It’s tough to argue with R as a high-quality, cross-platform, open source statistical software product—unless you’re in the business of crunching Big Data. This concise book introduces you to several strategies for using R to analyze large datasets. You’ll learn the basics of Snow, Multicore, Parallel, and some Hadoop-related tools, including how to find them, how to use them, when they work well, and when they don’t.
With these packages, you can overcome R’s single-threaded nature by spreading work across multiple CPUs, or offloading work to multiple machines to address R’s memory barrier.
Snow: works well in a traditional cluster environment
Multicore: popular for multiprocessor and multicore computers
Parallel: part of the upcoming R 2.14.0 release
R+Hadoop: provides low-level access to a popular form of cluster computing
RHIPE: uses Hadoop’s power with R’s language and interactive shell
Segue: lets you use Elastic MapReduce as a backend for lapply-style operations
具體描述
讀後感
評分
評分
評分
評分
用戶評價
不錯的書 的確不錯
评分以前覺得不明覺厲的東西，嘗試便也掌握瞭
评分以前覺得不明覺厲的東西，嘗試便也掌握瞭
评分還行 就是有點過時瞭
评分看得不是很仔細，以後說不定有用吧，就是有點短
相關圖書
本站所有內容均為互聯網搜索引擎提供的公開搜索信息，本站不存儲任何數據與內容，任何內容與數據均與本站無關，如有需要請聯繫相關搜索引擎包括但不限於百度，google,bing,sogou 等
© 2025 qciss.net All Rights Reserved. 小哈圖書下載中心 版权所有