- âś” Fast communication between threads
- âś” Covers both fixed-task and variable-task scenarios
- âś” Supports flexible pool sizes
- âś” Proper async tracking integration
- âś” Tracking statistics for run and wait times
- âś” Cancellation Support
- âś” Supports enforcing memory resource limits
- âś” Supports CommonJS, ESM, and TypeScript
- âś” Custom task queues
- âś” Optional CPU scheduling priorities on Linux
Written in TypeScript.
For Node.js 16.x and higher.
In main.js
:
const path = require('path');
const Piscina = require('piscina');
const piscina = new Piscina({
filename: path.resolve(__dirname, 'worker.js')
});
(async function() {
const result = await piscina.run({ a: 4, b: 6 });
console.log(result); // Prints 10
})();
In worker.js
:
module.exports = ({ a, b }) => {
return a + b;
};
The worker may also be an async function or may return a Promise:
const { promisify } = require('util');
// Awaitable timers are available in Node.js 15.x+
// For Node.js 12 and 14, use promisify(setTimeout)
const { setTimeout } = require('timers/promises');
module.exports = async ({ a, b }) => {
// Fake some async activity
await setTimeout(100);
return a + b;
};
ESM is also supported for both Piscina and workers:
import { Piscina } from 'piscina';
const piscina = new Piscina({
// The URL must be a file:// URL
filename: new URL('./worker.mjs', import.meta.url).href
});
const result = await piscina.run({ a: 4, b: 6 });
console.log(result); // Prints 10
In worker.mjs
:
export default ({ a, b }) => {
return a + b;
};
A single worker file may export multiple named handler functions.
'use strict';
function add({ a, b }) { return a + b; }
function multiply({ a, b }) { return a * b; }
add.add = add;
add.multiply = multiply;
module.exports = add;
The export to target can then be specified when the task is submitted:
'use strict';
const Piscina = require('piscina');
const { resolve } = require('path');
const piscina = new Piscina({
filename: resolve(__dirname, 'worker.js')
});
(async function() {
const res = await Promise.all([
piscina.run({ a: 4, b: 6 }, { name: 'add' }),
piscina.run({ a: 4, b: 6 }, { name: 'multiply' })
]);
})();
Submitted tasks may be canceled using either an AbortController
or
an EventEmitter
:
'use strict';
const Piscina = require('piscina');
const { AbortController } = require('abort-controller');
const { resolve } = require('path');
const piscina = new Piscina({
filename: resolve(__dirname, 'worker.js')
});
(async function() {
const abortController = new AbortController();
try {
const { signal } = abortController;
const task = piscina.run({ a: 4, b: 6 }, { signal });
abortController.abort();
await task;
} catch (err) {
console.log('The task was canceled');
}
})();
To use AbortController
, you will need to npm i abort-controller
(or yarn add abort-controller
).
(In Node.js 15.0.0 or higher, there is a new built-in AbortController
implementation that can be used here as well.)
Alternatively, any EventEmitter
that emits an 'abort'
event
may be used as an abort controller:
'use strict';
const Piscina = require('piscina');
const EventEmitter = require('events');
const { resolve } = require('path');
const piscina = new Piscina({
filename: resolve(__dirname, 'worker.js')
});
(async function() {
const ee = new EventEmitter();
try {
const task = piscina.run({ a: 4, b: 6 }, { signal: ee });
ee.emit('abort');
await task;
} catch (err) {
console.log('The task was canceled');
}
})();
A worker thread will not be made available to process tasks until Piscina determines that it is "ready". By default, a worker is ready as soon as Piscina loads it and acquires a reference to the exported handler function.
There may be times when the availability of a worker may need to be delayed
longer while the worker initializes any resources it may need to operate.
To support this case, the worker module may export a Promise
that resolves
the handler function as opposed to exporting the function directly:
async function initialize() {
await someAsyncInitializationActivity();
return ({ a, b }) => a + b;
}
module.exports = initialize();
Piscina will await the resolution of the exported Promise before marking the worker thread available.
When the maxQueue
option is set, once the Piscina
queue is full, no
additional tasks may be submitted until the queue size falls below the
limit. The 'drain'
event may be used to receive notification when the
queue is empty and all tasks have been submitted to workers for processing.
Example: Using a Node.js stream to feed a Piscina worker pool:
'use strict';
const { resolve } = require('path');
const Pool = require('../..');
const pool = new Pool({
filename: resolve(__dirname, 'worker.js'),
maxQueue: 'auto'
});
const stream = getStreamSomehow();
stream.setEncoding('utf8');
pool.on('drain', () => {
if (stream.isPaused()) {
console.log('resuming...', counter, pool.queueSize);
stream.resume();
}
});
stream
.on('data', (data) => {
pool.run(data);
if (pool.queueSize === pool.options.maxQueue) {
console.log('pausing...', counter, pool.queueSize);
stream.pause();
}
})
.on('error', console.error)
.on('end', () => {
console.log('done');
});
Additional examples can be found in the GitHub repo at https://github.com/piscinajs/piscina/tree/master/examples
Piscina works by creating a pool of Node.js Worker Threads to which one or more tasks may be dispatched. Each worker thread executes a single exported function defined in a separate file. Whenever a task is dispatched to a worker, the worker invokes the exported function and reports the return value back to Piscina when the function completes.
This class extends EventEmitter
from Node.js.
- The following optional configuration is supported:
filename
: (string | null
) Provides the default source for the code that runs the tasks on Worker threads. This should be an absolute path or an absolutefile://
URL to a file that exports a JavaScriptfunction
orasync function
as its default export ormodule.exports
. ES modules are supported.name
: (string | null
) Provides the name of the default exported worker function. The default is'default'
, indicating the default export of the worker module.minThreads
: (number
) Sets the minimum number of threads that are always running for this thread pool. The default is based on the number of available CPUs.maxThreads
: (number
) Sets the maximum number of threads that are running for this thread pool. The default is based on the number of available CPUs.idleTimeout
: (number
) A timeout in milliseconds that specifies how long aWorker
is allowed to be idle, i.e. not handling any tasks, before it is shut down. By default, this is immediate. Tip: The defaultidleTimeout
can lead to some performance loss in the application because of the overhead involved with stopping and starting new worker threads. To improve performance, try setting theidleTimeout
explicitly.maxQueue
: (number
|string
) The maximum number of tasks that may be scheduled to run, but not yet running due to lack of available threads, at a given time. By default, there is no limit. The special value'auto'
may be used to have Piscina calculate the maximum as the square ofmaxThreads
. When'auto'
is used, the calculatedmaxQueue
value may be found by checking theoptions.maxQueue
property.concurrentTasksPerWorker
: (number
) Specifies how many tasks can share a single Worker thread simultaneously. The default is1
. This generally only makes sense to specify if there is some kind of asynchronous component to the task. Keep in mind that Worker threads are generally not built for handling I/O in parallel.useAtomics
: (boolean
) Use theAtomics
API for faster communication between threads. This is on by default. You can disableAtomics
globally by setting the environment variablePISCINA_DISABLE_ATOMICS
to1
.resourceLimits
: (object
) See Node.js new Worker optionsmaxOldGenerationSizeMb
: (number
) The maximum size of each worker threads main heap in MB.maxYoungGenerationSizeMb
: (number
) The maximum size of a heap space for recently created objects.codeRangeSizeMb
: (number
) The size of a pre-allocated memory range used for generated code.stackSizeMb
: (number
) The default maximum stack size for the thread. Small values may lead to unusable Worker instances. Default: 4
env
: (object
) If set, specifies the initial value ofprocess.env
inside the worker threads. See Node.js new Worker options for details.argv
: (any[]
) List of arguments that will be stringified and appended toprocess.argv
in the worker. See Node.js new Worker options for details.execArgv
: (string[]
) List of Node.js CLI options passed to the worker. See Node.js new Worker options for details.workerData
: (any
) Any JavaScript value that can be cloned and made available asrequire('piscina').workerData
. See Node.js new Worker options for details. Unlike regular Node.js Worker Threads,workerData
must not specify any value requiring atransferList
. This is because theworkerData
will be cloned for each pooled worker.taskQueue
: (TaskQueue
) By default, Piscina uses a first-in-first-out queue for submitted tasks. ThetaskQueue
option can be used to provide an alternative implementation. See Custom Task Queues for additional detail.niceIncrement
: (number
) An optional value that decreases priority for the individual threads, i.e. the higher the value, the lower the priority of the Worker threads. This value is only used on Linux and requires the optionalnice-napi
module to be installed. Seenice(2)
for more details.trackUnmanagedFds
: (boolean
) An optional setting that, whentrue
, will cause Workers to track file descriptors managed usingfs.open()
andfs.close()
, and will close them automatically when the Worker exits. Defaults totrue
. (This option is only supported on Node.js 12.19+ and all Node.js versions higher than 14.6.0).
Use caution when setting resource limits. Setting limits that are too low may
result in the Piscina
worker threads being unusable.
Schedules a task to be run on a Worker thread.
task
: Any value. This will be passed to the function that is exported fromfilename
.options
:transferList
: An optional lists of objects that is passed to [postMessage()
] when postingtask
to the Worker, which are transferred rather than cloned.filename
: Optionally overrides thefilename
option passed to the constructor for this task. If nofilename
was specified to the constructor, this is mandatory.name
: Optionally overrides the exported worker function used for the task.abortSignal
: An [AbortSignal
][] instance. If passed, this can be used to cancel a task. If the task is already running, the correspondingWorker
thread will be stopped. (More generally, anyEventEmitter
orEventTarget
that emits'abort'
events can be passed here.) Abortable tasks cannot share threads regardless of theconcurrentTasksPerWorker
options.
This returns a Promise
for the return value of the (async) function call
made to the function exported from filename
. If the (async) function throws
an error, the returned Promise
will be rejected with that error.
If the task is aborted, the returned Promise
is rejected with an error
as well.
Deprecated -- Use run(task, options)
instead.
Schedules a task to be run on a Worker thread.
task
: Any value. This will be passed to the function that is exported fromfilename
.transferList
: An optional lists of objects that is passed to [postMessage()
] when postingtask
to the Worker, which are transferred rather than cloned.filename
: Optionally overrides thefilename
option passed to the constructor for this task. If nofilename
was specified to the constructor, this is mandatory.abortSignal
: An [AbortSignal
][] instance. If passed, this can be used to cancel a task. If the task is already running, the correspondingWorker
thread will be stopped. (More generally, anyEventEmitter
orEventTarget
that emits'abort'
events can be passed here.) Abortable tasks cannot share threads regardless of theconcurrentTasksPerWorker
options.
This returns a Promise
for the return value of the (async) function call
made to the function exported from filename
. If the (async) function throws
an error, the returned Promise
will be rejected with that error.
If the task is aborted, the returned Promise
is rejected with an error
as well.
Stops all Workers and rejects all Promise
s for pending tasks.
This returns a Promise
that is fulfilled once all threads have stopped.
An 'error'
event is emitted by instances of this class when:
- Uncaught exceptions occur inside Worker threads that do not currently handle tasks.
- Unexpected messages are sent from from Worker threads.
All other errors are reported by rejecting the Promise
returned from
run()
or runTask()
, including rejections reported by the handler function
itself.
A 'drain'
event is emitted whenever the queueSize
reaches 0
.
A 'message'
event is emitted whenever a message is received from a worker thread.
The current number of completed tasks.
The length of time (in milliseconds) since this Piscina
instance was
created.
A copy of the options that are currently being used by this instance. This object has the same properties as the options object passed to the constructor.
A histogram summary object summarizing the collected run times of completed tasks. All values are expressed in milliseconds.
runTime.average
{number
} The average run time of all tasksrunTime.mean
{number
} The mean run time of all tasksrunTime.stddev
{number
} The standard deviation of collected run timesrunTime.min
{number
} The fastest recorded run timerunTime.max
{number
} The slowest recorded run time
All properties following the pattern p{N}
where N is a number (e.g. p1
, p99
)
represent the percentile distributions of run time observations. For example,
p99
is the 99th percentile indicating that 99% of the observed run times were
faster or equal to the given value.
{
average: 1880.25,
mean: 1880.25,
stddev: 1.93,
min: 1877,
max: 1882.0190887451172,
p0_001: 1877,
p0_01: 1877,
p0_1: 1877,
p1: 1877,
p2_5: 1877,
p10: 1877,
p25: 1877,
p50: 1881,
p75: 1881,
p90: 1882,
p97_5: 1882,
p99: 1882,
p99_9: 1882,
p99_99: 1882,
p99_999: 1882
}
An Array of the Worker
instances used by this pool.
The current number of tasks waiting to be assigned to a Worker thread.
A point-in-time ratio comparing the approximate total mean run time of completed tasks to the total runtime capacity of the pool.
A pools runtime capacity is determined by multiplying the duration
by the options.maxThread
count. This provides an absolute theoretical
maximum aggregate compute time that the pool would be capable of.
The approximate total mean run time is determined by multiplying the mean run time of all completed tasks by the total number of completed tasks. This number represents the approximate amount of time the pool as been actively processing tasks.
The utilization is then calculated by dividing the approximate total
mean run time by the capacity, yielding a fraction between 0
and 1
.
A histogram summary object summarizing the collected times tasks spent waiting in the queue. All values are expressed in milliseconds.
waitTime.average
{number
} The average wait time of all taskswaitTime.mean
{number
} The mean wait time of all taskswaitTime.stddev
{number
} The standard deviation of collected wait timeswaitTime.min
{number
} The fastest recorded wait timewaitTime.max
{number
} The longest recorded wait time
All properties following the pattern p{N}
where N is a number (e.g. p1
, p99
)
represent the percentile distributions of wait time observations. For example,
p99
is the 99th percentile indicating that 99% of the observed wait times were
faster or equal to the given value.
{
average: 1880.25,
mean: 1880.25,
stddev: 1.93,
min: 1877,
max: 1882.0190887451172,
p0_001: 1877,
p0_01: 1877,
p0_1: 1877,
p1: 1877,
p2_5: 1877,
p10: 1877,
p25: 1877,
p50: 1881,
p75: 1881,
p90: 1882,
p97_5: 1882,
p99: 1882,
p99_9: 1882,
p99_99: 1882,
p99_999: 1882
}
Is true
if this code runs inside a Piscina
threadpool as a Worker.
Provides the current version of this library as a semver string.
By default, any value returned by a worker function will be cloned when
returned back to the Piscina pool, even if that object is capable of
being transfered. The Piscina.move()
method can be used to wrap and
mark transferable values such that they will by transfered rather than
cloned.
The value
may be any object supported by Node.js to be transferable
(e.g. ArrayBuffer
, any TypedArray
, or MessagePort
), or any object
implementing the Transferable
interface.
const { move } = require('piscina');
module.exports = () => {
return move(new ArrayBuffer(10));
}
The move()
method will throw if the value
is not transferable.
The object returned by the move()
method should not be set as a
nested value in an object. If it is used, the move()
object itself
will be cloned as opposed to transfering the object it wraps.
Objects may implement the Transferable
interface to create their own
custom transferable objects. This is useful when an object being
passed into or from a worker contains a deeply nested transferable
object such as an ArrayBuffer
or MessagePort
.
Transferable
objects expose two properties inspected by Piscina
to determine how to transfer the object. These properties are
named using the special static Piscina.transferableSymbol
and
Piscina.valueSymbol
properties:
-
The
Piscina.transferableSymbol
property provides the object (or objects) that are to be included in thetransferList
. -
The
Piscina.valueSymbol
property provides a surrogate value to transmit in place of theTransferable
itself.
Both properties are required.
For example,
const {
move,
transferableSymbol,
valueSymbol
} = require('piscina');
module.exports = () => {
const obj = {
a: { b: new Uint8Array(5); },
c: { new Uint8Array(10); },
get [transferableSymbol]() {
// Transfer the two underlying ArrayBuffers
return [this.a.b.buffer, this.c.buffer];
}
get [valueSymbol]() {
return { a: { b: this.a.b }, c: this.c };
}
};
return move(obj);
};
By default, Piscina uses a simple array-based first-in-first-out (fifo) task queue. When a new task is submitted and there are no available workers, tasks are pushed on to the queue until a worker becomes available.
If the default fifo queue is not sufficient, user code may replace the
task queue implementation with a custom implementation using the
taskQueue
option on the Piscina constructor.
Custom task queue objects must implement the TaskQueue
interface,
described below using TypeScript syntax:
interface Task {
readonly [Piscina.queueOptionsSymbol] : object | null;
}
interface TaskQueue {
readonly size : number;
shift () : Task | null;
remove (task : Task) : void;
push (task : Task) : void;
}
An example of a custom task queue that uses a shuffled priority queue
is available in examples/task-queue
;
The special symbol Piscina.queueOptionsSymbol
may be set as a property
on tasks submitted to run()
or runTask()
as a way of passing additional
options on to the custom TaskQueue
implementation. (Note that because the
queue options are set as a property on the task, tasks with queue
options cannot be submitted as JavaScript primitives).
- Improved Documentation
- Benchmarks
Workers are generally optimized for offloading synchronous, compute-intensive operations off the main Node.js event loop thread. While it is possible to perform asynchronous operations and I/O within a Worker, the performance advantages of doing so will be minimal.
Specifically, it is worth noting that asynchronous operations within Node.js, including I/O such as file system operations or CPU-bound tasks such as crypto operations or compression algorithms, are already performed in parallel by Node.js and libuv on a per-process level. This means that there will be little performance impact on moving such async operations into a Piscina worker (see examples/scrypt for example).
Piscina provides the ability to configure the minimum and
maximum number of worker threads active in the pool, as well as
set limits on the number of tasks that may be queued up waiting
for a free worker. It is important to note that setting the
maxQueue
size too high relative to the number of worker threads
can have a detrimental impact on performance and memory usage.
Setting the maxQueue
size too small can also be problematic
as doing so could cause your worker threads to become idle and
be shutdown. Our testing has shown that a maxQueue
size of
approximately the square of the maximum number of threads is
generally sufficient and performs well for many cases, but this
will vary significantly depending on your workload. It will be
important to test and benchmark your worker pools to ensure you've
effectively balanced queue wait times, memory usage, and worker
pool utilization.
The thread pool maintained by Piscina has both a minimum and maximum
limit to the number of threads that may be created. When a Piscina
instance is created, it will spawn the minimum number of threads
immediately, then create additional threads as needed up to the
limit set by maxThreads
. Whenever a worker completes a task, a
check is made to determine if there is additional work for it to
perform. If there is no additional work, the thread is marked idle.
By default, idle threads are shutdown immediately, with Piscina
ensuring that the pool always maintains at least the minimum.
When a Piscina pool is processing a stream of tasks (for instance, processing http server requests as in the React server-side rendering example in examples/react-ssr), if the rate in which new tasks are received and queued is not sufficient to keep workers from going idle and terminating, the pool can experience a thrashing effect -- excessively creating and terminating workers that will cause a net performance loss. There are a couple of strategies to avoid this churn:
Strategy 1: Ensure that the queue rate of new tasks is sufficient to keep workers from going idle. We refer to this as "queue pressure". If the queue pressure is too low, workers will go idle and terminate. If the queue pressure is too high, tasks will stack up, experience increased wait latency, and consume additional memory.
Strategy 2: Increase the idleTimeout
configuration option. By
default, idle threads terminate immediately. The idleTimeout
option
can be used to specify a longer period of time to wait for additional
tasks to be submitted before terminating the worker. If the queue
pressure is not maintained, this could result in workers sitting idle
but those will have less of a performance impact than the thrashing
that occurs when threads are repeatedly terminated and recreated.
Strategy 3: Increase the minThreads
configuration option. This has
the same basic effect as increasing the idleTimeout
. If the queue
pressure is not high enough, workers may sit idle indefinitely but
there will be less of a performance hit.
In applications using Piscina, it will be most effective to use a combination of these three approaches and tune the various configuration parameters to find the optimum combination both for the application workload and the capabilities of the deployment environment. There are no one set of options that are going to work best.
On Linux systems that support nice(2)
, Piscina is capable of setting
the priority of every worker in the pool. To use this mechanism, an additional
optional native addon dependency (nice-napi
, npm i nice-napi
) is required.
Once nice-napi
is installed, creating a Piscina
instance with the
niceIncrement
configuration option will set the priority for the pool:
const Piscina = require('piscina');
const pool = new Piscina({
worker: '/absolute/path/to/worker.js',
niceIncrement: 20
});
The higher the niceIncrement
, the lower the CPU scheduling priority will be
for the pooled workers which will generally extend the execution time of
CPU-bound tasks but will help prevent those threads from stealing CPU time from
the main Node.js event loop thread. Whether this is a good thing or not depends
entirely on your application and will require careful profiling to get correct.
The key metrics to pay attention to when tuning the niceIncrement
are the
sampled run times of the tasks in the worker pool (using the runTime
property) and the delay of the Node.js main thread event loop.
Every Piscina
instance creates a separate pool of threads and operates
without any awareness of the other. When multiple pools are created in a
single application the various threads may contend with one another, and
with the Node.js main event loop thread, and may cause an overall reduction
in system performance.
Modules that embed Piscina as a dependency should make it clear via
documentation that threads are being used. It would be ideal if those
would make it possible for users to provide an existing Piscina
instance
as a configuration option in lieu of always creating their own.
- Drop Node.js 14.x support
- Add Node.js 20.x to CI
- Adds a new
PISCINA_DISABLE_ATOMICS
environment variable as an alternative way of disabling Piscina's internal use of theAtomics
API. (piscinajs#163) - Fixes a bug with transferable objects. (piscinajs#155)
- Fixes CI issues with TypeScript. (piscinajs#161)
- Deprecates
piscina.runTask()
; addspiscina.run()
as an alternative. https://github.com/piscinajs/piscina/commit/d7fa24d7515789001f7237ad6ae9ad42d582fc75 - Allows multiple exported handler functions from a single file. https://github.com/piscinajs/piscina/commit/d7fa24d7515789001f7237ad6ae9ad42d582fc75
- Drops Node.js 10.x support
- Updates minimum TypeScript target to ES2019
- Adds name property to indicate
AbortError
when tasks are canceled using anAbortController
(or similar) - More examples
- Added unmanaged file descriptor tracking
- Updated dependencies
- Bug fix: Reject if AbortSignal is already aborted
- Bug Fix: Use once listener for abort event
- Add the
niceIncrement
configuration parameter.
- Bug fixes around abortable task selection.
- Added
Piscina.move()
- Added Custom Task Queues
- Added utilization metric
- Wait for workers to be ready before considering them as candidates
- Additional examples
- Added
maxQueue = 'auto'
to autocalculate the maximum queue size. - Added more examples, including an example of implementing a worker as a Node.js native addon.
- Added the
'drain'
event
- Added support for ESM and file:// URLs
- Added
env
,argv
,execArgv
, andworkerData
options - More examples
- Added support for Worker Thread
resourceLimits
- Initial release!
- James M Snell [email protected]
- Anna Henningsen [email protected]
- Matteo Collina [email protected]
Piscina development is sponsored by NearForm Research.