In richfitz/rrq: Simple Redis Queue
In addition to passing tasks (and results) between a controller and
workers, the controller can also send "messages" to workers. This
vignette shows what the possible messages do.
In order to do this, we're going to need a queue and a worker:
library(rrq)
id <- paste0("rrq:", ids::random_id(bytes = 4))
obj <- rrq_controller(id)
rrq_default_controller_set(obj)
logdir <- tempfile()
w <- rrq_worker_spawn(logdir = logdir)
#> ℹ Spawning 1 worker with prefix 'boiling_cockatoo'
worker_id <- w$id
On startup the worker log contains:
[2024-04-23 09:15:49.424189] ALIVE
[2024-04-23 09:15:49.425172] ENVIR new
[2024-04-23 09:15:49.425903] QUEUE default
__
______________ _/ /
______ / ___/ ___/ __ `/ /_____
/_____/ / / / / / /_/ /_/_____/
______ /_/ /_/ \__, (_) ______
/_____/ /_/ /_____/
worker: boiling_cockatoo_1
config: localhost
rrq_version: 0.7.15
platform: x86_64-pc-linux-gnu (64-bit)
running: Ubuntu 20.04.6 LTS
hostname: wpia-dide300
username: rfitzjoh
queue: rrq:7c911007:queue:default
wd: /home/rfitzjoh/Documents/src/rrq/vignettes_src
pid: 597597
redis_host: 127.0.0.1
redis_port: 6379
heartbeat_key: <not set>
Because one of the main effects of messages is to print to the
worker logfile, we'll print this fairly often.
Messages and responses
-
The queue sends a message for one or more workers to process.
The message has an identifier that is derived from the current
time. Messages are written to a first-in-first-out queue, per
worker, and are processed independently by workers who do not
look to see if other workers have messages or are processing
them.
-
As soon as a worker has finished processing any current job it
will process the message (it must wait to finish a current job
but will not start any further jobs).
-
Once the message has been processed (see below) a response will
be written to a response list with the same identifier as the
message.
Some messages interact with the worker timeout:
PING, ECHO, EVAL, INFO PAUSE, RESUME and REFRESH will reset the timer, as if a task had been runTIMEOUT_SET explicitly interacts with the timerTIMEOUT_GET does not reset the timer, reporting the remaining timeSTOP causes the worker to exit, so has no interaction with the timer
PING
The PING message simply asks the worker to return PONG. It's
useful for diagnosing communication issues because it does so
little
message_id <- rrq_message_send("PING")
The message id is going to be useful for getting responses:
message_id
#> [1] "1713860149.627246"
(this is derived from the current time, according to Redis which is
the central reference point of time for the whole system).
[2024-04-23 09:15:49.627994] MESSAGE PING
PONG
[2024-04-23 09:15:49.628864] RESPONSE PING
The logfile prints:
- the request for the
PING (MESSAGE PING)
- the value
PONG to the R message stream
- logging a response (
RESPONSE PONG), which means that something is written to the response stream.
We can access the same bits of information in the worker log:
rrq_worker_log_tail(n = Inf)
#> worker_id child time command message
#> 1 boiling_cockatoo_1 NA 1713860149 ALIVE
#> 2 boiling_cockatoo_1 NA 1713860149 ENVIR new
#> 3 boiling_cockatoo_1 NA 1713860149 QUEUE default
#> 4 boiling_cockatoo_1 NA 1713860150 MESSAGE PING
#> 5 boiling_cockatoo_1 NA 1713860150 RESPONSE PING
This includes the ALIVE message as the worker comes up.
Inspecting the logs is fine for interactive use, but it's going to
be more useful often to poll for a response.
We already know that our worker has a response, but we can ask anyway:
rrq_message_has_response(message_id)
#> boiling_cockatoo_1
#> TRUE
Or inversely we can as what messages a given worker has responses for:
rrq_message_response_ids(worker_id)
#> [1] "1713860149.627246"
To fetch the responses from all workers it was sent to (always
returning a named list):
rrq_message_get_response(message_id)
#> $boiling_cockatoo_1
#> [1] "PONG"
or to fetch the response from a given worker:
rrq_message_get_response(message_id, worker_id)
#> $boiling_cockatoo_1
#> [1] "PONG"
The response can be deleted by passing delete = TRUE to this method:
rrq_message_get_response(message_id, worker_id, delete = TRUE)
#> $boiling_cockatoo_1
#> [1] "PONG"
after which recalling the message will throw an error:
rrq_message_get_response(message_id, worker_id)
#> Error in `rrq_message_get_response()`:
#> ! Response missing for worker: 'boiling_cockatoo_1'
There is also a timeout argument that lets you wait until a response is
ready (as in rrq_task_wait()).
rrq_task_create_expr(Sys.sleep(2))
#> [1] "1a878e7cac11aa4e7fa234286676954c"
message_id <- rrq_message_send("PING")
rrq_message_get_response(
message_id, worker_id, delete = TRUE, timeout = 10)
#> $boiling_cockatoo_1
#> [1] "PONG"
Looking at the log will show what went on here:
rrq_worker_log_tail(n = 4)
#> worker_id child time command
#> 1 boiling_cockatoo_1 NA 1713860150 TASK_START
#> 2 boiling_cockatoo_1 NA 1713860152 TASK_COMPLETE
#> 3 boiling_cockatoo_1 NA 1713860152 MESSAGE
#> 4 boiling_cockatoo_1 NA 1713860152 RESPONSE
#> message
#> 1 1a878e7cac11aa4e7fa234286676954c
#> 2 1a878e7cac11aa4e7fa234286676954c
#> 3 PING
#> 4 PING
- A task is received
- 2s later the task is completed
- Then the message is received
- Then, basically instantaneously, the message is responded to
However, because the message is only processed after the task is
completed, the response takes a while to come back. Equivalently,
from the worker log:
[2024-04-23 09:15:49.751482] TASK_START 1a878e7cac11aa4e7fa234286676954c
[2024-04-23 09:15:51.754822] TASK_COMPLETE 1a878e7cac11aa4e7fa234286676954c
[2024-04-23 09:15:51.755615] MESSAGE PING
PONG
[2024-04-23 09:15:51.756114] RESPONSE PING
ECHO
This is basically like PING and not very interesting; it prints
an arbitrary string to the log. It always returns "OK" as a
response.
message_id <- rrq_message_send("ECHO", "hello world!")
rrq_message_get_response(message_id, worker_id, timeout = 10)
#> $boiling_cockatoo_1
#> [1] "OK"
[2024-04-23 09:15:52.269914] MESSAGE ECHO
hello world!
[2024-04-23 09:15:52.27044] RESPONSE ECHO
INFO
The INFO command refreshes and returns the worker information.
We already have a copy of the worker info; it was created when the
worker started up:
rrq_worker_info()[[worker_id]]
#> <rrq_worker_info>
#> worker: boiling_cockatoo_1
#> config: localhost
#> rrq_version: 0.7.15
#> platform: x86_64-pc-linux-gnu (64-bit)
#> running: Ubuntu 20.04.6 LTS
#> hostname: wpia-dide300
#> username: rfitzjoh
#> queue: rrq:7c911007:queue:default
#> wd: /home/rfitzjoh/Documents/src/rrq/vignettes_src
#> pid: 597597
#> redis_host: 127.0.0.1
#> redis_port: 6379
We can force the worker to refresh:
message_id <- rrq_message_send("INFO")
Here's the new worker information, complete with an updated envir
field:
rrq_message_get_response(message_id, worker_id, timeout = 10)
#> $boiling_cockatoo_1
#> $boiling_cockatoo_1$worker
#> [1] "boiling_cockatoo_1"
#>
#> $boiling_cockatoo_1$config
#> [1] "localhost"
#>
#> $boiling_cockatoo_1$rrq_version
#> [1] "0.7.15"
#>
#> $boiling_cockatoo_1$platform
#> [1] "x86_64-pc-linux-gnu (64-bit)"
#>
#> $boiling_cockatoo_1$running
#> [1] "Ubuntu 20.04.6 LTS"
#>
#> $boiling_cockatoo_1$hostname
#> [1] "wpia-dide300"
#>
#> $boiling_cockatoo_1$username
#> [1] "rfitzjoh"
#>
#> $boiling_cockatoo_1$queue
#> [1] "rrq:7c911007:queue:default"
#>
#> $boiling_cockatoo_1$wd
#> [1] "/home/rfitzjoh/Documents/src/rrq/vignettes_src"
#>
#> $boiling_cockatoo_1$pid
#> [1] 597597
#>
#> $boiling_cockatoo_1$redis_host
#> [1] "127.0.0.1"
#>
#> $boiling_cockatoo_1$redis_port
#> [1] 6379
EVAL
Evaluate an arbitrary R expression, passed as a string (not as
any sort of unevaluated or quoted expression). This expression is
evaluated in the global environment, which is not the environment
in which queued code is evaluated in.
message_id <- rrq_message_send("EVAL", "1 + 1")
rrq_message_get_response(message_id, worker_id, timeout = 10)
#> $boiling_cockatoo_1
#> [1] 2
This could be used to evaluate code that has side effects, such as
installing packages. However, due to limitations with how R loads
packages the only way to update and reload a package is going to be
to restart the worker.
PAUSE / RESUME
The PAUSE / RESUME messages can be used to prevent workers from picking up new work (and then allowing them to start again).
rrq_worker_status()
#> boiling_cockatoo_1
#> "IDLE"
message_id <- rrq_message_send("PAUSE")
rrq_message_get_response(message_id, worker_id, timeout = 10)
#> $boiling_cockatoo_1
#> [1] "OK"
rrq_worker_status()
#> boiling_cockatoo_1
#> "PAUSED"
Once paused workers ignore tasks, which stay on the queue:
t <- rrq_task_create_expr(runif(5))
rrq_task_status(t)
#> [1] "PENDING"
Sending a RESUME message unpauses the worker:
message_id <- rrq_message_send("RESUME")
rrq_message_get_response(message_id, worker_id, timeout = 10)
#> $boiling_cockatoo_1
#> [1] "OK"
rrq_task_wait(t, 5)
#> [1] TRUE
SET_TIMEOUT / GET_TIMEOUT
Workers will quit after being left idle for more than a certain time; this is their timeout. Only processing tasks counts as work (not messages). You can query the timeout with GET_TIMEOUT and set it with SET_TIMEOUT. For our worker above the timeout is infinite; it will never quit:
rrq_message_send_and_wait("TIMEOUT_GET", worker_ids = worker_id)
#> $boiling_cockatoo_1
#> timeout_idle remaining
#> Inf Inf
We can set this to a finite value, in seconds:
rrq_message_send_and_wait("TIMEOUT_SET", 600, worker_ids = worker_id)
#> $boiling_cockatoo_1
#> [1] "OK"
Here the timeout is set to 10 minutes (600s).
Once set, the TIMEOUT_GET returns the length of time remaining before the worker exits
rrq_message_send_and_wait("TIMEOUT_GET", worker_ids = worker_id)
#> $boiling_cockatoo_1
#> timeout_idle remaining
#> 600.0000 599.9353
Sys.sleep(5)
rrq_message_send_and_wait("TIMEOUT_GET", worker_ids = worker_id)
#> $boiling_cockatoo_1
#> timeout_idle remaining
#> 600.000 594.872
One useful pattern is to send work to workers, then set the timeout to zero. This means that when work is complete they will exit (almost) immediately:
ids <- rrq_task_create_bulk_call(function(x) {
Sys.sleep(0.5)
runif(x)
}, 1:5)
rrq_message_send("TIMEOUT_SET", 0, worker_id)
rrq_task_wait(ids)
#> [1] TRUE
rrq_task_results(ids)
#> [[1]]
#> [1] 0.6824953
#>
#> [[2]]
#> [1] 0.3917506 0.7700726
#>
#> [[3]]
#> [1] 0.61080994 0.47160999 0.06371166
#>
#> [[4]]
#> [1] 0.2314934 0.4231295 0.7559091 0.4027418
#>
#> [[5]]
#> [1] 0.6109091 0.8732575 0.4324995 0.2940482 0.2035300
The worker will remain idle for 60s (by default) which is the length of time that one poll for work lasts, then it will exit.
rrq_worker_status(worker_id)
#> boiling_cockatoo_1
#> "IDLE"
rrq_message_send_and_wait("TIMEOUT_GET", worker_ids = worker_id)
#> $boiling_cockatoo_1
#> timeout_idle remaining
#> 0 0
Messages that are supported but use via wrappers:
There are other methods that are typically used via methods on the [rrq_controller] object.
REFRESH: requests that the worker refresh its evaluation environment. Typically used via rrq_worker_envir_set()STOP: sent with a informational message as an argument, requests that the worker stop. Typically used via rrq_worker_stop()
richfitz/rrq documentation built on July 15, 2024, 8:12 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
In addition to passing tasks (and results) between a controller and workers, the controller can also send "messages" to workers. This vignette shows what the possible messages do.
In order to do this, we're going to need a queue and a worker:
library(rrq) id <- paste0("rrq:", ids::random_id(bytes = 4)) obj <- rrq_controller(id) rrq_default_controller_set(obj) logdir <- tempfile() w <- rrq_worker_spawn(logdir = logdir) #> ℹ Spawning 1 worker with prefix 'boiling_cockatoo' worker_id <- w$id
On startup the worker log contains:
[2024-04-23 09:15:49.424189] ALIVE
[2024-04-23 09:15:49.425172] ENVIR new
[2024-04-23 09:15:49.425903] QUEUE default
__
______________ _/ /
______ / ___/ ___/ __ `/ /_____
/_____/ / / / / / /_/ /_/_____/
______ /_/ /_/ \__, (_) ______
/_____/ /_/ /_____/
worker: boiling_cockatoo_1
config: localhost
rrq_version: 0.7.15
platform: x86_64-pc-linux-gnu (64-bit)
running: Ubuntu 20.04.6 LTS
hostname: wpia-dide300
username: rfitzjoh
queue: rrq:7c911007:queue:default
wd: /home/rfitzjoh/Documents/src/rrq/vignettes_src
pid: 597597
redis_host: 127.0.0.1
redis_port: 6379
heartbeat_key: <not set>
Because one of the main effects of messages is to print to the worker logfile, we'll print this fairly often.
Messages and responses
-
The queue sends a message for one or more workers to process. The message has an identifier that is derived from the current time. Messages are written to a first-in-first-out queue, per worker, and are processed independently by workers who do not look to see if other workers have messages or are processing them.
-
As soon as a worker has finished processing any current job it will process the message (it must wait to finish a current job but will not start any further jobs).
-
Once the message has been processed (see below) a response will be written to a response list with the same identifier as the message.
Some messages interact with the worker timeout:
PING,ECHO,EVAL,INFOPAUSE,RESUMEandREFRESHwill reset the timer, as if a task had been runTIMEOUT_SETexplicitly interacts with the timerTIMEOUT_GETdoes not reset the timer, reporting the remaining timeSTOPcauses the worker to exit, so has no interaction with the timer
PING
The PING message simply asks the worker to return PONG. It's
useful for diagnosing communication issues because it does so
little
message_id <- rrq_message_send("PING")
The message id is going to be useful for getting responses:
message_id
#> [1] "1713860149.627246"
(this is derived from the current time, according to Redis which is the central reference point of time for the whole system).
[2024-04-23 09:15:49.627994] MESSAGE PING PONG [2024-04-23 09:15:49.628864] RESPONSE PING
The logfile prints:
- the request for the
PING(MESSAGE PING) - the value
PONGto the R message stream - logging a response (
RESPONSE PONG), which means that something is written to the response stream.
We can access the same bits of information in the worker log:
rrq_worker_log_tail(n = Inf) #> worker_id child time command message #> 1 boiling_cockatoo_1 NA 1713860149 ALIVE #> 2 boiling_cockatoo_1 NA 1713860149 ENVIR new #> 3 boiling_cockatoo_1 NA 1713860149 QUEUE default #> 4 boiling_cockatoo_1 NA 1713860150 MESSAGE PING #> 5 boiling_cockatoo_1 NA 1713860150 RESPONSE PING
This includes the ALIVE message as the worker comes up.
Inspecting the logs is fine for interactive use, but it's going to be more useful often to poll for a response.
We already know that our worker has a response, but we can ask anyway:
rrq_message_has_response(message_id) #> boiling_cockatoo_1 #> TRUE
Or inversely we can as what messages a given worker has responses for:
rrq_message_response_ids(worker_id) #> [1] "1713860149.627246"
To fetch the responses from all workers it was sent to (always returning a named list):
rrq_message_get_response(message_id) #> $boiling_cockatoo_1 #> [1] "PONG"
or to fetch the response from a given worker:
rrq_message_get_response(message_id, worker_id) #> $boiling_cockatoo_1 #> [1] "PONG"
The response can be deleted by passing delete = TRUE to this method:
rrq_message_get_response(message_id, worker_id, delete = TRUE) #> $boiling_cockatoo_1 #> [1] "PONG"
after which recalling the message will throw an error:
rrq_message_get_response(message_id, worker_id) #> Error in `rrq_message_get_response()`: #> ! Response missing for worker: 'boiling_cockatoo_1'
There is also a timeout argument that lets you wait until a response is
ready (as in rrq_task_wait()).
rrq_task_create_expr(Sys.sleep(2)) #> [1] "1a878e7cac11aa4e7fa234286676954c" message_id <- rrq_message_send("PING") rrq_message_get_response( message_id, worker_id, delete = TRUE, timeout = 10) #> $boiling_cockatoo_1 #> [1] "PONG"
Looking at the log will show what went on here:
rrq_worker_log_tail(n = 4) #> worker_id child time command #> 1 boiling_cockatoo_1 NA 1713860150 TASK_START #> 2 boiling_cockatoo_1 NA 1713860152 TASK_COMPLETE #> 3 boiling_cockatoo_1 NA 1713860152 MESSAGE #> 4 boiling_cockatoo_1 NA 1713860152 RESPONSE #> message #> 1 1a878e7cac11aa4e7fa234286676954c #> 2 1a878e7cac11aa4e7fa234286676954c #> 3 PING #> 4 PING
- A task is received
- 2s later the task is completed
- Then the message is received
- Then, basically instantaneously, the message is responded to
However, because the message is only processed after the task is completed, the response takes a while to come back. Equivalently, from the worker log:
[2024-04-23 09:15:49.751482] TASK_START 1a878e7cac11aa4e7fa234286676954c [2024-04-23 09:15:51.754822] TASK_COMPLETE 1a878e7cac11aa4e7fa234286676954c [2024-04-23 09:15:51.755615] MESSAGE PING PONG [2024-04-23 09:15:51.756114] RESPONSE PING
ECHO
This is basically like PING and not very interesting; it prints
an arbitrary string to the log. It always returns "OK" as a
response.
message_id <- rrq_message_send("ECHO", "hello world!") rrq_message_get_response(message_id, worker_id, timeout = 10) #> $boiling_cockatoo_1 #> [1] "OK"
[2024-04-23 09:15:52.269914] MESSAGE ECHO hello world! [2024-04-23 09:15:52.27044] RESPONSE ECHO
INFO
The INFO command refreshes and returns the worker information.
We already have a copy of the worker info; it was created when the worker started up:
rrq_worker_info()[[worker_id]] #> <rrq_worker_info> #> worker: boiling_cockatoo_1 #> config: localhost #> rrq_version: 0.7.15 #> platform: x86_64-pc-linux-gnu (64-bit) #> running: Ubuntu 20.04.6 LTS #> hostname: wpia-dide300 #> username: rfitzjoh #> queue: rrq:7c911007:queue:default #> wd: /home/rfitzjoh/Documents/src/rrq/vignettes_src #> pid: 597597 #> redis_host: 127.0.0.1 #> redis_port: 6379
We can force the worker to refresh:
message_id <- rrq_message_send("INFO")
Here's the new worker information, complete with an updated envir
field:
rrq_message_get_response(message_id, worker_id, timeout = 10) #> $boiling_cockatoo_1 #> $boiling_cockatoo_1$worker #> [1] "boiling_cockatoo_1" #> #> $boiling_cockatoo_1$config #> [1] "localhost" #> #> $boiling_cockatoo_1$rrq_version #> [1] "0.7.15" #> #> $boiling_cockatoo_1$platform #> [1] "x86_64-pc-linux-gnu (64-bit)" #> #> $boiling_cockatoo_1$running #> [1] "Ubuntu 20.04.6 LTS" #> #> $boiling_cockatoo_1$hostname #> [1] "wpia-dide300" #> #> $boiling_cockatoo_1$username #> [1] "rfitzjoh" #> #> $boiling_cockatoo_1$queue #> [1] "rrq:7c911007:queue:default" #> #> $boiling_cockatoo_1$wd #> [1] "/home/rfitzjoh/Documents/src/rrq/vignettes_src" #> #> $boiling_cockatoo_1$pid #> [1] 597597 #> #> $boiling_cockatoo_1$redis_host #> [1] "127.0.0.1" #> #> $boiling_cockatoo_1$redis_port #> [1] 6379
EVAL
Evaluate an arbitrary R expression, passed as a string (not as any sort of unevaluated or quoted expression). This expression is evaluated in the global environment, which is not the environment in which queued code is evaluated in.
message_id <- rrq_message_send("EVAL", "1 + 1") rrq_message_get_response(message_id, worker_id, timeout = 10) #> $boiling_cockatoo_1 #> [1] 2
This could be used to evaluate code that has side effects, such as installing packages. However, due to limitations with how R loads packages the only way to update and reload a package is going to be to restart the worker.
PAUSE / RESUME
The PAUSE / RESUME messages can be used to prevent workers from picking up new work (and then allowing them to start again).
rrq_worker_status() #> boiling_cockatoo_1 #> "IDLE" message_id <- rrq_message_send("PAUSE") rrq_message_get_response(message_id, worker_id, timeout = 10) #> $boiling_cockatoo_1 #> [1] "OK" rrq_worker_status() #> boiling_cockatoo_1 #> "PAUSED"
Once paused workers ignore tasks, which stay on the queue:
t <- rrq_task_create_expr(runif(5)) rrq_task_status(t) #> [1] "PENDING"
Sending a RESUME message unpauses the worker:
message_id <- rrq_message_send("RESUME") rrq_message_get_response(message_id, worker_id, timeout = 10) #> $boiling_cockatoo_1 #> [1] "OK" rrq_task_wait(t, 5) #> [1] TRUE
SET_TIMEOUT / GET_TIMEOUT
Workers will quit after being left idle for more than a certain time; this is their timeout. Only processing tasks counts as work (not messages). You can query the timeout with GET_TIMEOUT and set it with SET_TIMEOUT. For our worker above the timeout is infinite; it will never quit:
rrq_message_send_and_wait("TIMEOUT_GET", worker_ids = worker_id) #> $boiling_cockatoo_1 #> timeout_idle remaining #> Inf Inf
We can set this to a finite value, in seconds:
rrq_message_send_and_wait("TIMEOUT_SET", 600, worker_ids = worker_id) #> $boiling_cockatoo_1 #> [1] "OK"
Here the timeout is set to 10 minutes (600s).
Once set, the TIMEOUT_GET returns the length of time remaining before the worker exits
rrq_message_send_and_wait("TIMEOUT_GET", worker_ids = worker_id) #> $boiling_cockatoo_1 #> timeout_idle remaining #> 600.0000 599.9353 Sys.sleep(5) rrq_message_send_and_wait("TIMEOUT_GET", worker_ids = worker_id) #> $boiling_cockatoo_1 #> timeout_idle remaining #> 600.000 594.872
One useful pattern is to send work to workers, then set the timeout to zero. This means that when work is complete they will exit (almost) immediately:
ids <- rrq_task_create_bulk_call(function(x) { Sys.sleep(0.5) runif(x) }, 1:5) rrq_message_send("TIMEOUT_SET", 0, worker_id) rrq_task_wait(ids) #> [1] TRUE rrq_task_results(ids) #> [[1]] #> [1] 0.6824953 #> #> [[2]] #> [1] 0.3917506 0.7700726 #> #> [[3]] #> [1] 0.61080994 0.47160999 0.06371166 #> #> [[4]] #> [1] 0.2314934 0.4231295 0.7559091 0.4027418 #> #> [[5]] #> [1] 0.6109091 0.8732575 0.4324995 0.2940482 0.2035300
The worker will remain idle for 60s (by default) which is the length of time that one poll for work lasts, then it will exit.
rrq_worker_status(worker_id) #> boiling_cockatoo_1 #> "IDLE" rrq_message_send_and_wait("TIMEOUT_GET", worker_ids = worker_id) #> $boiling_cockatoo_1 #> timeout_idle remaining #> 0 0
Messages that are supported but use via wrappers:
There are other methods that are typically used via methods on the [rrq_controller] object.
REFRESH: requests that the worker refresh its evaluation environment. Typically used viarrq_worker_envir_set()STOP: sent with a informational message as an argument, requests that the worker stop. Typically used viarrq_worker_stop()
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.