[R] Package parallel left orphan processes, how to clean-up?

Bin Ye robin.ye at gmail.com
Tue Jan 29 20:05:59 CET 2013


I've using package DEXSeq that implements functions with nCores for
speed-up. The functions work fine, but I found out that the children
processes were not terminated, they still hold memory, and new command
will start up new children processes. So if I don't manually kill those
orphan processes, they will cause problem. I was qlogin to SGE cluster
node to run R. From our administrator, I heard that at least another R
package zinba, which based on parallel too, met the same problem. I tried
to use functions from multicore, such as kill(children()) and collect(),
they just return NULL, but didn't do anything. I was wondering if anyone
has met this problem before? Beside kill in command line, is there any way
in R that I can use to clean-up the orphan processes?

My session info is attached below. Thank you!


R version 2.15.1 (2012-06-22)
Platform: x86_64-redhat-linux-gnu (64-bit)

   [1] LC_CTYPE=en_US.iso885915       LC_NUMERIC=C
   [3] LC_TIME=en_US.iso885915        LC_COLLATE=en_US.iso885915
   [5] LC_MONETARY=en_US.iso885915    LC_MESSAGES=en_US.iso885915
   [7] LC_PAPER=C                     LC_NAME=C
   [9] LC_ADDRESS=C                   LC_TELEPHONE=C

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base

other attached packages:
[1] DEXSeq_1.4.0         AnnotationDbi_1.20.3 Biobase_2.18.0
[4] BiocGenerics_0.4.0   RSQLite_0.11.2       DBI_0.2-5

loaded via a namespace (and not attached):
   [1] annotate_1.36.0       biomaRt_2.14.0        clusterProfiler_1.6.0
   [4] colorspace_1.2-0      DESeq_1.10.1          dichromat_1.2-4
   [7] digest_0.5.2          DO.db_2.5.0           DOSE_1.4.0
[10] genefilter_1.40.0     geneplotter_1.36.0    ggplot2_0.9.3
[13] GO.db_2.8.0           GOSemSim_1.16.1       grid_2.15.1
[16] gtable_0.1.2          hwriter_1.3           igraph_0.5.5-4
[19] IRanges_1.16.4        KEGG.db_2.8.0         labeling_0.1
[22] lattice_0.20-10       MASS_7.3-22           munsell_0.4
[25] parallel_2.15.1       plyr_1.8              proto_0.3-9.2
[28] qvalue_1.32.0         RColorBrewer_1.0-5    RCurl_1.95-3
[31] reshape2_1.2.2        scales_0.2.3          splines_2.15.1
[34] statmod_1.4.16        stats4_2.15.1         stringr_0.6.2
[37] survival_2.36-14      tcltk_2.15.1          tools_2.15.1
[40] XML_3.95-0.1          xtable_1.7-0

More information about the R-help mailing list