Map-reduce-merge: simplified relational data processing on large clusters Export

@inproceedings{citeulike:2326762, abstract = {Map-Reduce is a programming model that enables easy development of scalable parallel applications to process a vast amount of data on large clusters of commodity machines. Through a simple interface with two functions, map and reduce, this model facilitates parallel implementation of many real-world tasks such as data processing jobs for search engines and machine learning.}, address = {New York, NY, USA}, author = {Yang, Hung C. and Dasdan, Ali and Hsiao, Ruey L. and Parker, D. Stott}, booktitle = {SIGMOD '07: Proceedings of the 2007 ACM SIGMOD international conference on Management of data}, citeulike-article-id = {2326762}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1247480.1247602}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1247480.1247602}, doi = {10.1145/1247480.1247602}, isbn = {978-1-59593-686-8}, keywords = {algorithm, cluster, clustering, compsci, cs, data, distributed, mapreduce, parallel}, location = {Beijing, China}, pages = {1029--1040}, posted-at = {2008-06-17 06:14:02}, priority = {2}, publisher = {ACM}, title = {Map-reduce-merge: simplified relational data processing on large clusters}, url = {http://dx.doi.org/10.1145/1247480.1247602}, year = {2007} }

TY - CONF ID - citeulike:2326762 L3 - citeulike-article-id:2326762 N2 - Map-Reduce is a programming model that enables easy development of scalable parallel applications to process a vast amount of data on large clusters of commodity machines. Through a simple interface with two functions, map and reduce, this model facilitates parallel implementation of many real-world tasks such as data processing jobs for search engines and machine learning. CY - Beijing, China SN - 978-1-59593-686-8 AD - New York, NY, USA EP - 1040 TI - Map-reduce-merge: simplified relational data processing on large clusters PB - ACM T2 - SIGMOD '07: Proceedings of the 2007 ACM SIGMOD international conference on Management of data SP - 1029 KW - algorithm KW - cluster KW - clustering KW - compsci KW - cs KW - data KW - distributed KW - mapreduce KW - parallel AU - Yang, Hung AU - Dasdan, Ali AU - Hsiao, Ruey AU - Parker, Stott PY - 2007/// UR - http://dx.doi.org/10.1145/1247480.1247602 ER -