[Rd] Environments and parallel processing

[Clark Fitzgerald]

+1 to what Gabor and Ralf said.

In this case the memory address can be misleading. My understanding is that
the environments in all the processes, 1 parent and 2 child, have the
*same* memory address, but once you write to them the operating system
makes copies and maps the address to a *different* physical address. This
is the copy-on-write UNIX fork model.

The example below shows 3 processes that all use the same address for the
environment env1, yet there must be 3 different environments, because
env1$x has 3 different values simultaneously.

-Clark


library(parallel)
env1 <- new.env()
env1$x = 0
cl <- makeCluster(2, type="FORK")

# Now we write to the environment, and env1$x has two distinct values
clusterEvalQ(cl, env1$x <- rnorm(1))
# [[1]]
# [1] -1.296702
#
# [[2]]
# [1] -0.4001104

# The environments in the 2 child processes still have the same address,
# which is the same as the original address
parLapply(cl, 1:4, function(x) capture.output(str(env1)))
env1

# The original x is unchanged
env1$x

stopCluster(cl)


On Wed, Sep 12, 2018 at 11:31 AM Ralf Stubner <ralf.stubner using daqana.com>
wrote:

> On 12.09.2018 20:20, Gábor Csárdi wrote:
> > This is all normal, a fork cluster works with processes, that do not
> > share memory.
>
> And if you are after shared-memory parallelism, you can try the 'Rdsm'
> package: https://cran.r-project.org/package=Rdsm
>
> Greetings
> Ralf
>
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