• DocumentCode
    659503
  • Title

    Scaling deep social feeds at Pinterest

  • Author

    Sharma, Vishal ; Carroll, John ; Khune, Abhi

  • fYear
    2013
  • fDate
    6-9 Oct. 2013
  • Firstpage
    777
  • Lastpage
    783
  • Abstract
    With the advent of Twitter, the follow model has become pervasive across social networks. The follow model enables users to follow other users i.e. subscribe to content created by other users, thereby, establishing the concept of a following feed for a user. At Pinterest, we continually store, update and serve feeds for millions of users and fan out millions of newly created pins/repins to thousands of followers, leading to billions of operations everyday. We describe the current feed storage solution, backed by Apache HBase, at Pinterest. We describe how we handle data management challenges unique to our scale, in the wake of strict performance and availability requirements. We also present a qualitative comparison to our previous ”following feed” architecture, backed by Redis.
  • Keywords
    data handling; relational databases; social networking (online); storage management; Apache HBase; Pinterest; Twitter; availability requirements; data management challenges; feed storage solution; follow model; following feed architecture; performance requirements; social feeds scaling; social networks; Availability; Databases; Feeds; Pins; Servers; Sockets; Throughput;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data, 2013 IEEE International Conference on
  • Conference_Location
    Silicon Valley, CA
  • Type

    conf

  • DOI
    10.1109/BigData.2013.6691652
  • Filename
    6691652