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References (fun stuff to read)
1. Jay Kreps: “I ♥︎ Logs.” O'Reilly Media, September 2014. http://shop.oreilly.com/product/0636920034339.do
2. 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
3. Martin Kleppmann: “Designing data-intensive applications.” O’Reilly Media, to appear in 2015. http://dataintensive.net
4. Martin Kleppmann: “Rethinking caching in web apps.” 1 October 2012. http://martin.kleppmann.com/2012/10/01/
rethinking-caching-in-web-apps.html
5. 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
6. Nathan Marz and James Warren: “Big Data: Principles and best practices of scalable realtime data systems.” Manning
MEAP, to appear January 2015. http://manning.com/marz/
7. 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
8. Mahesh Balakrishnan, Dahlia Malkhi, Ted Wobber, et al.: “Tango: Distributed Data Structures over a Shared Log,” at
24th ACM Symposium on Operating Systems Principles (SOSP), pages 325–340, November 2013. http://
research.microsoft.com/pubs/199947/Tango.pdf
9. Roshan Sumbaly, Jay Kreps, and Sam Shah: “The ‘Big Data’ Ecosystem at LinkedIn,” at ACM International Conference
on Management of Data (SIGMOD), July 2013. http://www.slideshare.net/s_shah/the-big-data-ecosystem-at-
linkedin-23512853
10. Apache Samza documentation. http://samza.incubator.apache.org
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