June 2020
Beginner to intermediate
522 pages
9h 6m
Chinese
Content preview from R 语言经典实例（原书第 2 版）
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#>
#> value
plan(multiprocess)
tic("simulate pi - parallel")
sims_list <- future_map(draw_list, simulate_pi)
toc()
#> simulate pi - parallel: 26.33 sec elapsed
mean(unlist(sims_list))
#> [1] 3.14
前面的示例在 MacBook Pro 上运行，包含有四个物理内核和两个虚拟内核。当你并行运
行代码时，最佳情况是运行时间减少到 1/（物理内核数）。通过四个物理内核，你可以
看到并行运行时比单线程运行快得多，但不是单线程运行时的四分之一。内核间移动数
据总会花一些时间，因此你永远不会遇到最佳情况。每次迭代产生的数据越多，你在并
行化方面的速度提升就越少。
12.21.4 另请参阅
参见 12.22 节。
12.22 远程并行运行 R 代码
12.22.1 问题
你可以访问许多远程计算机，需要在它们之间并行运行代码。
12.22.2 解决方案
在多台机器上并行运行代码最初可能很难设置。但是，如果我们从一些关键预设条件开
始，那么该过程的成功概率要高得多。
首要条件是：
•
你可以使用以前生成的 SSH 密钥，从主机到每个远程节点进行保密通信（ssh）而无
须密码。
•
远程节点都安装了 R（理想情况下是 R 的相同版本）。
•
设置路径，以便你可以从 SSH 运行 Rscript。
•
远程节点安装了 furrr 包（该添加包将会安装 ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.