registerDoRedis: Register the Redis back end for foreach.

In doRedis: 'Foreach' Parallel Adapter Using the 'Redis' Database

Register the Redis back end for foreach.

Description

The doRedis package imlpements a simple but flexible parallel back end for foreach that uses Redis for inter-process communication. The work queue name specifies the base name of a small set of Redis keys that the coordinator and worker processes use to exchange data.

Usage

registerDoRedis(
  queue,
  host = "localhost",
  port = 6379,
  password,
  ftinterval = 30,
  chunkSize = 1,
  progress = FALSE,
  ...
)

Arguments

queue	A work queue name
host	The Redis server host name or IP address
port	The Redis server port number
password	An optional Redis database password
ftinterval	Default fault tolerance interval in seconds
chunkSize	Default iteration granularity, see setChunkSize
progress	(logical) Show progress bar for computations?
...	Optional arguments passed to redisConnect

Details

Back-end worker R processes advertise their availablility for work with the redisWorker function.

The doRedis parallel back end tolerates faults among the worker processes and automatically resubmits failed tasks. It is also portable and supports heterogeneous sets of workers, even across operative systems. The back end supports dynamic pools of worker processes. New workers may be added to work queues at any time and can be used by running foreach computations.

Value

NULL is invisibly returned; this function is called for side effect of registering a foreach backend.

Note

All doRedis functions require access to a Redis database server (not included with this package).

Worker processes default to same random number generator as the coordinator process by default with seeds set per iteration rather than per worker to yield reproducible output independent of the number of worker processes. The L'Ecuyer-CMRG RNG available from the parallel package is recommended when high-quality distributed pseudorandom numbers are needed. See package vignette for more details and additional options.

Avoid using fork-based parallel functions within doRedis expressions. Use of mclapply and similar functions in the body of a doRedis foreach loop can result in worker faults.

See Also

foreach, doRedis-package, setChunkSize, removeQueue

Examples

# Only run if a Redis server is running
if (redux::redis_available()) {
## The example assumes that a Redis server is running on the local host
## and standard port.

# 1. Start a single local R worker process
startLocalWorkers(n=1, queue="jobs", linger=1)

# 2. Run a simple sampling approximation of pi:
registerDoRedis("jobs")
pie = foreach(j=1:10, .combine=sum, .multicombine=TRUE) %dopar%
        4 * sum((runif(1000000) ^ 2 + runif(1000000) ^ 2) < 1) / 10000000
removeQueue("jobs")
print(pie)

# Note that removing the work queue automatically terminates worker processes.
}

doRedis documentation built on May 2, 2023, 5:10 p.m.