Apéndice A. Referencias de la Parte I

  • [Armbrust2018] Armbrust, M., T. Das, J. Torres, B. Yavuz, S. Zhu, R. Xin, A. Ghodsi, I. Stoica y M. Zaharia. "Streaming estructurado: A Declarative API for Real-Time Applications in Apache Spark", 27 de mayo de 2018. https://stanford.io/2Jia3iY.

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

  • [Chambers2018] Chambers, B., y Zaharia, M., Spark: La Guía Definitiva. O'Reilly, 2018.

  • [Chintapalli2015] Chintapalli, S., D. Dagit, B. Evans, R. Farivar, T. Graves, M. Holderbaugh, Z. Liu, K. Musbaum, K. Patil, B. Peng y P. Poulosky. "Benchmarking Streaming Computation Engines at Yahoo!" (Evaluación comparativa de motores de computación en flujo en Yahoo!). Yahoo! Engineering, 18 de diciembre de 2015. http://bit.ly/2bhgMJd.

  • [Das2013] Das, Tathagata. "Deep Dive With Spark Streaming," Spark meetup, 17 de junio de 2013. http://bit.ly/2Q8Xzem.

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

  • [Das2015] Das, Tathagata. "Tolerancia mejorada a fallos y pérdida cero de datos en Spark Streaming", blog Databricks Engineering. 15 de enero de 2015. http://bit.ly/2HqH614.

  • [Dean2004] Dean, Jeff, y Sanjay Ghemawat. "MapReduce: Simplified Data Processing on Large Clusters", OSDI San Francisco, diciembre de 2004. http://bit.ly/15LeQej ...

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