global base {pbdMPI} | R Documentation |
These functions are global base functions applying on distributed data for all ranks.
comm.length(x, comm = .pbd_env$SPMD.CT$comm) comm.sum(..., na.rm = TRUE, comm = .pbd_env$SPMD.CT$comm) comm.mean(x, na.rm = TRUE, comm = .pbd_env$SPMD.CT$comm) comm.var(x, na.rm = TRUE, comm = .pbd_env$SPMD.CT$comm) comm.sd(x, na.rm = TRUE, comm = .pbd_env$SPMD.CT$comm)
x |
a vector. |
... |
as in |
na.rm |
logical, if remove |
comm |
a communicator number. |
These functions will apply globally length()
, sum()
,
mean()
, var()
, and sd()
.
The global values are returned to all ranks.
Wei-Chen Chen wccsnow@gmail.com, George Ostrouchov, Drew Schmidt, Pragneshkumar Patel, and Hao Yu.
Programming with Big Data in R Website: http://r-pbd.org/
## Not run: ### Save code in a file "demo.r" and run with 2 processors by ### SHELL> mpiexec -np 2 Rscript demo.r ### Initial. suppressMessages(library(pbdMPI, quietly = TRUE)) init() if(comm.size() != 2){ comm.cat("2 processors are requried.\n", quiet = TRUE) finalize() } ### Examples. a <- 1:(comm.rank() + 1) b <- comm.length(a) comm.print(b) b <- comm.sum(a) comm.print(b) b <- comm.mean(a) comm.print(b) b <- comm.var(a) comm.print(b) b <- comm.sd(a) comm.print(b) ### Finish. finalize() ## End(Not run)