Title :
Scaling deep social feeds at Pinterest
Author :
Sharma, Vishal ; Carroll, John ; Khune, Abhi
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;
Conference_Titel :
Big Data, 2013 IEEE International Conference on
Conference_Location :
Silicon Valley, CA
DOI :
10.1109/BigData.2013.6691652