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Designing Data-Intensive Applications

Chapter 12 References

  1. Rachid Belaid: “Postgres Full-Text Search is Good Enough!,” rachbelaid.com, July 13, 2015.

  2. Philippe Ajoux, Nathan Bronson, Sanjeev Kumar, et al.: “Challenges to Adopting Stronger Consistency at Scale,” at 15th USENIX Workshop on Hot Topics in Operating Systems (HotOS), May 2015.

  3. Pat Helland and Dave Campbell: “Building on Quicksand,” at 4th Biennial Conference on Innovative Data Systems Research (CIDR), January 2009.

  4. Jessica Kerr: “Provenance and Causality in Distributed Systems,” blog.jessitron.com, September 25, 2016.

  5. Kostas Tzoumas: “Batch Is a Special Case of Streaming,” data-artisans.com, September 15, 2015.

  6. Shinji Kim and Robert Blafford: “Stream Windowing Performance Analysis: Concord and Spark Streaming,” concord.io, July 6, 2016.

  7. Jay Kreps: “The Log: What Every Software Engineer Should Know About Real-Time Data's Unifying Abstraction,” engineering.linkedin.com, December 16, 2013.

  8. Pat Helland: “Life Beyond Distributed Transactions: An Apostate’s Opinion,” at 3rd Biennial Conference on Innovative Data Systems Research (CIDR), January 2007.

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  12. Nathan Marz and James Warren: Big Data: Principles and Best Practices of Scalable Real-Time Data Systems. Manning, 2015. ISBN: 978-1-617-29034-3

  13. Oscar Boykin, Sam Ritchie, Ian O'Connell, and Jimmy Lin: “Summingbird: A Framework for Integrating Batch and Online MapReduce Computations,” at 40th International Conference on Very Large Data Bases (VLDB), September 2014.

  14. Jay Kreps: “Questioning the Lambda Architecture,” oreilly.com, July 2, 2014.

  15. Raul Castro Fernandez, Peter Pietzuch, Jay Kreps, et al.: “Liquid: Unifying Nearline and Offline Big Data Integration,” at 7th Biennial Conference on Innovative Data Systems Research (CIDR), January 2015.

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  20. Patrycja Dybka: “Foreign Data Wrappers for PostgreSQL,” vertabelo.com, March 24, 2015.

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  22. Martin Kleppmann and Jay Kreps: “Kafka, Samza and the Unix Philosophy of Distributed Data,” IEEE Data Engineering Bulletin, volume 38, number 4, pages 4–14, December 2015.

  23. John Hugg: “Winning Now and in the Future: Where VoltDB Shines,” voltdb.com, March 23, 2016.

  24. Frank McSherry, Derek G. Murray, Rebecca Isaacs, and Michael Isard: “Differential Dataflow,” at 6th Biennial Conference on Innovative Data Systems Research (CIDR), January 2013.

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  26. Gwen Shapira: “We have a bunch of customers who are implementing ‘database inside-out’ concept and they all ask ‘is anyone else doing it? are we crazy?’twitter.com, July 28, 2016.

  27. Martin Kleppmann: “Turning the Database Inside-out with Apache Samza,” at Strange Loop, September 2014.

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  31. Engineer Bainomugisha, Andoni Lombide Carreton, Tom van Cutsem, Stijn Mostinckx, and Wolfgang de Meuter: “A Survey on Reactive Programming,” ACM Computing Surveys, volume 45, number 4, pages 1–34, August 2013. doi:10.1145/2501654.2501666

  32. Peter Alvaro, Neil Conway, Joseph M. Hellerstein, and William R. Marczak: “Consistency Analysis in Bloom: A CALM and Collected Approach,” at 5th Biennial Conference on Innovative Data Systems Research (CIDR), January 2011.

  33. Felienne Hermans: “Spreadsheets Are Code,” at Code Mesh, November 2015.

  34. Dan Bricklin and Bob Frankston: “VisiCalc: Information from Its Creators,” danbricklin.com.

  35. D. Sculley, Gary Holt, Daniel Golovin, et al.: “Machine Learning: The High-Interest Credit Card of Technical Debt,” at NIPS Workshop on Software Engineering for Machine Learning (SE4ML), December 2014.

  36. Peter Bailis, Alan Fekete, Michael J Franklin, et al.: “Feral Concurrency Control: An Empirical Investigation of Modern Application Integrity,” at ACM International Conference on Management of Data (SIGMOD), June 2015. doi:10.1145/2723372.2737784

  37. Guy Steele: “Re: Need for Macros (Was Re: Icon),” email to ll1-discuss mailing list, people.csail.mit.edu, December 24, 2001.

  38. David Gelernter: “Generative Communication in Linda,” ACM Transactions on Programming Languages and Systems (TOPLAS), volume 7, number 1, pages 80–112, January 1985. doi:10.1145/2363.2433

  39. Patrick Th. Eugster, Pascal A. Felber, Rachid Guerraoui, and Anne-Marie Kermarrec: “The Many Faces of Publish/Subscribe,” ACM Computing Surveys, volume 35, number 2, pages 114–131, June 2003. doi:10.1145/857076.857078

  40. Ben Stopford: “Microservices in a Streaming World,” at QCon London, March 2016.

  41. Christian Posta: “Why Microservices Should Be Event Driven: Autonomy vs Authority,” blog.christianposta.com, May 27, 2016.

  42. Alex Feyerke: “Say Hello to Offline First,” hood.ie, November 5, 2013.

  43. Sebastian Burckhardt, Daan Leijen, Jonathan Protzenko, and Manuel Fähndrich: “Global Sequence Protocol: A Robust Abstraction for Replicated Shared State,” at 29th European Conference on Object-Oriented Programming (ECOOP), July 2015. doi:10.4230/LIPIcs.ECOOP.2015.568

  44. Mark Soper: “Clearing Up React Data Management Confusion with Flux, Redux, and Relay,” medium.com, December 3, 2015.

  45. Eno Thereska, Damian Guy, Michael Noll, and Neha Narkhede: “Unifying Stream Processing and Interactive Queries in Apache Kafka,” confluent.io, October 26, 2016.

  46. Frank McSherry: “Dataflow as Database,” github.com, July 17, 2016.

  47. Peter Alvaro: “I See What You Mean,” at Strange Loop, September 2015.

  48. Nathan Marz: “Trident: A High-Level Abstraction for Realtime Computation,” blog.twitter.com, August 2, 2012.

  49. Edi Bice: “Low Latency Web Scale Fraud Prevention with Apache Samza, Kafka and Friends,” at Merchant Risk Council MRC Vegas Conference, March 2016.

  50. Charity Majors: “The Accidental DBA,” charity.wtf, October 2, 2016.

  51. Arthur J. Bernstein, Philip M. Lewis, and Shiyong Lu: “Semantic Conditions for Correctness at Different Isolation Levels,” at 16th International Conference on Data Engineering (ICDE), February 2000. doi:10.1109/ICDE.2000.839387

  52. Sudhir Jorwekar, Alan Fekete, Krithi Ramamritham, and S. Sudarshan: “Automating the Detection of Snapshot Isolation Anomalies,” at 33rd International Conference on Very Large Data Bases (VLDB), September 2007.

  53. Kyle Kingsbury: Jepsen blog post series, aphyr.com, 2013–2016.

  54. Michael Jouravlev: “Redirect After Post,” theserverside.com, August 1, 2004.

  55. Jerome H. Saltzer, David P. Reed, and David D. Clark: “End-to-End Arguments in System Design,” ACM Transactions on Computer Systems, volume 2, number 4, pages 277–288, November 1984. doi:10.1145/357401.357402

  56. Peter Bailis, Alan Fekete, Michael J. Franklin, et al.: “Coordination-Avoiding Database Systems,” Proceedings of the VLDB Endowment, volume 8, number 3, pages 185–196, November 2014.

  57. Alex Yarmula: “Strong Consistency in Manhattan,” blog.twitter.com, March 17, 2016.

  58. Douglas B Terry, Marvin M Theimer, Karin Petersen, et al.: “Managing Update Conflicts in Bayou, a Weakly Connected Replicated Storage System,” at 15th ACM Symposium on Operating Systems Principles (SOSP), pages 172–182, December 1995. doi:10.1145/224056.224070

  59. Jim Gray: “The Transaction Concept: Virtues and Limitations,” at 7th International Conference on Very Large Data Bases (VLDB), September 1981.

  60. Hector Garcia-Molina and Kenneth Salem: “Sagas,” at ACM International Conference on Management of Data (SIGMOD), May 1987. doi:10.1145/38713.38742

  61. Pat Helland: “Memories, Guesses, and Apologies,” blogs.msdn.com, May 15, 2007.

  62. Yoongu Kim, Ross Daly, Jeremie Kim, et al.: “Flipping Bits in Memory Without Accessing Them: An Experimental Study of DRAM Disturbance Errors,” at 41st Annual International Symposium on Computer Architecture (ISCA), June 2014. doi:10.1145/2678373.2665726

  63. Mark Seaborn and Thomas Dullien: “Exploiting the DRAM Rowhammer Bug to Gain Kernel Privileges,” googleprojectzero.blogspot.co.uk, March 9, 2015.

  64. Jim N. Gray and Catharine van Ingen: “Empirical Measurements of Disk Failure Rates and Error Rates,” Microsoft Research, MSR-TR-2005-166, December 2005.

  65. Annamalai Gurusami and Daniel Price: “Bug #73170: Duplicates in Unique Secondary Index Because of Fix of Bug#68021,” bugs.mysql.com, July 2014.

  66. Gary Fredericks: “Postgres Serializability Bug,” github.com, September 2015.

  67. Xiao Chen: “HDFS DataNode Scanners and Disk Checker Explained,” blog.cloudera.com, December 20, 2016.

  68. Jay Kreps: “Getting Real About Distributed System Reliability,” blog.empathybox.com, March 19, 2012.

  69. Martin Fowler: “The LMAX Architecture,” martinfowler.com, July 12, 2011.

  70. Sam Stokes: “Move Fast with Confidence,” blog.samstokes.co.uk, July 11, 2016.

  71. Hyperledger Sawtooth documentation,” Intel Corporation, sawtooth.hyperledger.org, 2017.

  72. Richard Gendal Brown: “Introducing R3 Corda™: A Distributed Ledger Designed for Financial Services,” gendal.me, April 5, 2016.

  73. Trent McConaghy, Rodolphe Marques, Andreas Müller, et al.: “BigchainDB: A Scalable Blockchain Database,” bigchaindb.com, June 8, 2016.

  74. Ralph C. Merkle: “A Digital Signature Based on a Conventional Encryption Function,” at CRYPTO '87, August 1987. doi:10.1007/3-540-48184-2_32

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  76. Mark D. Ryan: “Enhanced Certificate Transparency and End-to-End Encrypted Mail,” at Network and Distributed System Security Symposium (NDSS), February 2014. doi:10.14722/ndss.2014.23379

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  79. François Chollet: “Software development is starting to involve important ethical choices,” twitter.com, October 30, 2016.

  80. Igor Perisic: “Making Hard Choices: The Quest for Ethics in Machine Learning,” engineering.linkedin.com, November 2016.

  81. John Naughton: “Algorithm Writers Need a Code of Conduct,” theguardian.com, December 6, 2015.

  82. Logan Kugler: “What Happens When Big Data Blunders?,” Communications of the ACM, volume 59, number 6, pages 15–16, June 2016. doi:10.1145/2911975

  83. Bill Davidow: “Welcome to Algorithmic Prison,” theatlantic.com, February 20, 2014.

  84. Don Peck: “They're Watching You at Work,” theatlantic.com, December 2013.

  85. Leigh Alexander: “Is an Algorithm Any Less Racist Than a Human?theguardian.com, August 3, 2016.

  86. Jesse Emspak: “How a Machine Learns Prejudice,” scientificamerican.com, December 29, 2016.

  87. Maciej Cegłowski: “The Moral Economy of Tech,” idlewords.com, June 2016.

  88. Cathy O'Neil: Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown Publishing, 2016. ISBN: 978-0-553-41881-1

  89. Julia Angwin: “Make Algorithms Accountable,” nytimes.com, August 1, 2016.

  90. Bryce Goodman and Seth Flaxman: “European Union Regulations on Algorithmic Decision-Making and a ‘Right to Explanation’,” arXiv:1606.08813, August 31, 2016.

  91. A Review of the Data Broker Industry: Collection, Use, and Sale of Consumer Data for Marketing Purposes,” Staff Report, United States Senate Committee on Commerce, Science, and Transportation, commerce.senate.gov, December 2013.

  92. Olivia Solon: “Facebook’s Failure: Did Fake News and Polarized Politics Get Trump Elected?theguardian.com, November 10, 2016.

  93. Donella H. Meadows and Diana Wright: Thinking in Systems: A Primer. Chelsea Green Publishing, 2008. ISBN: 978-1-603-58055-7

  94. Daniel J. Bernstein: “Listening to a ‘big data’/‘data science’ talk,” twitter.com, May 12, 2015.

  95. Marc Andreessen: “Why Software Is Eating the World,” The Wall Street Journal, 20 August 2011.

  96. J. M. Porup: “‘Internet of Things’ Security Is Hilariously Broken and Getting Worse,” arstechnica.com, January 23, 2016.

  97. Bruce Schneier: Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World. W. W. Norton, 2015. ISBN: 978-0-393-35217-7

  98. The Grugq: “Nothing to Hide,” grugq.tumblr.com, April 15, 2016.

  99. Tony Beltramelli: “Deep-Spying: Spying Using Smartwatch and Deep Learning,” Masters Thesis, IT University of Copenhagen, December 2015. Available at arxiv.org/abs/1512.05616

  100. Shoshana Zuboff: “Big Other: Surveillance Capitalism and the Prospects of an Information Civilization,” Journal of Information Technology, volume 30, number 1, pages 75–89, April 2015. doi:10.1057/jit.2015.5

  101. Carina C. Zona: “Consequences of an Insightful Algorithm,” at GOTO Berlin, November 2016.

  102. Bruce Schneier: “Data Is a Toxic Asset, So Why Not Throw It Out?,” schneier.com, March 1, 2016.

  103. John E. Dunn: “The UK’s 15 Most Infamous Data Breaches,” techworld.com, November 18, 2016.

  104. Cory Scott: “Data is not toxic - which implies no benefit - but rather hazardous material, where we must balance need vs. want,” twitter.com, March 6, 2016.

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