Appendix A. References for Part I

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  • [Bhartia2016] Bhartia, R. “Optimize Spark-Streaming to Efficiently Process Amazon Kinesis Streams,” AWS Big Data blog, February 26, 2016. https://amzn.to/2E7I69h.

  • [Chambers2018] Chambers, B., and Zaharia, M., Spark: The Definitive Guide. O’Reilly, 2018.

  • [Chintapalli2015] Chintapalli, S., D. Dagit, B. Evans, R. Farivar, T. Graves, M. Holderbaugh, Z. Liu, K. Musbaum, K. Patil, B. Peng, and P. Poulosky. “Benchmarking Streaming Computation Engines at Yahoo!” Yahoo! Engineering, December 18, 2015. http://bit.ly/2bhgMJd.

  • [Das2013] Das, Tathagata. “Deep Dive With Spark Streaming,” Spark meetup, June 17, 2013. http://bit.ly/2Q8Xzem.

  • [Das2014] Das, Tathagata, and Yuan Zhong. “Adaptive Stream Processing Using Dynamic Batch Sizing,” 2014 ACM Symposium on Cloud Computing. http://bit.ly/2WTOuby.

  • [Das2015] Das, Tathagata. “Improved Fault Tolerance and Zero Data Loss in Spark Streaming,” Databricks Engineering blog. January 15, 2015. http://bit.ly/2HqH614.

  • [Dean2004] Dean, Jeff, and Sanjay Ghemawat. “MapReduce: Simplified Data Processing on Large Clusters,” OSDI San Francisco, December, 2004. http://bit.ly/15LeQej.

  • [Doley1987] Doley, D., C. Dwork, and L. Stockmeyer. “On the ...

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