Enable simple network of workstations (SNOW)-style parallel evaluation

Description

This class is used to parameterize simple network of workstations (SNOW) parallel evaluation on one or several physical computers. snowWorkers() chooses the number of workers based on global user preference (options(mc.cores=...)), or the minimum of 8 and the number of detected cores (detectCores()).

Usage

## constructor 
## ------------------------------------

SnowParam(workers = snowWorkers(), type=c("SOCK", "MPI", "FORK"),
          tasks = 0L, catch.errors=TRUE, stop.on.error = TRUE, 
          progressbar = FALSE, RNGseed = NULL,
          timeout = 30L * 24L * 60L * 60L,
          log = FALSE, threshold = "INFO", logdir = NA_character_, 
          resultdir = NA_character_, jobname = "BPJOB", ...)

## coercion 
## ------------------------------------

## as(SOCKcluster, SnowParam)
## as(spawnedMPIcluster,SnowParam)

## detect workers 
## ------------------------------------

snowWorkers()

Arguments

Details

SnowParam is used for distributed memory computing and supports 2 cluster types: ‘SOCK’ (default) and ‘MPI’. The SnowParam builds on infrastructure in the snow and parallel packages and provides the additional features of error handling, logging and writing out results. When not specified, the default number of workers is determined by snowWorkers() which is parallel::detectCores() - 2. Machines with 3 or less cores are assigned a single worker.

error handling:

The catch.errors field has been deprecated.

By default all computations are attempted and partial results are returned with any error messages.

• catch.errors (DEPRECATED) determines whether errors are caught and returned with other results. When TRUE, all computations are attempted and output contains both errors and successfully completed results. When FALSE, the job is terminated as soon as the first error is hit and only the error message is returned (no results); this is the default behavior of the parent packages, e.g., parallel, snow, foreach.

• stop.on.error A logical. Stops all jobs as soon as one job fails or wait for all jobs to terminate. When FALSE, the return value is a list of successful results along with error messages as 'conditions'.

• The bpok(x) function returns a logical() vector that is FALSE for any jobs that threw an error. The input x is a list output from a bp*apply function such as bplapply or bpmapply.

logging:

When log = TRUE the futile.logger package is loaded on the workers. All log messages written in the futile.logger format are captured by the logging mechanism and returned real-time (i.e., as each task completes) instead of after all jobs have finished.

Messages sent to stdout and stderr are returned to the workspace by default. When log = TRUE these are diverted to the log output. Those familiar with the outfile argument to makeCluster can think of log = FALSE as equivalent to outfile = NULL; providing a logdir is the same as providing a name for outfile except that BiocParallel writes a log file for each task.

The log output includes additional statistics such as memory use and task runtime. Memory use is computed by calling gc(reset=TRUE) before code evaluation and gc() (no reseet) after. The output of the second gc() call is sent to the log file. There are many ways to track memory use - this particular approach was taken because it is consistent with how the BatchJobs package reports memory on the workers.

log and result files:

Results and logs can be written to a file instead of returned to the workspace. Writing to files is done from the master as each task completes. Options can be set with the logdir and resultdir fields in the constructor or with the accessors, bplogdir and bpresultdir.

random number generation:

MulticoreParam and SnowParam use the random number generation support from the parallel package. These params are snow-derived clusters so the arguments for multicore-derived functions such as mc.set.seed and mc.reset.stream do not apply.

Random number generation is controlled through the param argument, RNGseed which is passed to parallel::clusterSetRNGStream. clusterSetRNGStream uses the L'Ecuyer-CMRG random number generator and distributes streams to the members of a cluster. If RNGseed is not NULL it serves as the seed to the streams, otherwise the streams are set from the current seed of the master process after selecting the L'Ecuyer generator. See ?clusterSetRNGStream for more details.

NOTE: The PSOCK cluster from the parallel package does not support cluster options scriptdir and useRscript. PSOCK is not supported because these options are needed to re-direct to an alternate worker script located in BiocParallel.

Constructor

SnowParam(workers = snowWorkers(), type=c("SOCK", "MPI"), tasks = 0L, catch.errors = TRUE, stop.on.error = FALSE, progressbar = FALSE, RNGseed = NULL, timeout = Inf, log = FALSE, threshold = "INFO", logdir = NA_character_, resultdir = NA_character_, jobname = "BPJOB", ...):

Return an object representing a SNOW cluster. The cluster is not created until bpstart is called. Named arguments in ... are passed to makeCluster.

Accessors: Logging and results

In the following code, x is a SnowParam object.

bpprogressbar(x), bpprogressbar(x) <- value: Get or set the value to enable text progress bar. value must be a logical(1).

bpjobname(x), bpjobname(x) <- value: Get or set the job name.

bpRNGseed(x), bpRNGseed(x) <- value: Get or set the seed for random number generaton. value must be a numeric(1).

bplog(x), bplog(x) <- value: Get or set the value to enable logging. value must be a logical(1).

bpthreshold(x), bpthreshold(x) <- value: Get or set the logging threshold. value must be a character(1) string of one of the levels defined in the futile.logger package: “TRACE”, “DEBUG”, “INFO”, “WARN”, “ERROR”, or “FATAL”.

bplogdir(x), bplogdir(x) <- value: Get or set the directory for the log file. value must be a character(1) path, not a file name. The file is written out as BPLOG.out. If no logdir is provided and bplog=TRUE log messages are sent to stdout.

bpresultdir(x), bpresultdir(x) <- value: Get or set the directory for the result files. value must be a character(1) path, not a file name. Separate files are written for each job with the prefix TASK (e.g., TASK1, TASK2, etc.). When no resultdir is provided the results are returned to the session as list.

Accessors: Back-end control

In the code below x is a SnowParam object. See the ?BiocParallelParam man page for details on these accessors.

bpworkers(x), bpworkers(x) <- value, bpnworkers(x)

bptasks(x), bptasks(x) <- value

bpstart(x)

bpstop(x)

bpisup(x)

bpbackend(x), bpbackend(x) <- value

Accessors: Error Handling

In the code below x is a SnowParam object. See the ?BiocParallelParam man page for details on these accessors.

bpcatchErrors(x), bpcatchErrors(x) <- value

bpstopOnError(x), bpstopOnError(x) <- value

Methods: Evaluation

In the code below BPPARAM is a SnowParam object. Full documentation for these functions are on separate man pages: see ?bpmapply, ?bplapply, ?bpvec, ?bpiterate and ?bpaggregate.

bpmapply(FUN, ..., MoreArgs=NULL, SIMPLIFY=TRUE, USE.NAMES=TRUE, BPPARAM=bpparam())

bplapply(X, FUN, ..., BPPARAM=bpparam())

bpvec(X, FUN, ..., AGGREGATE=c, BPPARAM=bpparam())

bpiterate(ITER, FUN, ..., BPPARAM=bpparam())

bpaggregate(x, data, FUN, ..., BPPARAM=bpparam())

Methods: Other

In the code below x is a SnowParam object.

show(x): Displays the SnowParam object.

bpok(x): Returns a logical() vector: FALSE for any jobs that resulted in an error. x is the result list output by a BiocParallel function such as bplapply or bpmapply.

Coercion

as(from, "SnowParam"): Creates a SnowParam object from a SOCKcluster or spawnedMPIcluster object. Instances created in this way cannot be started or stopped.

Author(s)

Martin Morgan and Valerie Obenchain.

See Also

• register for registering parameter classes for use in parallel evaluation.

• MulticoreParam for computing in shared memory

• BatchJobsParam for computing with cluster schedulers

• DoparParam for computing with foreach

• SerialParam for non-parallel evaluation

Examples

## -----------------------------------------------------------------------
## Job configuration:
## -----------------------------------------------------------------------

## SnowParam supports distributed memory computing. The object fields
## control the division of tasks, error handling, logging and result
## format.
bpparam <- SnowParam()
bpparam

## Fields are modified with accessors of the same name:
bplog(bpparam) <- TRUE
bpresultdir(bpparam) <- "/myResults/"
bpparam

## -----------------------------------------------------------------------
## Logging:
## -----------------------------------------------------------------------

## When 'log == TRUE' the workers use a custom script (in BiocParallel)
## that enables logging and access to other job statistics. Log messages
## are returned as each job completes rather than waiting for all to
## finish.

## In 'fun', a value of 'x = 1' will throw a warning, 'x = 2' is ok
## and 'x = 3' throws an error. Because 'x = 1' sleeps, the warning
## should return after the error.

X <- 1:3 
fun <- function(x) {
    if (x == 1) {
        Sys.sleep(2)
        if (TRUE & c(TRUE, TRUE))  ## warning
            x 
    } else if (x == 2) { 
        x                          ## ok
    } else if (x == 3) { 
        sqrt("FOO")                ## error
    }
}

## By default logging is off. Turn it on with the bplog()<- setter
## or by specifying 'log = TRUE' in the constructor.
bpparam <- SnowParam(3, log = TRUE, stop.on.error = FALSE)
tryCatch({
    bplapply(X, fun, BPPARAM = bpparam)
}, error=identity)

## When a 'logdir' location is given the messages are redirected to a
## file:
## Not run: 
bplogdir(bpparam) <- tempdir()
bplapply(X, fun, BPPARAM = bpparam)
list.files(bplogdir(bpparam))

## End(Not run)

## -----------------------------------------------------------------------
## Managing results:
## -----------------------------------------------------------------------

## By default results are returned as a list. When 'resultdir' is given
## files are saved in the directory specified by job, e.g., 'TASK1.Rda', 
## 'TASK2.Rda', etc.
## Not run: 
bpparam <- SnowParam(2, resultdir = tempdir())
bplapply(X, fun, BPPARAM = bpparam)
list.files(bpresultdir(bpparam))

## End(Not run)

## -----------------------------------------------------------------------
## Error handling:
## -----------------------------------------------------------------------

## When 'stop.on.error' is TRUE the process returns as soon as an error 
## is thrown. 

## When 'stop.on.error' is FALSE all computations are attempted. Partial
## results are returned along with errors. Use bptry() to see the
## partial results
bpparam <- SnowParam(2, stop.on.error = FALSE)
res <- bptry(bplapply(list(1, "two", 3, 4), sqrt, BPPARAM = bpparam))
res

## Calling bpok() on the result list returns TRUE for elements with no
## error.
bpok(res)

## -----------------------------------------------------------------------
## Random number generation:
## -----------------------------------------------------------------------

## Random number generation is controlled with the 'RNGseed' field. 
## This seed is passed to parallel::clusterSetRNGStream
## which uses the L'Ecuyer-CMRG random number generator and distributes
## streams to members of the cluster.

bpparam <- SnowParam(3, RNGseed = 7739465)
bplapply(seq_len(bpnworkers(bpparam)), function(i) rnorm(1),
         BPPARAM = bpparam)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(BiocParallel)
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/BiocParallel/SnowParam-class.Rd_%03d_medium.png", width=480, height=480)
> ### Name: SnowParam-class
> ### Title: Enable simple network of workstations (SNOW)-style parallel
> ###   evaluation
> ### Aliases: SnowParam SnowParam-class snowWorkers
> ###   bpbackend,SnowParam-method bpbackend<-,SnowParam,cluster-method
> ###   bpisup,SnowParam-method bpstart,SnowParam-method
> ###   bpstop,SnowParam-method bpworkers,SnowParam-method
> ###   bpworkers<-,SnowParam,numeric-method
> ###   bpworkers<-,SnowParam,character-method bplog,SnowParam-method
> ###   bplog<-,SnowParam,logical-method bpthreshold,SnowParam-method
> ###   bpthreshold<-,SnowParam,character-method bpRNGseed bpRNGseed<-
> ###   bpRNGseed,SnowParam-method bpRNGseed<-,SnowParam,numeric-method
> ###   bplogdir bplogdir<- bplogdir,SnowParam-method
> ###   bplogdir<-,SnowParam,character-method bpresultdir bpresultdir<-
> ###   bpresultdir,SnowParam-method bpresultdir<-,SnowParam,character-method
> ###   coerce,SOCKcluster,SnowParam-method
> ###   coerce,spawnedMPIcluster,SnowParam-method show,SnowParam-method
> ### Keywords: classes methods
> 
> ### ** Examples
> 
> 
> ## -----------------------------------------------------------------------
> ## Job configuration:
> ## -----------------------------------------------------------------------
> 
> ## SnowParam supports distributed memory computing. The object fields
> ## control the division of tasks, error handling, logging and result
> ## format.
> bpparam <- SnowParam()
> bpparam
class: SnowParam
  bpisup: FALSE; bpworkers: 2; bptasks: 0; bpjobname: BPJOB
  bplog: FALSE; bpthreshold: INFO; bpstopOnError: TRUE
  bptimeout: 2592000; bpprogressbar: FALSE
  bpRNGseed: 
  bplogdir: NA
  bpresultdir: NA
  cluster type: SOCK
> 
> ## Fields are modified with accessors of the same name:
> bplog(bpparam) <- TRUE
> bpresultdir(bpparam) <- "/myResults/"
> bpparam
class: SnowParam
  bpisup: FALSE; bpworkers: 2; bptasks: 0; bpjobname: BPJOB
  bplog: TRUE; bpthreshold: INFO; bpstopOnError: TRUE
  bptimeout: 2592000; bpprogressbar: FALSE
  bpRNGseed: 
  bplogdir: NA
  bpresultdir: /myResults/
  cluster type: SOCK
> 
> ## -----------------------------------------------------------------------
> ## Logging:
> ## -----------------------------------------------------------------------
> 
> ## When 'log == TRUE' the workers use a custom script (in BiocParallel)
> ## that enables logging and access to other job statistics. Log messages
> ## are returned as each job completes rather than waiting for all to
> ## finish.
> 
> ## In 'fun', a value of 'x = 1' will throw a warning, 'x = 2' is ok
> ## and 'x = 3' throws an error. Because 'x = 1' sleeps, the warning
> ## should return after the error.
> 
> X <- 1:3 
> fun <- function(x) {
+     if (x == 1) {
+         Sys.sleep(2)
+         if (TRUE & c(TRUE, TRUE))  ## warning
+             x 
+     } else if (x == 2) { 
+         x                          ## ok
+     } else if (x == 3) { 
+         sqrt("FOO")                ## error
+     }
+ }
> 
> ## By default logging is off. Turn it on with the bplog()<- setter
> ## or by specifying 'log = TRUE' in the constructor.
> bpparam <- SnowParam(3, log = TRUE, stop.on.error = FALSE)
> tryCatch({
+     bplapply(X, fun, BPPARAM = bpparam)
+ }, error=identity)
starting worker localhost:11149
starting worker localhost:11149
starting worker localhost:11149
############### LOG OUTPUT ###############
Task: 2
Node: 2
Timestamp: 2016-07-05 17:51:08
Success: TRUE
Task duration:
   user  system elapsed 
      0       0       0 
Memory used:
         used (Mb) gc trigger (Mb) max used (Mb)
Ncells 304009 16.3     592000 31.7   378451 20.3
Vcells 412615  3.2    1023718  7.9   786432  6.0
Log messages:

stderr and stdout:
character(0)
############### LOG OUTPUT ###############
Task: 3
Node: 3
Timestamp: 2016-07-05 17:51:08
Success: FALSE
Task duration:
   user  system elapsed 
  0.008   0.000   0.014 
Memory used:
         used (Mb) gc trigger (Mb) max used (Mb)
Ncells 304032 16.3     592000 31.7   378451 20.3
Vcells 413509  3.2    1023718  7.9   786432  6.0
Log messages:
ERROR [2016-07-05 17:51:08] non-numeric argument to mathematical function

stderr and stdout:
character(0)
############### LOG OUTPUT ###############
Task: 1
Node: 1
Timestamp: 2016-07-05 17:51:10
Success: TRUE
Task duration:
   user  system elapsed 
  0.000   0.000   2.004 
Memory used:
         used (Mb) gc trigger (Mb) max used (Mb)
Ncells 304034 16.3     592000 31.7   378451 20.3
Vcells 413511  3.2    1023718  7.9   786432  6.0
Log messages:
WARN [2016-07-05 17:51:10] the condition has length > 1 and only the first element will be used

stderr and stdout:
character(0)
Warning message:
In if (TRUE & c(TRUE, TRUE)) x :
  the condition has length > 1 and only the first element will be used
<bplist_error: BiocParallel errors
  element index: 3
  first error: non-numeric argument to mathematical function>
results and errors available as 'attr(x, "result")'
> 
> ## When a 'logdir' location is given the messages are redirected to a
> ## file:
> ## Not run: 
> ##D bplogdir(bpparam) <- tempdir()
> ##D bplapply(X, fun, BPPARAM = bpparam)
> ##D list.files(bplogdir(bpparam))
> ## End(Not run)
> 
> ## -----------------------------------------------------------------------
> ## Managing results:
> ## -----------------------------------------------------------------------
> 
> ## By default results are returned as a list. When 'resultdir' is given
> ## files are saved in the directory specified by job, e.g., 'TASK1.Rda', 
> ## 'TASK2.Rda', etc.
> ## Not run: 
> ##D bpparam <- SnowParam(2, resultdir = tempdir())
> ##D bplapply(X, fun, BPPARAM = bpparam)
> ##D list.files(bpresultdir(bpparam))
> ## End(Not run)
> 
> ## -----------------------------------------------------------------------
> ## Error handling:
> ## -----------------------------------------------------------------------
> 
> ## When 'stop.on.error' is TRUE the process returns as soon as an error 
> ## is thrown. 
> 
> ## When 'stop.on.error' is FALSE all computations are attempted. Partial
> ## results are returned along with errors. Use bptry() to see the
> ## partial results
> bpparam <- SnowParam(2, stop.on.error = FALSE)
> res <- bptry(bplapply(list(1, "two", 3, 4), sqrt, BPPARAM = bpparam))
starting worker localhost:11149
starting worker localhost:11149
> res
[[1]]
[1] 1

[[2]]
<remote_error in FUN(...): non-numeric argument to mathematical function>
traceback() available as 'attr(x, "traceback")'

[[3]]
[1] 1.732051

[[4]]
[1] 2

> 
> ## Calling bpok() on the result list returns TRUE for elements with no
> ## error.
> bpok(res)
[1]  TRUE FALSE  TRUE  TRUE
> 
> ## -----------------------------------------------------------------------
> ## Random number generation:
> ## -----------------------------------------------------------------------
> 
> ## Random number generation is controlled with the 'RNGseed' field. 
> ## This seed is passed to parallel::clusterSetRNGStream
> ## which uses the L'Ecuyer-CMRG random number generator and distributes
> ## streams to members of the cluster.
> 
> bpparam <- SnowParam(3, RNGseed = 7739465)
> bplapply(seq_len(bpnworkers(bpparam)), function(i) rnorm(1),
+          BPPARAM = bpparam)
starting worker localhost:11149
starting worker localhost:11149
starting worker localhost:11149
[[1]]
[1] 0.8552377

[[2]]
[1] -0.2198241

[[3]]
[1] -0.5324814

> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>