%0 Report %1 IRP-TR-08-05 %A Chen, Shimin %A Schlosser, Steven W. %D 2008 %K awm2010 awmhadoop hadoop map meets reduce varieties wider %T Map-Reduce Meets Wider Varieties of Applications. %U http://www.pittsburgh.intel-research.net/~chensm/papers/IRP-TR-08-05.pdf %X Recent studies and industry practices build data-center-scale computer systems to meet the high storage and processing demands of data-intensive and compute-intensive applications, such as web searches. The Map-Reduce programming model is one of the most popular programming paradigms on these systems. In this paper, we report our experiences and insights gained from implementing three data-intensive and compute-intensive tasks that have different characteristics from previous studies: a large-scale machine learning computation, a physical simulation task, and a digital media processing task. We identify desirable features and places to improve in the Map-Reduce model. Our goal is to better understand such large-scale computation and data processing in order to design better supports for them.

@techreport{IRP-TR-08-05, abstract = {Recent studies and industry practices build data-center-scale computer systems to meet the high storage and processing demands of data-intensive and compute-intensive applications, such as web searches. The Map-Reduce programming model is one of the most popular programming paradigms on these systems. In this paper, we report our experiences and insights gained from implementing three data-intensive and compute-intensive tasks that have different characteristics from previous studies: a large-scale machine learning computation, a physical simulation task, and a digital media processing task. We identify desirable features and places to improve in the Map-Reduce model. Our goal is to better understand such large-scale computation and data processing in order to design better supports for them.}, added-at = {2010-05-10T09:33:14.000+0200}, author = {Chen, Shimin and Schlosser, Steven W.}, biburl = {https://www.bibsonomy.org/bibtex/2e3b284e09d2a3fd3992f7eb70ddd061a/muehlburger}, interhash = {77d8b41029ab54cd6c78ca06d0ad4d59}, intrahash = {e3b284e09d2a3fd3992f7eb70ddd061a}, keywords = {awm2010 awmhadoop hadoop map meets reduce varieties wider}, timestamp = {2010-06-23T08:22:48.000+0200}, title = {Map-Reduce Meets Wider Varieties of Applications.}, url = {http://www.pittsburgh.intel-research.net/~chensm/papers/IRP-TR-08-05.pdf}, year = 2008 }