The Rush manager is responsible for starting, observing, and stopping workers within a rush network.
It is initialized using the rsh() function, which requires a network ID and a config argument.
The config argument is a configuration used to connect to the Redis database via the redux package.
Value
Object of class R6::R6Class and Rush.
Tasks
Tasks are the unit in which workers exchange information.
The main components of a task are the key, computational state, input (xs), and output (ys).
The key is a unique identifier for the task in the Redis database.
The four possible computational states are "running", "finished", "failed", and "queued".
The input xs and output ys are lists that can contain arbitrary data.
Methods to create a task:
$push_running_tasks(xss): Create running tasks$push_finished_tasks(xss, yss): Create finished tasks.$push_failed_tasks(xss, conditions): Create failed tasks.$push_tasks(xss): Create queued tasks.
These methods return the key of the created tasks.
The methods work on multiple tasks at once, so xss and yss are lists of inputs and outputs.
Methods to change the state of an existing task:
$finish_tasks(keys, yss): Save the output of tasks and mark them as finished.$fail_tasks(keys, conditions): Mark tasks as failed and optionally save the condition objects.$pop_task(): Pop a task from the queue and mark it as running.
The following methods are used to fetch tasks:
$fetch_tasks(): Fetch all tasks.$fetch_finished_tasks(): Fetch finished tasks.$fetch_failed_tasks(): Fetch failed tasks.$fetch_tasks_with_state(): Fetch tasks with different states at once.$fetch_new_tasks(): Fetch new tasks and optionally block until new tasks are available.
The methods return a data.table() with the tasks.
Tasks have the following fields:
xs: The input of the task.ys: The output of the task.xs_extra: Metadata created when creating the task.ys_extra: Metadata created when finishing the task.condition: Condition object when the task failed.worker_id: The id of the worker that created the task.
Workers
Workers are spawned with the $start_workers() method on mirai daemons.
Use mirai::daemons() to start daemons.
Workers can be started on the
or HPC cluster using the mirai package.
Alternatively, workers can be started locally with the $start_local_workers() method via the processx package.
Or a help script can be generated with the $worker_script() method that can be run anywhere.
The only requirement is that the worker can connect to the Redis database.
Worker Loop
The worker loop is the main function that is run on the workers.
It is defined by the user and is passed to the $start_workers() method.
Debugging
The mirai::mirai objects started with $start_workers() are stored in $processes_mirai.
Standard output and error of the workers ca be written to log files with the message_log and output_log arguments of $start_workers().
Public fields
processes_processx(processx::process)
List of processes started with$start_local_workers().processes_mirai(mirai::mirai)
List of mirai processes started with$start_remote_workers().
Active bindings
network_id(
character(1))
Identifier of the rush network.config(redux::redis_config)
Redis configuration options.connector(redux::redis_api)
Returns a connection to Redis.n_workers(
integer(1))
Number of workers.n_running_workers(
integer(1))
Number of running workers.n_terminated_workers(
integer(1))
Number of terminated workers.worker_ids(
character())
Ids of workers.running_worker_ids(
character())
Ids of running workers.terminated_worker_ids(
character())
Ids of terminated workers.tasks(
character())
Keys of all tasks.queued_tasks(
character())
Keys of queued tasks.running_tasks(
character())
Keys of running tasks.finished_tasks(
character())
Keys of finished tasks.failed_tasks(
character())
Keys of failed tasks.n_queued_tasks(
integer(1))
Number of queued tasks.n_running_tasks(
integer(1))
Number of running tasks.n_finished_tasks(
integer(1))
Number of finished tasks.n_failed_tasks(
integer(1))
Number of failed tasks.n_tasks(
integer(1))
Number of all tasks.worker_info(
data.table::data.table())
Contains information about the workers.
Methods
Method new()
Creates a new instance of this R6 class.
Usage
Rush$new(network_id = NULL, config = NULL)Arguments
network_id(
character(1))
Identifier of the rush network. Manager and workers must have the same id. Keys in Redis are prefixed with the instance id.config(redux::redis_config)
Redis configuration options. IfNULL, configuration set byrush_plan()is used. Ifrush_plan()has not been called, theREDIS_URLenvironment variable is parsed. IfREDIS_URLis not set, a default configuration is used. See redux::redis_config for details.
Method reconnect()
Reconnect to Redis. The connection breaks when the Rush object is saved to disk. Call this method to reconnect after loading the object.
Method start_workers()
Start workers to run the worker loop in mirai::daemons().
Initializes a RushWorker in each process and starts the worker loop.
Usage
Rush$start_workers(
worker_loop,
...,
n_workers = NULL,
packages = NULL,
lgr_thresholds = NULL,
lgr_buffer_size = NULL,
message_log = NULL,
output_log = NULL
)Arguments
worker_loop(
function)
Loop run on the workers....(
any)
Arguments passed toworker_loop.n_workers(
integer(1))
Number of workers to be started.packages(
character())
Packages to be loaded by the workers.lgr_thresholds(named
character()| namednumeric())
Logger threshold on the workers e.g.c("mlr3/rush" = "debug").lgr_buffer_size(
integer(1))
By default (lgr_buffer_size = 0), the log messages are directly saved in the Redis data store. Iflgr_buffer_size > 0, the log messages are buffered and saved in the Redis data store when the buffer is full. This improves the performance of the logging.message_log(
character(1))
Path to the message log files e.g./tmp/message_logs/The message log files are namedmessage_<worker_id>.log. IfNULL, no messages, warnings or errors are stored.output_log(
character(1))
Path to the output log files e.g./tmp/output_logs/The output log files are namedoutput_<worker_id>.log. IfNULL, no output is stored.
Method start_local_workers()
Start workers locally with processx.
Initializes a RushWorker in each process and starts the worker loop.
Use $wait_for_workers() to wait until the workers are registered in the network.
Usage
Rush$start_local_workers(
worker_loop,
...,
n_workers = NULL,
packages = NULL,
lgr_thresholds = NULL,
lgr_buffer_size = NULL,
supervise = TRUE,
message_log = NULL,
output_log = NULL
)Arguments
worker_loop(
function)
Loop run on the workers....(
any)
Arguments passed toworker_loop.n_workers(
integer(1))
Number of workers to be started.packages(
character())
Packages to be loaded by the workers.lgr_thresholds(named
character()| namednumeric())
Logger threshold on the workers e.g.c("mlr3/rush" = "debug").lgr_buffer_size(
integer(1))
By default (lgr_buffer_size = 0), the log messages are directly saved in the Redis data store. Iflgr_buffer_size > 0, the log messages are buffered and saved in the Redis data store when the buffer is full. This improves the performance of the logging.supervise(
logical(1))
Whether to kill the workers when the main R process is shut down.message_log(
character(1))
Path to the message log files e.g./tmp/message_logs/The message log files are namedmessage_<worker_id>.log. IfNULL, no messages, warnings or errors are stored.output_log(
character(1))
Path to the output log files e.g./tmp/output_logs/The output log files are namedoutput_<worker_id>.log. IfNULL, no output is stored.
Method start_remote_workers()
Start workers to run the worker loop in mirai::daemons().
Initializes a RushWorker in each process and starts the worker loop.
Usage
Rush$start_remote_workers(
worker_loop,
...,
n_workers = NULL,
packages = NULL,
lgr_thresholds = NULL,
lgr_buffer_size = NULL,
message_log = NULL,
output_log = NULL
)Arguments
worker_loop(
function)
Loop run on the workers....(
any)
Arguments passed toworker_loop.n_workers(
integer(1))
Number of workers to be started.packages(
character())
Packages to be loaded by the workers.lgr_thresholds(named
character()| namednumeric())
Logger threshold on the workers e.g.c("mlr3/rush" = "debug").lgr_buffer_size(
integer(1))
By default (lgr_buffer_size = 0), the log messages are directly saved in the Redis data store. Iflgr_buffer_size > 0, the log messages are buffered and saved in the Redis data store when the buffer is full. This improves the performance of the logging.message_log(
character(1))
Path to the message log files e.g./tmp/message_logs/The message log files are namedmessage_<worker_id>.log. IfNULL, no messages, warnings or errors are stored.output_log(
character(1))
Path to the output log files e.g./tmp/output_logs/The output log files are namedoutput_<worker_id>.log. IfNULL, no output is stored.
Method worker_script()
Generate a script to start workers.
Run this script n times to start n workers.
Usage
Rush$worker_script(
worker_loop,
...,
packages = NULL,
lgr_thresholds = NULL,
lgr_buffer_size = NULL,
heartbeat_period = NULL,
heartbeat_expire = NULL,
message_log = NULL,
output_log = NULL
)Arguments
worker_loop(
function)
Loop run on the workers....(
any)
Arguments passed toworker_loop.packages(
character())
Packages to be loaded by the workers.lgr_thresholds(named
character()| namednumeric())
Logger threshold on the workers e.g.c("mlr3/rush" = "debug").lgr_buffer_size(
integer(1))
By default (lgr_buffer_size = 0), the log messages are directly saved in the Redis data store. Iflgr_buffer_size > 0, the log messages are buffered and saved in the Redis data store when the buffer is full. This improves the performance of the logging.heartbeat_period(
integer(1))
Period of the heartbeat in seconds. The heartbeat is updated everyheartbeat_periodseconds.heartbeat_expire(
integer(1))
Time to live of the heartbeat in seconds. The heartbeat key is set to expire afterheartbeat_expireseconds.message_log(
character(1))
Path to the message log files e.g./tmp/message_logs/The message log files are namedmessage_<worker_id>.log. IfNULL, no messages, warnings or errors are stored.output_log(
character(1))
Path to the output log files e.g./tmp/output_logs/The output log files are namedoutput_<worker_id>.log. IfNULL, no output is stored.
Method wait_for_workers()
Wait until workers are registered in the network.
Either n, worker_ids or both must be provided.
Arguments
n(
integer(1))
Number of workers to wait for. IfNULL, wait for all workers inworker_ids.worker_ids(
character())
Worker ids to wait for. IfNULL, wait for anynworkers to be registered.timeout(
numeric(1))
Timeout in seconds. Default isInf.
Method stop_workers()
Stop workers.
Arguments
type(
character(1))
Type of stopping. Either"terminate"or"kill". If"kill"the workers are stopped immediately. If"terminate"the workers evaluate the currently running task and then terminate. The"terminate"option must be implemented in the worker loop.worker_ids(
character())
Worker ids to be stopped. IfNULLall workers are stopped.
Method detect_lost_workers()
Detect lost workers.
The state of the worker is changed to "terminated".
Returns
(character())
Worker ids of detected lost workers.
Method read_log()
Read log messages written with the lgr package by the workers.
Arguments
worker_ids(
character())
Worker ids to be read log messages from. Defaults to all worker ids.time_difference(
logical(1))
Whether to calculate the time difference between log messages.
Method print_log()
Print log messages written with the lgr package by the workers.
Log messages are printed with the original logger.
Method pop_task()
Pop a task from the queue and mark it as running.
Arguments
timeout(
numeric(1))
Time to wait for task in seconds.fields(
character())
Fields to be returned.
Method fail_tasks()
Mark tasks as failed and optionally save the condition objects
Arguments
keys(
character())
Keys of the tasks to be moved. Defaults to all queued tasks.conditions(named
list())
List of lists of conditions. Defaults tolist(message = "Failed").
Method push_tasks()
Create queued tasks and add them to the queue.
Returns
(character())
Keys of the tasks.
Method push_running_tasks()
Create running tasks.
Arguments
xss(list of named
list())
Lists of arguments for the function e.g.list(list(x1, x2), list(x1, x2))).extra(
list)
List of additional information stored along with the task e.g.list(list(timestamp), list(timestamp))).
Returns
(character())
Keys of the tasks.
Method push_finished_tasks()
Create finished tasks.
See $finish_tasks() for moving existing tasks from running to finished.
Arguments
xss(list of named
list())
Lists of arguments for the function e.g.list(list(x1, x2), list(x1, x2))).yss(list of named
list())
Lists of results for the function e.g.list(list(y1, y2), list(y1, y2))).xss_extra(
list)
List of additional information stored along with the task e.g.list(list(timestamp), list(timestamp))).yss_extra(
list)
List of additional information stored along with the results e.g.list(list(timestamp), list(timestamp))).
Returns
(character())
Keys of the tasks.
Method push_failed_tasks()
Create failed tasks.
See $fail_tasks() for moving existing tasks from queued and running to failed.
Returns
(character())
Keys of the tasks.
Method empty_queue()
Remove all tasks from the queue. The state of the tasks is set to failed.
Arguments
keys(
character())
Keys of the tasks to be moved. Defaults to all queued tasks.conditions(named
list())
List of lists of conditions.
Method fetch_tasks()
Fetch all tasks from the data base.
Usage
Rush$fetch_tasks(
fields = c("xs", "ys", "xs_extra", "worker_id", "ys_extra", "condition")
)Arguments
fields(
character())
Fields to be read from the hashes. Defaults toc("xs", "xs_extra", "worker_id", "ys", "ys_extra", "condition").
Method fetch_queued_tasks()
Fetch queued tasks from the data base.
Usage
Rush$fetch_queued_tasks(fields = c("xs", "xs_extra"))Arguments
fields(
character())
Fields to be read from the hashes. Defaults toc("xs", "xs_extra").
Method fetch_running_tasks()
Fetch running tasks from the data base.
Usage
Rush$fetch_running_tasks(fields = c("xs", "xs_extra", "worker_id"))Arguments
fields(
character())
Fields to be read from the hashes. Defaults toc("xs", "xs_extra", "worker_id").
Method fetch_failed_tasks()
Fetch failed tasks from the data base.
Usage
Rush$fetch_failed_tasks(fields = c("xs", "xs_extra", "worker_id", "condition"))Arguments
fields(
character())
Fields to be read from the hashes. Defaults toc("xs", "xs_extra", "worker_id", "condition".
Method fetch_finished_tasks()
Fetch finished tasks from the data base. Finished tasks are cached.
Usage
Rush$fetch_finished_tasks(
fields = c("worker_id", "xs", "ys", "xs_extra", "ys_extra", "condition")
)Arguments
fields(
character())
Fields to be read from the hashes. Defaults toc("xs", "xs_extra", "worker_id", "ys", "ys_extra").
Method fetch_tasks_with_state()
Fetch tasks with different states from the data base. If tasks with different states are to be queried at the same time, this function prevents tasks from appearing twice. This could be the case if a worker changes the state of a task while the tasks are being fetched. Finished tasks are cached.
Arguments
fields(
character())
Fields to be read from the hashes. Defaults toc("worker_id", "xs", "ys", "xs_extra", "ys_extra", "condition").states(
character())
States of the tasks to be fetched. Defaults toc("queued", "running", "finished", "failed").
Method fetch_new_tasks()
Fetch new tasks that finished after the last call of this function.
Updates the cache of the finished tasks.
If timeout is set, blocks until new tasks are available or the timeout is reached.
Usage
Rush$fetch_new_tasks(
fields = c("xs", "ys", "xs_extra", "worker_id", "ys_extra", "condition"),
timeout = 0
)Arguments
fields(
character())
Fields to be read from the hashes.timeout(
numeric(1))
Time to wait for new results in seconds. Defaults to0(no waiting).
Method wait_for_tasks()
Wait until tasks are finished. The function also unblocks when no worker is running or all tasks failed.
Arguments
keys(
character())
Keys of the tasks to wait for.detect_lost_workers(
logical(1))
Whether to detect failed tasks. Comes with an overhead.
Method write_hashes()
Writes R objects to Redis hashes.
The function takes the vectors in ... as input and writes each element as a field-value pair to a new hash.
The name of the argument defines the field into which the serialized element is written.
For example, xs = list(list(x1 = 1, x2 = 2), list(x1 = 3, x2 = 4)) writes serialize(list(x1 = 1, x2 = 2)) at field xs into a hash
and serialize(list(x1 = 3, x2 = 4)) at field xs into another hash.
The function can iterate over multiple vectors simultaneously.
For example, xs = list(list(x1 = 1, x2 = 2), list(x1 = 3, x2 = 4)), ys = list(list(y = 3), list(y = 7)) creates two hashes with the fields xs and ys.
The vectors are recycled to the length of the longest vector.
Both lists and atomic vectors are supported.
Arguments that are NULL are ignored.
Usage
Rush$write_hashes(..., .values = list(), keys = NULL)Returns
(character())
Keys of the hashes.
Method read_hashes()
Reads R Objects from Redis hashes.
The function reads the field-value pairs of the hashes stored at keys.
The values of a hash are deserialized and combined to a list.
If flatten is TRUE, the values are flattened to a single list e.g. list(xs = list(x1 = 1, x2 = 2), ys = list(y = 3)) becomes list(x1 = 1, x2 = 2, y = 3).
The reading functions combine the hashes to a table where the names of the inner lists are the column names.
For example, xs = list(list(x1 = 1, x2 = 2), list(x1 = 3, x2 = 4)), ys = list(list(y = 3), list(y = 7)) becomes data.table(x1 = c(1, 3), x2 = c(2, 4), y = c(3, 7)).
Arguments
keys(
character())
Keys of the hashes.fields(
character())
Fields to be read from the hashes.flatten(
logical(1))
Whether to flatten the list.
Returns
(list of list())
The outer list contains one element for each key.
The inner list is the combination of the lists stored at the different fields.
Method read_hash()
Reads a single Redis hash and returns the values as a list named by the fields.
Arguments
key(
character(1))
Key of the hash.fields(
character())
Fields to be read from the hash.
Returns
(list of list())
The outer list contains one element for each key.
The inner list is the combination of the lists stored at the different fields.
Method is_running_task()
Checks whether tasks have the status "running".
Arguments
keys(
character())
Keys of the tasks.
Method is_failed_task()
Checks whether tasks have the status "failed".
Arguments
keys(
character())
Keys of the tasks.
Method tasks_with_state()
Returns keys of requested states.
Arguments
states(
character())
States of the tasks.
Returns
(Named list of character()).
Method push_results()
Deprecated method.
Use $finish_tasks() instead.
Arguments
keys(
character())
Keys of the associated tasks.yss(named
list())
List of lists of named results.extra(named
list())
List of lists of additional information stored along with the results.
Method push_failed()
Deprecated method.
Use $fail_tasks() instead.
Arguments
keys(
character())
Keys of the associated tasks.conditions(
list())
List of conditions.
Examples
# This example is not executed since Redis must be installed
# \donttest{
config_local = redux::redis_config()
rush = rsh(network_id = "test_network", config = config_local)
rush
#>
#> ── <Rush> ──────────────────────────────────────────────────────────────────────
#> • Running Workers: 0
#> • Queued Tasks: 0
#> • Running Tasks: 0
#> • Finished Tasks: 0
#> • Failed Tasks: 0
# }