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{
eventType: PageViewEvent,
3mestamp: 1413215518,
viewerId: 1234,
sessionId: fa1afe101234deadbeef,
pageKey: profile-view,
viewedProfileId: 4321,
trackingKey: invita3on-email,
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{
eventType: PageViewEvent,
3mestamp: 1413215518,
viewerId: 1234,
sessionId: fa1afe101234deadbeef,
pageKey: profile-view,
viewedProfileId: 4321,
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... etc. metadata about what content was displayed...
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{
eventType: ProfileEditEvent,
3mestamp: 1413215518,
profileId: 1234,
old: {
loca3on: "London, UK",
industry: "Financial Services"},
new: {
loca3on: "Budapest, Hungary",
industry: "SoTware"}
}
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https://github.com/ept/newsfeed
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References
1. Apache Samza documentation. http://samza.apache.org
2. Tyler Akidau, Robert Bradshaw, Craig Chambers, et al.: “The Dataflow Model: A Practical Approach to Balancing
Correctness, Latency, and Cost in Massive-Scale, Unbounded, Out-of-Order Data Processing,” Proceedings of the VLDB
Endowment, volume 8, number 12, pages 1792–1803, August 2015. http://www.vldb.org/pvldb/vol8/p1792-Akidau.pdf
3. Shirshanka Das, Chavdar Botev, Kapil Surlaker, et al.: “All Aboard the Databus!,” at ACM Symposium on Cloud
Computing (SoCC), October 2012. http://www.socc2012.org/s18-das.pdf
4. Nathan Marz and James Warren: “Big Data: Principles and best practices of scalable realtime data systems.” Manning,
April 2015, ISBN 9781617290343. http://manning.com/marz/
5. Martin Kleppmann: “Designing data-intensive applications.” O’Reilly Media, to appear. http://dataintensive.net
6. Martin Kleppmann: “Moving faster with data streams: The rise of Samza at LinkedIn.” 14 July 2014. http://
engineering.linkedin.com/stream-processing/moving-faster-data-streams-rise-samza-linkedin
7. Jay Kreps: “Why local state is a fundamental primitive in stream processing.” 31 July 2014. http://radar.oreilly.com/
2014/07/why-local-state-is-a-fundamental-primitive-in-stream-processing.html
8. Jay Kreps: “I ♥︎ Logs.” O'Reilly Media, September 2014. http://shop.oreilly.com/product/0636920034339.do
9. Praveen Neppalli Naga: “Real-time Analytics at Massive Scale with Pinot.” 29 Sept 2014. http://
engineering.linkedin.com/analytics/real-time-analytics-massive-scale-pinot
10. Lili Wu, Sam Shah, Sean Choi, Mitul Tiwari, and Christian Posse: “The Browsemaps: Collaborative Filtering at LinkedIn,”
at 6th Workshop on Recommender Systems and the Social Web, Oct 2014. http://ls13-www.cs.uni-dortmund.de/
homepage/rsweb2014/papers/rsweb2014_submission_3.pdf
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