R GC() CMD 批处理执行时间上的垃圾收集

Posted 2023-02-16

【中文标题】R GC() CMD 批处理执行时间上的垃圾收集

【英文标题】：R GC() Garbage collection on CMD Batch execution time

【发布时间】：2017-06-26 18:55:00

【问题描述】：

在服务器上执行 CMD 批处理时，R 脚本需要很长时间才能启动，这在 ROut 文件中得到了证实。 打开 Verbose 显示所有脚本的 GC 运行大约 10 分钟，这些脚本在 RStudio 中运行良好

这是任务调度程序中的命令行 C:\Program Files\R\R-3.3.2\bin\x64\R.exe” CMD BATCH "\Server-Directory\RFilename.R"

ROut 文件如下所示/ 正如我所说，在 RStudio 中运行时不会发生这种情况。

任何帮助将不胜感激

---

'verbose' and 'quietly' are both true; being verbose then ..
now dyn.load("C:/Program Files/R/R-3.3.2/library/methods/libs/x64/methods.dll") ...

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Garbage collection 1 = 0+0+1 (level 2) ... 
5.4 Mbytes of cons cells used (29%)
1.4 Mbytes of vectors used (17%)
Garbage collection 2 = 0+1+1 (level 1) ... 
15.6 Mbytes of cons cells used (83%)
7.4 Mbytes of vectors used (94%)
Garbage collection 3 = 0+1+2 (level 2) ... 
17.4 Mbytes of cons cells used (71%)
7.9 Mbytes of vectors used (68%)
Garbage collection 4 = 0+1+3 (level 2) ... 
23.0 Mbytes of cons cells used (73%)
10.5 Mbytes of vectors used (72%)
Garbage collection 5 = 0+1+4 (level 2) ... 
27.2 Mbytes of cons cells used (68%)
11.7 Mbytes of vectors used (59%)
Garbage collection 6 = 0+1+5 (level 2) ... 
27.2 Mbytes of cons cells used (54%)
17.9 Mbytes of vectors used (66%)
Garbage collection 7 = 0+1+6 (level 2) ... 
27.2 Mbytes of cons cells used (54%)
27.2 Mbytes of vectors used (71%)
Garbage collection 8 = 0+1+7 (level 2) ... 
27.2 Mbytes of cons cells used (54%)
36.5 Mbytes of vectors used (74%)
Garbage collection 9 = 0+1+8 (level 2) ... 
27.2 Mbytes of cons cells used (54%)
49.0 Mbytes of vectors used (76%)
Garbage collection 10 = 0+1+9 (level 2) ... 
27.4 Mbytes of cons cells used (54%)
63.5 Mbytes of vectors used (75%)
Garbage collection 11 = 0+1+10 (level 2) ... 
27.4 Mbytes of cons cells used (54%)
80.3 Mbytes of vectors used (76%)
Garbage collection 12 = 0+1+11 (level 2) ... 
27.4 Mbytes of cons cells used (54%)
102.6 Mbytes of vectors used (78%)
Garbage collection 13 = 0+1+12 (level 2) ... 
27.4 Mbytes of cons cells used (54%)
130.4 Mbytes of vectors used (79%)
Garbage collection 14 = 0+1+13 (level 2) ... 
29.3 Mbytes of cons cells used (58%)
164.4 Mbytes of vectors used (80%)
Garbage collection 15 = 0+1+14 (level 2) ... 
33.9 Mbytes of cons cells used (54%)
204.1 Mbytes of vectors used (80%)
Garbage collection 16 = 0+1+15 (level 2) ... 
33.9 Mbytes of cons cells used (54%)
248.8 Mbytes of vectors used (81%)
Garbage collection 17 = 1+1+15 (level 0) ... 
62.5 Mbytes of cons cells used (100%)
300.4 Mbytes of vectors used (98%)
Garbage collection 18 = 1+1+16 (level 2) ... 
62.5 Mbytes of cons cells used (81%)
298.4 Mbytes of vectors used (81%)
Garbage collection 19 = 1+1+17 (level 2) ... 
63.2 Mbytes of cons cells used (67%)
364.6 Mbytes of vectors used (58%)
Garbage collection 20 = 1+1+18 (level 2) ... 
94.6 Mbytes of cons cells used (82%)
541.5 Mbytes of vectors used (72%)
Garbage collection 21 = 1+1+19 (level 2) ... 
115.7 Mbytes of cons cells used (82%)
562.3 Mbytes of vectors used (62%)
Garbage collection 22 = 1+1+20 (level 2) ... 
140.9 Mbytes of cons cells used (82%)
577.8 Mbytes of vectors used (64%)
Garbage collection 23 = 1+1+21 (level 2) ... 
171.2 Mbytes of cons cells used (82%)
595.1 Mbytes of vectors used (65%)
Garbage collection 24 = 1+1+22 (level 2) ... 
207.6 Mbytes of cons cells used (83%)
615.9 Mbytes of vectors used (68%)
Garbage collection 25 = 1+1+23 (level 2) ... 
251.3 Mbytes of cons cells used (83%)
656.9 Mbytes of vectors used (60%)
Garbage collection 26 = 1+1+24 (level 2) ... 
303.6 Mbytes of cons cells used (83%)
686.9 Mbytes of vectors used (63%)
Garbage collection 27 = 1+1+25 (level 2) ... 
366.5 Mbytes of cons cells used (83%)
722.8 Mbytes of vectors used (66%)
Garbage collection 28 = 1+1+26 (level 2) ... 
441.9 Mbytes of cons cells used (83%)
798.1 Mbytes of vectors used (61%)
Garbage collection 29 = 1+1+27 (level 2) ... 
532.4 Mbytes of cons cells used (83%)
850.1 Mbytes of vectors used (65%)
Garbage collection 30 = 1+1+28 (level 2) ... 
641.0 Mbytes of cons cells used (83%)
912.6 Mbytes of vectors used (70%)
Garbage collection 31 = 1+1+29 (level 2) ... 
771.4 Mbytes of cons cells used (83%)
987.8 Mbytes of vectors used (63%)
Garbage collection 32 = 1+1+30 (level 2) ... 
927.8 Mbytes of cons cells used (83%)
1141.0 Mbytes of vectors used (60%)
Garbage collection 33 = 1+1+31 (level 2) ... 
1115.5 Mbytes of cons cells used (83%)
1248.3 Mbytes of vectors used (66%)
Garbage collection 34 = 1+1+32 (level 2) ... 
1261.6 Mbytes of cons cells used (78%)
1885.0 Mbytes of vectors used (83%)

【问题讨论】：

改用 Rscript.exe 吗？

您是否在同一台机器上运行 Rstudio？他们有相同数量的 RAM 吗？如果没有reproducible example，要帮助您并不容易。

机器有 32GB 内存，测试是在同一台机器上和另一台机器上进行的。我想知道在运行 CMD Batch 与 RStudio 时 Java 是否有区别？如果可以的话，我会分享代码，但这是在任何代码执行之前，所以我怀疑它会有所帮助。

刚刚尝试了一个空的脚本文件，结果相同。

RScript 没有这个问题。感谢 A.Webb 的建议

【参考方案1】：

不是对 CMD BATCH 的修复，但 A.Webb 建议改用 RScript。 这有效，因为脚本现在执行得非常快，但它缺少 ROut 文件。

曾经： C:\Program Files\R\R-3.3.2\bin\x64\R.exe” CMD BATCH "\Server-Directory\RFilename.R"

现在： C:\Program Files\R\R-3.3.2\bin\x64\RScript.exe” "\Server-Directory\RFilename.R"