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An introduction to SphinxSearch by Adrian Schneider for presenting at OKDG

An introduction to SphinxSearch by Adrian Schneider for presenting at OKDG

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    Sphinx Intro Sphinx Intro Presentation Transcript

    • About Me
      • Adrian Schneider – siradrian.com
      • PHP Developer
      • Online Community Consultant
      • @AdrianSchneider
    • Searching Web Content
      • A web application needs to be able to effectively search its content.
      • Measures:
        • Relevance and Efficiency
      • Affected by:
        • Document Count and Traffic
    • Searching Web Content ...
      • How do we effectively handle searching?
    • Common Solutions
      • Database Engine
        • Ex: MySQL FULLTEXT
      • Native Filesystem Search Engine
        • Ex: Lucene (ZF, Apache)
      • Web Crawler
        • Ex: Google Site Search
    • Enter Sphinx Search
      • How is Sphinx different?
      • Open Source
      • Much Faster
      • Scales
      • Integrates
    • Sites using Sphinx
      • boardreader.com – 2 billion docs / 2TB
      • craigslist.org – 575q/s
      • Honorable Mentions:
        • MySQL.com
        • Joomla.org
        • Many Torrent Sites
    • Indexing
      • Data Sources:
        • SQL Query
        • XML Data
      • Incremental Indexing
        • Less redundancy
        • Light on server
    • Searching: SphinxQL
      • Sphinx listens for MySQL connections
      • PHP connects to Sphinx like it would MySQL
    • Searching: SphinxSE
      • MySQL Storage Engine
      • Acts as Table – JOINS!
      • Req. patching MySQL
    • Searching: Client Libraries
      • Client libraries also exist for most languages.
      • CLI for Testing
    • More Features
      • Most features you'd expect...
      • Encoding (UTF support)
      • English and Russian Stemming
      • Boolean, phrase, proximity queries
      • Excellent Relevance
    • How it Works
      • Create indexes using data sources
      • Index contains different “attributes”
      • Attributes act similar to database indexes
        • WHERE, GROUP BY, ORDER BY
      • Attributes can be:
        • Numbers
        • Timestamps
        • Strings (recent)
    • Hidden Gem: Full Scans
      • Good for huge data sets
      • Much faster than a database engine
      • Good for reports / stats and browsing
    • My Gripes
      • Global Document Identifiers
      • 1000 Max Matches (before limit)
        • Configurable
        • Google returns 1000 only!
    • Summary
      • Takes a bit of work to set up
      • Very fast search solution that will scale well
      • Open source code
      • Development is still active
    • Questions
      • This is where you wake up and pretend you were listening ^.^