Parallel R
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, M...
| Autor principal: | |
|---|---|
| Otros Autores: | , , , |
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Sebastopol, CA :
O'Reilly
2011.
|
| Edición: | First edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628001906719 |
| Sumario: | 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 memo |
|---|---|
| Notas: | Description based upon print version of record. |
| Descripción Física: | 1 online resource (122 p.) |
| Bibliografía: | Includes bibliographical references. |
| ISBN: | 9781306813648 9781449320331 9781449320348 |
