サクサク読めて、アプリ限定の機能も多数！
トップへ戻る
参議院選挙2025
www.umiacs.umd.edu/~jimmylin
Cloud9 is a MapReduce library for Hadoop designed to serve as both a teaching tool and to support research in data-intensive text processing. MapReduce is a programming model for expressing distributed computations on massive datasets and an execution framework for large-scale data processing on clusters of commodity servers. Hadoop provides an open-source implementation of the programming model.
This page describes the code used to run experiments in the following paper: Jimmy Lin and Michael Schatz. Design Patterns for Efficient Graph Algorithms in MapReduce. Proceedings of the 2010 Workshop on Mining and Learning with Graphs Workshop (MLG-2010), July 2010, Washington, D.C. There's code in Cloud9 that illustrates three different design patterns for graph algorithms in MapReduce using Pag
Design Patterns for Efficient Graph Algorithms in MapReduce Jimmy Lin and Michael Schatz University of Maryland, College Park {jimmylin,mschatz}@umd.edu ABSTRACT Graphs are analyzed in many important contexts, includ- ing ranking search results based on the hyperlink struc- ture of the world wide web, module detection of protein- protein interaction networks, and privacy analysis of social network
A Hadoop toolkit for web-scale information retrieval research Ivory is a Hadoop toolkit for web-scale information retrieval research that features a retrieval engine based on Markov Random Fields, appropriately named SMRF (Searching with Markov Random Fields). Ivory takes full advantage of the Hadoop distributed environment (the MapReduce programming model and the underlying distributed file syste
Data-Intensive Information Processing Applications (Spring 2010) Course: INFM718G/CMSC838G Time: Tuesday, 2:00-4:45pm Location: HBK 2119 Instructors: Jimmy Lin, () and Nitin Madnani, () This course is about scalable approaches to processing large amounts of information (terabytes and even petabytes). We focus mostly on MapReduce, which is presently the most accessible and practical means of co
Cloud9: Working with counters by Jimmy Lin (Page first created: 31 Oct 2008; last updated: Built-In Counters Counters are lightweight objects in Hadoop that allow you to keep track of system progress in both the map and reduce stages of processing. By default, Hadoop defines a number of standard counters in "groups"; these show up in the jobtracker Webapp, giving you information such as "Map input
Cloud9 was designed to serve as both a teaching tool and to support research in text processing. It was used in "cloud computing" courses at the University of Maryland in Spring 2008 and Fall 2008. The library itself is available via anonymous Subversion checkout. Like Hadoop itself, Cloud9 is distributed under the Apache License. Starting Points Subversion access: https://subversion.u
What are the lab sessions? The lectures focus on concepts and theory, but there's often quite a gap between that and actually getting your code to run. There are a lot of details that are best practiced in a hands-on/tutorial environment with peers. Remember to bring your laptops! The lab sessions will be loosely structured: I will discuss algorithms, share tips and tricks, answer any questi
このページを最初にブックマークしてみませんか？
『www.umiacs.umd.edu』の新着エントリーを見る
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く
