messages

Messages and responses

1. 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.

2. 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).

3. 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 run
• TIMEOUT_SET explicitly interacts with the timer
• TIMEOUT_GET does not reset the timer, reporting the remaining time
• STOP 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:

1. the request for the PING (MESSAGE PING)
2. the value PONG to the R message stream
3. 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

1. A task is received
2. 2s later the task is completed
3. Then the message is received
4. 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()