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商品描述
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
商品描述(中文翻譯)
很難否認 R 是一款高品質、跨平台的開源統計軟體產品——除非你從事大數據分析。本書簡明扼要地介紹了幾種使用 R 來分析大型數據集的策略。你將學習 Snow、Multicore、Parallel 以及一些與 Hadoop 相關的工具的基本知識,包括如何找到這些工具、如何使用它們、何時它們運作良好以及何時不適用。
透過這些套件,你可以克服 R 的單執行緒特性,將工作分散到多個 CPU 上,或將工作卸載到多台機器上,以解決 R 的記憶體限制。
- **Snow:** 在傳統集群環境中運作良好
- **Multicore:** 在多處理器和多核心電腦中非常受歡迎
- **Parallel:** 是即將推出的 R 2.14.0 版本的一部分
- **R+Hadoop:** 提供對一種流行的集群計算形式的低層次訪問
- **RHIPE:** 結合 Hadoop 的強大功能與 R 的語言和互動式命令行
- **Segue:** 讓你可以將 Elastic MapReduce 作為 lapply 風格操作的後端使用