MySQL in eBay's Personalization Platform
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MySQL in eBay's Personalization Platform

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    MySQL in eBay's Personalization Platform MySQL in eBay's Personalization Platform Presentation Transcript

    • MySQL in eBay’s Personalization Platform
      • Chris Kasten eBay Kernel Framework Group April 16, 2008
    • Outline
      • Background
      • General Vision
      • General Requirements
      • Why MySQL Memory Engine?
      • System Overview
      • Results
    • Fun Facts About eBay
      • 110 Million items for sale on the site
      • $59 Billion in gross merchandize value (GMV) per year
      • Approx $2,039 worth of goods traded on the site every second
      • 276 Million registered users
      • 2 Billion URL requests per day
      • 6,000 application servers with 12,000 Java processes
      • 40 Billion database requests per day
      • 300 different databases (over 700 instances)
      • 9 PB of data storage
      • 13 million lines of source code (In 2008 will surpass Windows NT 4.0 O/S 16 million lines)
    • Background
      • Further distinguish the eBay shopping experience
        • Provide a more relevant and even better user experience
        • Provide users with a more rich experience with greater continuity
        • Provide users with the best selection tailored to their interests/profile
        • Provide better user experience through real time personalization data feedback loop that is immediately available
        • Provide users with tailored alternatives
      • Further distinguish the eBay business value proposition
        • Advertising shown to more relevant buyers
        • More effective merchandizing and marketing of items
        • Increase conversion rates through better buyer experience and greater relevancy of items presented to the buyer
    • Background
      • eBay needed to expand its real time personalization capabilities
      • eBay needed to be able to associate more data with sessions
      • Both personalization and session data were constrained by technology
        • Cookies limitation
          • Client side cookie limit of 4KB data
          • Long term scalability issue of sending all cookie data, whether needed or not
        • High cost of traditional server side solutions using an OLTP database
          • eBay’s very large scale quickly multiplies costs in to a very large number
          • Throughput of OLTP’s decrease with high write ratio of approximately 50%
          • Large number of licenses/servers needed for throughput was cost prohibitive
        • High cost of other commercial alternatives at eBay’s very large scale
      • These constraints were limiting business decisions and had to be solved
    • General Vision Every Application Server Can Access Data For Every URL Request (All 2 Billion of them!) Session Data Personalization Data
    • General Requirements
      • Handle 4 Billion reads/writes per day
      • Support connections and requests from 12,000 Java processes
      • High throughput on low cost hardware
      • Scale both horizontally and vertically for 10x future growth
      • Scale without operational interruption
      • High availability and operational failure robustness
      • Low latency response times
      • Low licensing, support, and total cost of ownership costs
      • Enterprise class support agreement
      • Enterprise class management and monitoring tools
      • Driver for Java
    • Why MySQL Memory Engine?
      • MySQL Memory Engine had the best performance
      • Very impressive POC results for MySQL Memory Engine
        • Approx 2X more throughput than nearest competitor (Java driver)
        • eBay test case of 50/50 read/writes showed approx 13,000 TPS @ 50% CPU for a Sun 4100 running Solaris 10 x86 (2 CPU, Dual Core Opteron, 16GB RAM) for a network client
        • Handled 20,000 concurrent connections with less than 1% degradation in throughput than baseline case (eBay developed patch)
      • Production performance has been consistent with POC results
    • Why MySQL Memory Engine?
      • MySQL Enterprise had a very attractive cost structure
      • MySQL’s ability to offer enterprise class support
      • MySQL’s combined throughput and cost structure provided a low cost system for the scale of eBay
      • Power and flexibility of using SQL for different needs
      • A company with a significant track record
    • Why MySQL Memory Engine?
      • The power of open source
        • eBay has developed and contributed two enhancements to MySQL
          • Support for an event port based threading and connection handling model for scalable connection handling
          • Support for true variable size columns in MySQL Memory Engine
        • Option to be able to apply our talent and create the enhancements we need quickly
        • Receive the benefits of innovations of others via open source
    • Why MySQL Memory Engine?
      • The power of an open source company behind the product
        • Ability to collaborate with MySQL on enhancements to the product
        • Option to request enhancements from a company behind the product
        • Out of the box monitoring and administration tools
        • Eliminate tying up high end eBay talent in owning it ourselves
        • An enterprise class open source product
        • Enterprise class support offerings for use in critical systems
    • eBay Personalization System Overview MySQL Memory Engine Cache Tier Application Servers Browser Persistent Database
    • eBay Personalization System Overview Replication MySQL Memory Engine Cache Tier Application Servers Persistent Database 5 min Batched Write Back Read/Write Cache Miss Read
    • eBay Personalization System Overview
      • Replication optional based on criticality of data loss for past 5 min
        • Trade-off between data criticality versus double the memory cost
        • Some personalization data may not be critical enough for the additional hardware cost
      • Single threaded MySQL replication is generally problematic
        • Once replication falls behind it stays behind with continued traffic
        • Replication can be achieved via dual writes from the application server performed transparently by the framework
        • Second write to replica can be asynchronous
      • Automatic redistribution of data when node failure or draining a node
    • eBay Personalization System Overview
      • Write back to persistent database performed by batch process
      • Evictions performed by batch process based on target free memory
      • Buffering space is set aside in case persistent database is unavailable
      • Special techniques used to minimize table lock duration during write back and eviction operations
    • Results
      • A business critical system running on MySQL Enterprise for one of the largest scale websites in the world
      • Highly scalable and low cost system that handles all of eBay’s personalization and session data needs
      • Ability to handle 4 billion requests per day of 50/50 read/write operations for approximately 40KB of data per user / session
      • Approx 25 Sun 4100’s running 100% of eBay’s personalization and session data service (2 CPU, Dual core Opteron, 16 GB RAM, Solaris 10 x86)
    • Results
      • Highly manageable system for entire operational life cycle
      • Leveraging MySQL Dashboard as a critical tool in providing insight into system performance, trending, and identifying issues
      • Adding new applications to ebay.com domain that previously would have been in a different domain because of cookie constraints
      • Creating several new business opportunities that would not have been possible without this new low cost personalization platform
      • Leveraging MySQL Memory Engine for other types of caching tiers that are enabling new business opportunities
    • Q & A
      • Thank you for coming!
      • Questions?