STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Answering queries using views: A survey
The VLDB Journal — The International Journal on Very Large Data Bases
The many faces of publish/subscribe
ACM Computing Surveys (CSUR)
Feeding frenzy: selectively materializing users' event feeds
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
The little engine(s) that could: scaling online social networks
Proceedings of the ACM SIGCOMM 2010 conference
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Social networking systems present users with online event streams that include recent activities of their friends. Materialized per-user views are a common way to generate such event streams on-line and with low latency. We propose improving throughput by using social piggybacking: process the requests of two friends by just querying and updating the view of a third common friend. By using one such hub view, the system can serve requests of the first friend without querying nor updating the view of the second. This reduces the overall load on views, and can be implemented with minimal adaptations by existing social networking architectures. We show that, given a social graph, there exist hub-based schedules that minimize the overall number of view requests, but computing them is NP-hard. We propose a heuristic to solve the problem and evaluate it using samples from the Twitter and Flickr social graphs. The evaluation shows that existing solutions generate up to 2.4 times the amount of view requests induced by our heuristic.