If Datacenter is the computer
  • What is the programming language?
  • What are the libraries?
  • How do trace/monitor programs?
  • What is the simulator?
  • What is Computer Aided Design?
  • What is the Operating System?
  • What is the Database System?

4
Storage Status Quo
  • Current status of data storage for Web 2.0 apps
  • Large relational databases running on expensive
    hardware
  • Manual horizontal and vertical partitioning of
    data
  • Problem Requires redesign at each scaling
    milestone
  • Goal Scaleable structured data storage for Web
    2.0

5
Web 2.0 App Characteristics
  • Need to scale to YouTube or MySpace sizes
  • Require geographic replication
  • Short transactions
  • No ad-hoc queries
  • Willing to trade relaxed consistency for
    scalability and availability
  • Photos, not financials

6
Relaxed Consistency
  • Some things can be updated lazily
  • Eventual consistency is often acceptable
  • However users should see their own writes
    immediately
  • Need to provide simple choices to developers

7
Our Idea
  • Large scale distributed database underneath
  • Runs on 1000 of shared nothing commodity servers
  • ActiveRecord-like layer in Ruby on Rails vs. SQL
  • Provides simple relationships and consistency
    guarantees between models
  • has_many
  • belongs_to
  • searchable_by (for full-text search)
  • Pre-compute joins for quick reads

8
Related Work (we know of)
  • G. DeCandia, D. Hastorun, et al. Dynamo Amazons
    highly available key-value store. In SOSP. 2007.
    5 M. Stonebraker and U. Cetintemel. one size
    fits all an idea whose time has come and gone.
    pp. 211. 2005.
  • M. Stonebraker, S. R. Madden, et al. The end of
    an architectural era (its time for a complete
    rewrite). In VLDB. Vienna, Austria, 2007.
  • D. J. Abadi, A. Marcus, S. R. Madden, and K.
    Hollenbach. Scalable semantic web data management
    using vertical partitioning. In VLDB, Vienna,
    Austria, 2007.
  • F. Chang, J. Dean, S. Ghemawat, W. C. Hsieh, D.
    A. Wallach, M. Burrows, T. Chandra, A. Fikes, and
    R. E. Gruber. Bigtable A distributed storage
    system for structured data. In OSDI?06 Seventh
    Symposium on Operating System Design and
    Implementation, November 2006.
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