{"id":17,"date":"2017-06-09T13:41:10","date_gmt":"2017-06-09T13:41:10","guid":{"rendered":"http:\/\/vargas-solar.com\/datacentric-sciences\/?page_id=17"},"modified":"2018-03-06T16:28:44","modified_gmt":"2018-03-06T16:28:44","slug":"bibliography","status":"publish","type":"page","link":"http:\/\/vargas-solar.com\/datacentric-sciences\/bibliography\/","title":{"rendered":"BIBLIOGRAPHY"},"content":{"rendered":"
    \n
  1. Chaudhuri, \u201cWhat next?: a half-dozen data management research goals for big data and the cloud,\u201d in Proc. of the 31st PODS Symposium on Principles of Database Systems <\/em><\/li>\n
  2. A.K and Madam Prabhu D., \u201cNo problem with Big Data. What do you mean by Big?,\u201d Informatics<\/em>, no. October, pp. 30\u201332, 2012.<\/li>\n
  3. Atkinson, D. Dewitt, D. Maier, K. Dittrich, and S. Zdonik, \u201cThe Object-Oriented Database System Manifesto r,\u201d pp. 1\u201317.<\/li>\n
  4. Langford, \u201cParallel machine learning on big data,\u201d XRDS Crossroads, ACM Mag. Students<\/em>, vol. 19, no. 1, Sep. 2012.<\/li>\n
  5. Apps and R. Scale, Big Data Sourcebook<\/em>. 2014.<\/li>\n
  6. L. Kersten, S. Idreos, S. Manegold, and E. Liarou, \u201cThe Researcher\u2019s Guide to the Data Deluge\u202f: Querying a Scientific Database in Just a Few Seconds,\u201d Proc. VLDB Endow.<\/em>, vol. 4, no. 12, 2011.<\/li>\n
  7. Hoffmann, \u201cLooking back at big data,\u201d Commun. ACM<\/em>, vol. 56, no. 4, Apr. 2013.<\/li>\n
  8. S. Vitter, \u201cExternal memory algorithms and structures: dealing with Massive Data,\u201d ACM Comput. Surv.<\/em>, vol. 33, no. 2, 2001.<\/li>\n
  9. Cattell, \u201cScalable SQL and NoSQL data stores,\u201d SIGMOD Rec.<\/em>, vol. 39, no. 4, May 2011.<\/li>\n
  10. J. Sadalage and M. Fowler, NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot<\/em>. 2012.<\/li>\n
  11. Ghemawat, H. Gobioff, and S.-T. Leung, \u201cThe Google file system,\u201d in Proc. of the 19th ACM SOSP Symposium on Operating Systems Principles (SOSP\u201903)<\/em>, 2003, vol. 37, no. 5.<\/li>\n
  12. Cafarella, A. Halevy, W. Hsieh, S. Muthukrishnan, R. Bayardo, O. Benjelloun, V. Ganapathy, Y. Matias, R. Pike, and R. Srikant, \u201cData Management Projects at Google,\u201d SIGMOD Rec.<\/em>, vol. 37, no. 1, 2008.<\/li>\n
  13. Dean and S. Ghemawat, \u201cMapReduce: simplified data processing on large clusters,\u201d Commun. ACM<\/em>, vol. 51, no. 1, Jan. 2008.<\/li>\n
  14. Borthakur, \u201cHDFS Architecture Guide,\u201d Apache Rep.<\/em>, pp. 1\u201313, 2010.<\/li>\n
  15. Dittrich and J.-A. Quian\u00e9-Ruiz, \u201cEfficient big data processing in Hadoop MapReduce,\u201d Proc. VLDB Endow.<\/em>, vol. 5, no. 12, Aug. 2012.<\/li>\n
  16. Li, B. C. Ooi, M. T. \u00d6zsu, and S. Wu, \u201cDistributed data management using MapReduce,\u201d ACM Comput. Surv.<\/em>, vol. 46, no. 3, Feb. 2014.<\/li>\n
  17. Okcan and M. Riedewald, \u201cProcessing theta-joins using MapReduce,\u201d in of the 2011 ACM SIGMOD Int. Conference on Management of Data (SIGMOD \u201911)<\/em>, 2011.<\/li>\n
  18. D. Ullman, \u201cDesigning good MapReduce algorithms,\u201d XRDS Crossroads, ACM Mag. Students<\/em>, vol. 19, no. 1, Sep. 2012.<\/li>\n
  19. Chandar, \u201cJoin Algorithms using Map \/ Reduce,\u201d Slides<\/em>, 2010.<\/li>\n
  20. Thusoo, J. Sen Sarma, N. Jain, Z. Shao, P. Chakka, N. Zhang, S. Antony, H. Liu, and R. Murthy, \u201cHive – a petabyte scale data warehouse using Hadoop,\u201d in of the 26th ICDE Int. Conference on Data Engineering (ICDE\u201910)<\/em>, 2010.<\/li>\n
  21. Olston, B. Reed, U. Srivastava, R. Kumar, and A. Tomkins, \u201cPig latin: a not-so-foreign language for data processing,\u201d in of the 2008 ACM SIGMOD Int. Conference on Management of data (SIGMOD\u201908)<\/em>, 2008.<\/li>\n
  22. R. Borkar, M. J. Carey, and C. Li, \u201cBig data platforms: What\u2019s next?,\u201d XRDS Crossroads, ACM Mag. Students<\/em>, vol. 19, no. 1, Sep. 2012.<\/li>\n
  23. Abadi and D. J. Dewitt, \u201cmapReduce and Parallel DBmss\u202f: friends or foes\u202f?\u201d<\/li>\n
  24. Stonebraker, S. Madden, D. J. Abadi, S. Harizopoulos, N. Hachem, and P. Helland, \u201cThe end of an architectural era: (it\u2019s time for a complete rewrite),\u201d in Proc. of the 33rd VLDB Int. Conference on Very Large Data Bases (VLDB \u201907)<\/em>, 2007.<\/li>\n
  25. Mohan, \u201cHistory repeats itself: sensible and NonsenSQL aspects of the NoSQL hoopla,\u201d in Proc. of the 16th EDBT Int. Conference on Extending Database Technology (EDBT\u201913)<\/em>, 2013.<\/li>\n
  26. Ren, Y. Kwon, M. Balazinska, and B. Howe, \u201cHadoop\u2019s adolescence: an analysis of Hadoop usage in scientific workloads,\u201d Proc. VLDB Endow.<\/em>, vol. 6, no. 10, Aug. 2013.<\/li>\n
  27. C. Economics, \u201cFor Big Data Analytics There \u2019 s No Such Thing as Too Big,\u201d no. March, pp. 1\u201320, 2012.<\/li>\n
  28. Idreos, I. Alagiannis, R. Johnson, and A. Ailamaki, \u201cHere are my Data Files. Here are my Queries. Where are my Results?,\u201d in Proc. of the 5th CIDR Biennial Conference on Innovative Data Systems Research (CIDR\u201911)<\/em>, 2011.<\/li>\n
  29. Michael and K. Miller, \u201cBig Data: New opportunities and new challenges,\u201d Computer (Long. Beach. Calif).<\/em>, vol. 46, no. 6, 2013.<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

    Chaudhuri, “What next?: a half-dozen data management research goals for big data and the cloud,” in Proc. of the 31st PODS Symposium on Principles of Database Systems A.K and Madam Prabhu D., “No problem with Big Data. What do you mean by Big?,” Informatics, no. October, pp. 30–32, 2012. Atkinson, D. Dewitt, D. Maier, K. […]<\/p>\n","protected":false},"author":11,"featured_media":0,"parent":0,"menu_order":5,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-17","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"http:\/\/vargas-solar.com\/datacentric-sciences\/wp-json\/wp\/v2\/pages\/17","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/vargas-solar.com\/datacentric-sciences\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"http:\/\/vargas-solar.com\/datacentric-sciences\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"http:\/\/vargas-solar.com\/datacentric-sciences\/wp-json\/wp\/v2\/users\/11"}],"replies":[{"embeddable":true,"href":"http:\/\/vargas-solar.com\/datacentric-sciences\/wp-json\/wp\/v2\/comments?post=17"}],"version-history":[{"count":2,"href":"http:\/\/vargas-solar.com\/datacentric-sciences\/wp-json\/wp\/v2\/pages\/17\/revisions"}],"predecessor-version":[{"id":40,"href":"http:\/\/vargas-solar.com\/datacentric-sciences\/wp-json\/wp\/v2\/pages\/17\/revisions\/40"}],"wp:attachment":[{"href":"http:\/\/vargas-solar.com\/datacentric-sciences\/wp-json\/wp\/v2\/media?parent=17"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}