DocumentCode :
660752
Title :
Scaling Deep Social Feeds at Pinterest
Author :
Sharma, Vishal ; Carroll, John ; Khune, Abhi
fYear :
2013
fDate :
8-14 Sept. 2013
Firstpage :
7
Lastpage :
12
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 :
SQL; content management; social networking (online); storage management; Apache HBase; Pinterest; Redis; Twitter; availability requirements; content subscription; data management; deep social feed scaling; feed storage solution; follow model; following feed architecture; performance requirements; pin creation; repin; social networks; user feed following; Availability; Compaction; Databases; Feeds; Pins; Servers; Throughput;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Social Computing (SocialCom), 2013 International Conference on
Conference_Location :
Alexandria, VA
Type :
conf
DOI :
10.1109/SocialCom.2013.7
Filename :
6693304
Link To Document :
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