{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T11:38:20Z","timestamp":1791459500701,"version":"4.3.4"},"reference-count":9,"publisher":"Association for Computing Machinery (ACM)","issue":"12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2012,8]]},"abstract":"\n The current research focus on Big Data systems calls for a rethinking of data generation methods. The traditional sequential data generation approach is not well suited to large-scale systems as generating a terabyte of data may require days or even weeks depending on the number of constraints imposed on the generated model. We demonstrate\n Myriad<\/jats:italic>\n , a new data generation toolkit that enables the specification of semantically rich data generator programs that can scale out linearly in a shared-nothing environment. Data generation programs built on top of\n Myriad<\/jats:italic>\n implement an efficient parallel execution strategy leveraged by the extensive use of pseudo-random number generators with random access support.\n <\/jats:p>","DOI":"10.14778\/2367502.2367530","type":"journal-article","created":{"date-parts":[[2014,6,24]],"date-time":"2014-06-24T12:17:57Z","timestamp":1403612277000},"page":"1890-1893","source":"Crossref","is-referenced-by-count":22,"title":["Myriad"],"prefix":"10.14778","volume":"5","author":[{"given":"Alexander","family":"Alexandrov","sequence":"first","affiliation":[{"name":"Technische Universit\u00e4t Berlin, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kostas","family":"Tzoumas","sequence":"additional","affiliation":[{"name":"Technische Universit\u00e4t Berlin, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Volker","family":"Markl","sequence":"additional","affiliation":[{"name":"Technische Universit\u00e4t Berlin, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2012,8]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Apache Hadoop. http:\/\/hadoop.apache.org. Apache Hadoop. http:\/\/hadoop.apache.org."},{"key":"e_1_2_1_2_1","unstructured":"Myriad Toolkit. http:\/\/www.myriad-toolkit.com. Myriad Toolkit. http:\/\/www.myriad-toolkit.com."},{"key":"e_1_2_1_3_1","unstructured":"Transaction Processing Performance Council. http:\/\/www.tpc.org. Transaction Processing Performance Council. http:\/\/www.tpc.org."},{"key":"e_1_2_1_4_1","volume-title":"Architectures and Systems for Big Data (ASBD)","author":"Alexandrov A.","year":"2011","unstructured":"A. Alexandrov , B. Schiefer , J. Poelman , S. Ewen , T. Bodner , and V. Markl . Myriad -- Parallel Data Generation on Shared-Nothing Architectures . In Architectures and Systems for Big Data (ASBD) , 2011 . 10.1145\/2377978.2377983 A. Alexandrov, B. Schiefer, J. Poelman, S. Ewen, T. Bodner, and V. Markl. Myriad -- Parallel Data Generation on Shared-Nothing Architectures. In Architectures and Systems for Big Data (ASBD), 2011. 10.1145\/2377978.2377983"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/1276301.1276305"},{"key":"e_1_2_1_6_1","first-page":"1243","volume-title":"VLDB","author":"Houkj\u00e6r K.","year":"2006","unstructured":"K. Houkj\u00e6r , K. Torp , and R. Wind . Simple and Realistic Data Generation . In VLDB , pages 1243 -- 1246 , 2006 . K. Houkj\u00e6r, K. Torp, and R. Wind. Simple and Realistic Data Generation. In VLDB, pages 1243--1246, 2006."},{"key":"e_1_2_1_7_1","first-page":"133","volume-title":"Using Kronecker Multiplication. In PKDD","author":"Leskovec J.","year":"2005","unstructured":"J. Leskovec , D. Chakrabarti , J. M. Kleinberg , and C. Faloutsos . Realistic, Mathematically Tractable Graph Generation and Evolution , Using Kronecker Multiplication. In PKDD , pages 133 -- 145 , 2005 . 10.1007\/11564126_17 J. Leskovec, D. Chakrabarti, J. M. Kleinberg, and C. Faloutsos. Realistic, Mathematically Tractable Graph Generation and Evolution, Using Kronecker Multiplication. In PKDD, pages 133--145, 2005. 10.1007\/11564126_17"},{"key":"e_1_2_1_8_1","unstructured":"J. Manyika M. Chui B. Brown J. Bughin R. Dobbs C. Roxburgh and A. H. Byers. Big Data: The Next Frontier for Innovation Competition and Productivity. http:\/\/www.mckinsey.com\/insights\/mgi\/research\/technology_and_innovation\/big_data_the_next_frontier_for_innovation May 2011. J. Manyika M. Chui B. Brown J. Bughin R. Dobbs C. Roxburgh and A. H. Byers. Big Data: The Next Frontier for Innovation Competition and Productivity. http:\/\/www.mckinsey.com\/insights\/mgi\/research\/technology_and_innovation\/big_data_the_next_frontier_for_innovation May 2011."},{"key":"e_1_2_1_9_1","first-page":"41","volume-title":"TPCTC","author":"Rabl T.","year":"2010","unstructured":"T. Rabl , M. Frank , H. M. Sergieh , and H. Kosch . A Data Generator for Cloud-Scale Benchmarking . In TPCTC , pages 41 -- 56 , 2010 . T. Rabl, M. Frank, H. M. Sergieh, and H. Kosch. A Data Generator for Cloud-Scale Benchmarking. In TPCTC, pages 41--56, 2010."}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/2367502.2367530","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T10:49:18Z","timestamp":1672224558000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/2367502.2367530"}},"subtitle":["scalable and expressive data generation"],"short-title":[],"issued":{"date-parts":[[2012,8]]},"references-count":9,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2012,8]]}},"alternative-id":["10.14778\/2367502.2367530"],"URL":"https:\/\/doi.org\/10.14778\/2367502.2367530","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2012,8]]}}}