Skip to main content

参考文献（References）

原文：Readings in Database Systems, Fifth Edition (2015)，References。原书文本采用 CC BY-NC-SA 4.0 许可；本译文按同一许可发布。

  • [1] Apache Tez. https://tez.apache.org/.
  • [2] Flexcoin: The Bitcoin Bank, 2014. http://www.flexcoin.com/; originally via Emin Gun Sirer.
  • [3] D. J. Abadi, D. Carney, U. Cetintemel, M. Cherniack, C. Convey, S. Lee, M. Stonebraker, N. Tatbul, and S. Zdonik. Aurora: a new model and architecture for data stream management. The VLDB Journal: The International Journal on Very Large Data Bases, 12(2):120–139, 2003.
  • [4] Z. Abedjan, J. Morcos, M. Gubanov, I. F. Ilyas, M. Stonebraker, P. Papotti, and M. Ouzzani. Dataxformer: Leveraging the web for semantic transformations. In CIDR, 2015.
  • [5] S. Acharya, P. B. Gibbons, V. Poosala, and S. Ramaswamy. The Aqua approximate query answering system. In SIGMOD, 1999.
  • [6] A. Adya. Weak consistency: a generalized theory and optimistic implementations for distributed transactions. PhD thesis, MIT, 1999.
  • [7] R. Agrawal, T. Imielinski, and A. Swami. Mining association rules between sets of items in large databases. In SIGMOD, 1993.
  • [8] T. Akidau et al. The dataflow model: A practical approach to balancing correctness, latency, and cost in massive-scale, unbounded, out-of-order data processing. In VLDB, 2015.
  • [9] A. Alexandrov, R. Bergmann, S. Ewen, J.-C. Freytag, F. Hueske, A. Heise, O. Kao, M. Leich, U. Leser, V. Markl, et al. The Stratosphere platform for big data analytics. The VLDB Journal, 23(6):939–964, 2014.
  • [10] S. Alsubaiee, Y. Altowim, H. Altwaijry, A. Behm, V. Borkar, Y. Bu, M. Carey, I. Cetindil, M. Cheelangi, K. Faraaz, et al. Asterixdb: A scalable, open source bdms. In VLDB, 2014.
  • [11] P. Alvaro, P. Bailis, N. Conway, and J. M. Hellerstein. Consistency without borders. In SoCC, 2013.
  • [12] P. Alvaro, N. Conway, J. M. Hellerstein, and D. Maier. Blazes: Coordination analysis for distributed programs. In Data Engineering (ICDE), 2014 IEEE 30th International Conference on, pages 52–63. IEEE, 2014.
  • [13] T. J. Ameloot. Declarative networking: Recent theoretical work on coordination, correctness, and declarative semantics. ACM SIGMOD Record, 43(2):5–16, 2014.
  • [14] T. J. Ameloot, F. Neven, and J. Van den Bussche. Relational transducers for declarative networking. Journal of the ACM (JACM), 60(2):15, 2013.
  • [15] M. Armbrust, R. S. Xin, C. Lian, Y. Huai, D. Liu, J. K. Bradley, X. Meng, T. Kaftan, M. J. Franklin, A. Ghodsi, et al. Spark SQL: Relational data processing in spark. In SIGMOD, 2015.
  • [16] S. Babu and H. Herodotou. Massively parallel databases and MapReduce systems. Foundations and Trends in Databases, 5(1):1–104, 2013.
  • [17] P. Bailis. Coordination avoidance in distributed databases. PhD thesis, University of California at Berkeley, 2015.
  • [18] P. Bailis, A. Davidson, A. Fekete, A. Ghodsi, J. M. Hellerstein, and I. Stoica. Highly Available Transactions: Virtues and limitations. In VLDB, 2014.
  • [19] P. Bailis, A. Fekete, M. J. Franklin, A. Ghodsi, J. M. Hellerstein, and I. Stoica. Feral Concurrency Control: An empirical investigation of modern application integrity. In SIGMOD, 2015.
  • [20] P. Bailis, A. Fekete, M. J. Franklin, J. M. Hellerstein, A. Ghodsi, and I. Stoica. Coordination avoidance in database systems. In VLDB, 2015.
  • [21] P. Bailis, A. Fekete, A. Ghodsi, J. M. Hellerstein, and I. Stoica. Scalable atomic visibility with RAMP transactions. In SIGMOD, 2014.
  • [22] P. Bailis and A. Ghodsi. Eventual consistency today: Limitations, extensions, and beyond. ACM Queue, 11(3), 2013.
  • [23] P. Bailis, S. Venkataraman, M. J. Franklin, J. M. Hellerstein, and I. Stoica. Probabilistically Bounded Staleness for practical partial quorums. In VLDB, 2012.
  • [24] S. Balakrishnan, A. Halevy, B. Harb, H. Lee, J. Madhavan, A. Rostamizadeh, W. Shen, K. Wilder, F. Wu, and C. Yu. Applying webtables in practice. In CIDR, 2015.
  • [25] D. S. Batory. On searching transposed files. ACM Transactions on Database Systems (TODS), 4(4), Dec. 1979.
  • [26] P. Baumann, A. Dehmel, P. Furtado, R. Ritsch, and N. Widmann. The multidimensional database system rasdaman. In SIGMOD, 1998.
  • [27] H. Berenson, P. Bernstein, J. Gray, J. Melton, E. O’Neil, and P. O’Neil. A critique of ANSI SQL isolation levels. In SIGMOD, 1995.
  • [28] P. Bernstein, V. Hadzilacos, and N. Goodman. Concurrency control and recovery in database systems, volume 370. Addison-Wesley New York, 1987.
  • [29] P. A. Bernstein and S. Das. Rethinking eventual consistency. In SIGMOD, 2013.
  • [30] P. A. Boncz, M. Zukowski, and N. Nes. Monetdb/x100: Hyper-pipelining query execution. In CIDR, 2005.
  • [31] E. Brewer et al. Lessons from giant-scale services. Internet Computing, IEEE, 5(4):46–55, 2001.
  • [32] M. Burrows. The chubby lock service for loosely-coupled distributed systems. In OSDI, 2006.
  • [33] D. D. Chamberlin. Early history of sql. Annals of the History of Computing, IEEE, 34(4):78–82, 2012.
  • [34] D. D. Chamberlin and R. F. Boyce. Sequel: A structured english query language. In Proceedings of the 1974 ACM SIGFIDET (now SIGMOD) workshop on Data description, access and control, pages 249–264. ACM, 1974.
  • [35] T. D. Chandra, R. Griesemer, and J. Redstone. Paxos made live: an engineering perspective. In PODC, 2007.
  • [36] S. Chandrasekaran, O. Cooper, A. Deshpande, M. J. Franklin, J. M. Hellerstein, W. Hong, S. Krishnamurthy, S. Madden, V. Raman, F. Reiss, et al. Telegraphcq: Continuous dataflow processing for an uncertain world. In CIDR, 2003.
  • [37] F. Chang, J. Dean, S. Ghemawat, W. C. Hsieh, D. A. Wallach, M. Burrows, T. Chandra, A. Fikes, and R. E. Gruber. Bigtable: A distributed storage system for structured data. In OSDI, 2006.
  • [38] A. Cheung, O. Arden, S. Madden, A. Solar-Lezama, and A. C. Myers. StatusQuo: Making familiar abstractions perform using program analysis. In CIDR, 2013.
  • [39] T. Chilimbi, Y. Suzue, J. Apacible, and K. Kalyanaraman. Project adam: Building an efficient and scalable deep learning training system. In OSDI, 2014.
  • [40] J. Choi et al. ScaLAPACK: A portable linear algebra library for distributed memory computers—design issues and performance. In Applied Parallel Computing Computations in Physics, Chemistry and Engineering Science, pages 95–106. Springer, 1996.
  • [41] X. Chu, I. F. Ilyas, and P. Papotti. Holistic data cleaning: Putting violations into context. In ICDE, 2013.
  • [42] A. T. Clements, M. F. Kaashoek, N. Zeldovich, R. T. Morris, and E. Kohler. The scalable commutativity rule: Designing scalable software for multicore processors. ACM Transactions on Computer Systems (TOCS), 32(4):10, 2015.
  • [43] T. Condie, D. Chu, J. M. Hellerstein, and P. Maniatis. Evita raced: metacompilation for declarative networks. Proceedings of the VLDB Endowment, 1(1):1153–1165, 2008.
  • [44] G. Cormode, M. Garofalakis, P. J. Haas, and C. Jermaine. Synopses for massive data: Samples, histograms, wavelets, sketches. Foundations and Trends in Databases, 4(1–3):1–294, 2012.
  • [45] C. J. Date. An architecture for high-level language database extensions. In SIGMOD, 1976.
  • [46] C. J. Date. A critique of the SQL database language. ACM SIGMOD Record, 14(3), Nov. 1984.
  • [47] S. Davidson, H. Garcia-Molina, and D. Skeen. Consistency in partitioned networks. ACM CSUR, 17(3):341– 370, 1985.
  • [48] J. Dean. Designs, lessons and advice from building large distributed systems (keynote). In LADIS, 2009.
  • [49] J. Dean, G. Corrado, R. Monga, K. Chen, M. Devin, M. Mao, A. Senior, P. Tucker, K. Yang, Q. V. Le, et al. Large scale distributed deep networks. In Advances in Neural Information Processing Systems, pages 1223– 1231, 2012.
  • [50] A. Deshpande. An initial study of overheads of eddies. ACM SIGMOD Record, 33(1):44–49, 2004.
  • [51] A. Deshpande and J. M. Hellerstein. Lifting the burden of history from adaptive query processing. In VLDB, 2004.
  • [52] A. Deshpande, Z. Ives, and V. Raman. Adaptive query processing. Foundations and Trends in Databases, 1(1):1–140, 2007.
  • [53] D. DeWitt and M. Stonebraker. Mapreduce: A major step backwards. The Database Column, 2008.
  • [54] T. Dohzen, M. Pamuk, S.-W. Seong, J. Hammer, and M. Stonebraker. Data integration through transform reuse in the morpheus project. In SIGMOD, 2006.
  • [55] J. Duggan and M. Stonebraker. Incremental elasticity for array databases. In Proceedings of the 2014 ACM SIGMOD international conference on Management of data, pages 409–420. ACM, 2014.
  • [56] A. Elmore, J. Duggan, M. Stonebraker, M. Balazinska, U. Cetintemel, V. Gadepally, J. Heer, B. Howe, J. Kep- ner, T. Kraska, et al. A demonstration of the BigDAWG polystore system. In VLDB, 2015.
  • [57] K. P. Eswaran, J. N. Gray, R. A. Lorie, and I. L. Traiger. The notions of consistency and predicate locks in a database system. Communications of the ACM, 19(11):624–633, 1976.
  • [58] J. Fan, A. Gerald, S. Raj, and J. M. Patel. The case against specialized graph analytics engines. In CIDR, 2015.
  • [59] A. Fekete, D. Liarokapis, E. O’Neil, P. O’Neil, and D. Shasha. Making snapshot isolation serializable. ACM TODS, 30(2):492–528, June 2005.
  • [60] M. J. Fischer, N. A. Lynch, and M. S. Paterson. Impossibility of distributed consensus with one faulty process. Journal of the ACM (JACM), 32(2):374–382, 1985.
  • [61] M. J. Franklin. Concurrency control and recovery. The Computer Science and Engineering Handbook, pages 1–58–1077, 1997.
  • [62] S. Ghemawat, H. Gobioff, and S.-T. Leung. The google file system. In SOSP, 2003.
  • [63] A. Ghoting, R. Krishnamurthy, E. Pednault, B. Reinwald, V. Sindhwani, S. Tatikonda, Y. Tian, and S. Vaithyanathan. Systemml: Declarative machine learning on mapreduce. In ICDE, 2011.
  • [64] J. E. Gonzales, R. S. Xin, D. Crankshaw, A. Dave, M. J. Franklin, and I. Stoica. Graphx: Unifying data-parallel and graph-parallel analytics. In OSDI, 2014.
  • [65] G. Graefe. The cascades framework for query optimization. IEEE Data Eng. Bull., 18(3):19–29, 1995.
  • [66] G. Graefe. The five-minute rule twenty years later, and how flash memory changes the rules. In DaMoN, 2007.
  • [67] J. Gray. Notes on data base operating systems. In Operating Systems: An Advanced Course, volume 60 of Lecture Notes in Computer Science, pages 393–481. Springer Berlin Heidelberg, 1978.
  • [68] J. Gray, S. Chaudhuri, A. Bosworth, A. Layman, D. Reichart, M. Venkatrao, F. Pellow, and H. Pirahesh. Data cube: A relational aggregation operator generalizing group-by, cross-tab, and sub-totals. Data Mining and Knowledge Discovery, 1(1):29–53, 1997.
  • [69] J. Gray and G. Graefe. The five-minute rule ten years later, and other computer storage rules of thumb. ACM SIGMOD Record, 26(4):63–68, 1997.
  • [70] J. Gray, P. Helland, P. ONeil, and D. Shasha. The dangers of replication and a solution. In SIGMOD, 1996.
  • [71] J. Gray and L. Lamport. Consensus on transaction commit. ACM Transactions on Database Systems (TODS), 31(1):133–160, Mar. 2006.
  • [72] J. Gray, R. Lorie, G. Putzolu, and I. Traiger. Granularity of locks and degrees of consistency in a shared data base. Technical report, IBM, 1976.
  • [73] J. Gray and F. Putzolu. The 5 minute rule for trading memory for disc accesses and the 10 byte rule for trading memory for cpu time. In SIGMOD, 1987.
  • [74] T. J. Green, S. S. Huang, B. T. Loo, and W. Zhou. Datalog and recursive query processing. Foundations and Trends in Databases, 5(2):105–195, 2013.
  • [75] R. Guerraoui. Revisiting the relationship between non-blocking atomic commitment and consensus. In WDAG, 1995.
  • [76] R. Guerraoui, M. Larrea, and A. Schiper. Non blocking atomic commitment with an unreliable failure detector. In SRDS, 1995.
  • [77] L. Haas, D. Kossmann, E. Wimmers, and J. Yang. Optimizing queries across diverse data sources. In VLDB, 1997.
  • [78] T. Haerder and A. Reuter. Principles of transaction-oriented database recovery. ACM Computing Surveys (CSUR), 15(4):287–317, 1983.
  • [79] A. Halevy, P. Norvig, and F. Pereira. The unreasonable effectiveness of data. IEEE Intelligent Systems, 24(2):8– 12, Mar. 2009.
  • [80] D. H. Hansson et al. Ruby on rails. http://www.rubyonrails.org.
  • [81] D. Harris. Forbes: Why Cloudera is saying ’Goodbye, MapReduce’ and ’Hello, Spark’, 2015. http:// fortune.com/2015/09/09/cloudera-spark-mapreduce/.
  • [82] M. Hausenblas and J. Nadeau. Apache Drill: Interactive ad-hoc analysis at scale. Big Data, 1(2):100–104, 2013.
  • [83] P. Helland and D. Campbell. Building on quicksand. In CIDR, 2009.
  • [84] J. M. Hellerstein. The declarative imperative: experiences and conjectures in distributed logic. ACM SIGMOD Record, 39(1):5–19, 2010.
  • [85] J. M. Hellerstein, C. Re, F. Schoppmann, D. Z. Wang, E. Fratkin, A. Gorajek, K. S. Ng, C. Welton, X. Feng, K. Li, et al. The MADlib analytics library: or MAD skills, the SQL. In VLDB, 2012.
  • [86] T. Ibaraki and T. Kameda. On the optimal nesting order for computing n-relational joins. ACM Transactions on Database Systems (TODS), 9(3):482–502, 1984.
  • [87] I. F. Ilyas and X. Chu. Trends in cleaning relational data: Consistency and deduplication. Foundations and Trends in Databases, 5(4):281–393, 2012.
  • [88] Y. E. Ioannidis and S. Christodoulakis. On the propagation of errors in the size of join results. In SIGMOD, 1991.
  • [89] M. Isard, M. Budiu, Y. Yu, A. Birrell, and D. Fetterly. Dryad: distributed data-parallel programs from sequential building blocks. In EuroSys, 2007.
  • [90] A. Jindal, P. Rawlani, E. Wu, S. Madden, A. Deshpande, and M. Stonebraker. Vertexica: your relational friend for graph analytics! In VLDB, 2014.
  • [91] P. R. Johnson and R. H. Thomas. Rfc 667: The maintenance of duplicate databases. Technical report, 1 1975.
  • [92] F. P. Junqueira, B. C. Reed, and M. Serafini. Zab: High-performance broadcast for primary-backup systems. In DSN, 2011.
  • [93] N. Kabra and D. J. DeWitt. Efficient mid-query re-optimization of sub-optimal query execution plans. In SIGMOD, 1998.
  • [94] S. Kandel, A. Paepcke, J. Hellerstein, and J. Heer. Wrangler: Interactive visual specification of data transfor- mation scripts. In CHI, 2011.
  • [95] J. Kepner et al. Dynamic distributed dimensional data model (D4M) database and computation system. In Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on, pages 5349–5352. IEEE, 2012.
  • [96] R. Kimball and M. Ross. The data warehouse toolkit: the complete guide to dimensional modeling. John Wiley & Sons, 2011.
  • [97] T. Koponen, K. Amidon, P. Balland, M. Casado, A. Chanda, B. Fulton, I. Ganichev, J. Gross, N. Gude, P. In- gram, et al. Network virtualization in multi-tenant datacenters. In USENIX NSDI, 2014.
  • [98] M. Kornacker, A. Behm, V. Bittorf, T. Bobrovytsky, C. Ching, A. Choi, J. Erickson, M. Grund, D. Hecht, M. Jacobs, et al. Impala: A modern, open-source sql engine for hadoop. In CIDR, 2015.
  • [99] L. Lamport. The part-time parliament. ACM Transactions on Computer Systems (TOCS), 16(2):133–169, 1998.
  • [100] B. Lampson and H. Sturgis. Crash recovery in a distributed data storage system. Technical report, 1979.
  • [101] M. Li, D. G. Andersen, J. W. Park, A. J. Smola, A. Ahmed, V. Josifovski, J. Long, E. J. Shekita, and B.-Y. Su. Scaling distributed machine learning with the parameter server. In OSDI, 2014.
  • [102] B. Liskov and J. Cowling. Viewstamped replication revisited. Technical report, MIT, 2012.
  • [103] G. M. Lohman. Grammar-like functional rules for representing query optimization alternatives. In SIGMOD, 1988.
  • [104] R. Lorie and A. Symonds. A relational access method for interactive applications. Courant Computer Science Symposia, Vol. 6: Data Base Systems, 1971.
  • [105] Y. Low, D. Bickson, J. Gonzalez, C. Guestrin, A. Kyrola, and J. M. Hellerstein. Distributed graphlab: a framework for machine learning and data mining in the cloud. In VLDB, 2012.
  • [106] H. Lu, K. Veeraraghavan, P. Ajoux, J. Hunt, Y. J. Song, W. Tobagus, S. Kumar, and W. Lloyd. Existential consistency: measuring and understanding consistency at Facebook. In SOSP, 2015.
  • [107] H. P. Luhn. Auto-encoding of documents for information retrieval systems. Modern Trends in Documentation, pages 45–58, 1959.
  • [108] R. MacNicol and B. French. Sybase iq multiplex-designed for analytics. In VLDB, 2004.
  • [109] S. Madden, M. Shah, J. M. Hellerstein, and V. Raman. Continuously adaptive continuous queries over streams. In SIGMOD, 2002.
  • [110] G. Malewicz, M. H. Austern, A. J. Bik, J. C. Dehnert, I. Horn, N. Leiser, and G. Czajkowski. Pregel: a system for large-scale graph processing. In SIGMOD, 2010.
  • [111] N. Malviya, A. Weisberg, S. Madden, and M. Stonebraker. Rethinking main memory OLTP recovery. In ICDE, 2014.
  • [112] M. K. McKusick, K. Bostic, M. J. Karels, and J. S. Quarterman. The design and implementation of the 4.4 BSD operating system. Pearson Education, 1996.
  • [113] F. McSherry, M. Isard, and D. G. Murray. Scalability! But at what COST" In HotOS, 2015.
  • [114] E. Meijer. Your mouse is a database. Queue, 10(3):20, 2012.
  • [115] E. Meijer, B. Beckman, and G. Bierman. Linq: reconciling object, relations and XML in the .NET framework. In SIGMOD, 2006.
  • [116] J. Melton, J. E. Michels, V. Josifovski, K. Kulkarni, and P. Schwarz. Sql/med: a status report. ACM SIGMOD Record, 31(3):81–89, 2002.
  • [117] R. J. Miller, M. A. Hernandez, L. M. Haas, L.-L. Yan, C. H. Ho, R. Fagin, and L. Popa. The clio project: managing heterogeneity. SIGMOD Record, 30(1):78–83, 2001.
  • [118] R. Motwani, J. Widom, A. Arasu, B. Babcock, S. Babu, M. Datar, G. Manku, C. Olston, J. Rosenstein, and R. Varma. Query processing, resource management, and approximation in a data stream management system. In CIDR, 2003.
  • [119] D. G. Murray, F. McSherry, R. Isaacs, M. Isard, P. Barham, and M. Abadi. Naiad: A timely dataflow system. In SOSP, 2013.
  • [120] J. F. Naughton, D. J. DeWitt, D. Maier, A. Aboulnaga, J. Chen, L. Galanis, J. Kang, R. Krishnamurthy, Q. Luo, N. Prakash, et al. The niagara internet query system. IEEE Data Eng. Bull., 24(2):27–33, 2001.
  • [121] H. Q. Ngo, E. Porat, C. Re, and A. Rudra. Worst-case optimal join algorithms:[extended abstract]. In Proceedings of the 31st symposium on Principles of Database Systems, pages 37–48. ACM, 2012.
  • [122] F. Olken. Random sampling from databases. PhD thesis, University of California at Berkeley, 1993.
  • [123] C. Olston, B. Reed, U. Srivastava, R. Kumar, and A. Tomkins. Pig latin: a not-so-foreign language for data processing. In SIGMOD, 2008.
  • [124] P. E. O’Neil. The escrow transactional method. ACM Transactions on Database Systems, 11(4):405–430, 1986.
  • [125] D. Ongaro and J. Ousterhout. In search of an understandable consensus algorithm. In USENIX ATC, 2014.
  • [126] L. Page, S. Brin, R. Motwani, and T. Winograd. The PageRank citation ranking: bringing order to the web. Technical report, Stanford InfoLab, 1999. SIDL-WP-1999-0120.
  • [127] R. Ramakrishnan and J. Gehrke. Database management systems. McGraw Hill, 2000.
  • [128] R. Ramakrishnan and S. Sudarshan. Top-down vs. bottom-up revisited. In Proceedings of the International Logic Programming Symposium, pages 321–336, 1991.
  • [129] V. Raman, A. Deshpande, and J. M. Hellerstein. Using state modules for adaptive query processing. In ICDE. IEEE, 2003.
  • [130] V. Raman and J. M. Hellerstein. Potter’s wheel: An interactive data cleaning system. In VLDB, 2001.
  • [131] V. Raman and J. M. Hellerstein. Partial results for online query processing. In SIGMOD, pages 275–286. ACM, 2002.
  • [132] A. Rasmussen, V. T. Lam, M. Conley, G. Porter, R. Kapoor, and A. Vahdat. Themis: An i/o-efficient mapreduce. In SoCC, 2012.
  • [133] B. Recht, C. Re, S. Wright, and F. Niu. Hogwild: A lock-free approach to parallelizing stochastic gradient descent. In Advances in Neural Information Processing Systems, pages 693–701, 2011.
  • [134] M. T. Roth and P. M. Schwarz. Don’t scrap it, wrap it! a wrapper architecture for legacy data sources. In VLDB, 1997.
  • [135] L. A. Rowe and K. A. Shoens. Data abstraction, views and updates in RIGEL. In SIGMOD, 1979.
  • [136] S. Roy, L. Kot, G. Bender, B. Ding, H. Hojjat, C. Koch, N. Foster, and J. Gehrke. The homeostasis protocol: Avoiding transaction coordination through program analysis. In SIGMOD, 2015.
  • [137] S. Roy, L. Kot, G. Bender, B. Ding, H. Hojjat, C. Koch, N. Foster, and J. Gehrke. The homeostasis protocol: Avoiding transaction coordination through program analysis. In SIGMOD, 2015.
  • [138] Y. Saito and M. Shapiro. Optimistic replication. ACM Comput. Surv., 37(1), Mar. 2005.
  • [139] G. Salton and M. E. Lesk. Computer evaluation of indexing and text processing. Journal of the ACM (JACM), 15(1):8–36, 1968.
  • [140] J. W. Schmidt. Some high level language constructs for data of type relation. ACM Trans. Database Syst., 2(3), Sept. 1977.
  • [141] F. B. Schneider. Implementing fault-tolerant services using the state machine approach: A tutorial. ACM Computing Surveys (CSUR), 22(4):299–319, 1990.
  • [142] M. Shapiro, N. Preguica, C. Baquero, and M. Zawirski. A comprehensive study of convergent and commutative replicated data types. INRIA TR 7506, 2011.
  • [143] J. Shute, R. Vingralek, B. Samwel, B. Handy, C. Whipkey, E. Rollins, M. Oancea, K. Littlefield, D. Menestrina, S. Ellner, et al. F1: A distributed sql database that scales. In VLDB, 2013.
  • [144] N. Siva. 1000 genomes project. Nature biotechnology, 26(3):256–256, 2008.
  • [145] D. Skeen. Nonblocking commit protocols. In SIGMOD, 1981.
  • [146] E. R. Sparks, A. Talwalkar, V. Smith, J. Kottalam, X. Pan, J. Gonzalez, M. J. Franklin, M. Jordan, T. Kraska, et al. Mli: An api for distributed machine learning. In ICDM, 2013.
  • [147] M. Stonebraker. The land sharks are on the squawk box. Communications of the ACM. To appear.
  • [148] M. Stonebraker, D. Bruckner, I. F. Ilyas, G. Beskales, M. Cherniack, S. B. Zdonik, A. Pagan, and S. Xu. Data curation at scale: The data tamer system. In CIDR, 2013.
  • [149] M. Stonebraker and U. Cetintemel. “one size fits all”: an idea whose time has come and gone. In ICDE, 2005.
  • [150] M. Stonebraker, G. Held, E. Wong, and P. Kreps. The design and implementation of ingres. ACM Transactions on Database Systems (TODS), 1(3):189–222, 1976.
  • [151] M. Stonebraker, S. Madden, and P. Dubey. Intel big data science and technology center vision and execution plan. ACM SIGMOD Record, 42(1):44–49, 2013.
  • [152] M. Stonebraker and E. Neuhold. The laguna beach report. Technical Report 1, International Institute of Computer Science, 1989.
  • [153] D. Terry. Replicated data consistency explained through baseball. Communications of the ACM, 56(12):82–89, 2013.
  • [154] D. B. Terry, A. J. Demers, K. Petersen, M. J. Spreitzer, M. M. Theimer, et al. Session guarantees for weakly consistent replicated data. In PDIS, 1994.
  • [155] The SciDB Development Team. Overview of SciDB: large scale array storage, processing and analysis. In SIGMOD, 2010.
  • [156] A. Thusoo, J. S. Sarma, N. Jain, Z. Shao, P. Chakka, S. Anthony, H. Liu, P. Wyckoff, and R. Murthy. Hive: A warehousing solution over a map-reduce framework. In VLDB, 2009.
  • [157] T. Urhan, M. J. Franklin, and L. Amsaleg. Cost-based query scrambling for initial delays. ACM SIGMOD Record, 27(2):130–141, 1998.
  • [158] M. Vartak, S. Madden, A. Parameswaran, and N. Polyzotis. Seedb: automatically generating query visualizations. In VLDB, 2014.
  • [159] H. Wada, A. Fekete, L. Zhao, K. Lee, and A. Liu. Data consistency properties and the trade-offs in commercial cloud storage: the consumers’ perspective. In CIDR, 2011.
  • [160] A. N. Wilschut and P. M. Apers. Dataflow query execution in a parallel main-memory environment. In Parallel and Distributed Information Systems, 1991., Proceedings of the First International Conference on, pages 68–77. IEEE, 1991.
  • [161] E. Wong and K. Youssefi. Decomposition: a strategy for query processing. ACM Transactions on Database Systems (TODS), 1(3):223–241, 1976.
  • [162] E. Wu and S. Madden. Scorpion: Explaining away outliers in aggregate queries. In VLDB, 2013.
  • [163] M. Zaharia, M. Chowdhury, T. Das, A. Dave, J. Ma, M. McCauley, M. J. Franklin, S. Shenker, and I. Stoica. Resilient distributed datasets: A fault-tolerant abstraction for in-memory cluster computing. In NSDI, 2012.