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Performance Notes

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).

Queue Size​

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.

Queue Pressure and Idle Threads​

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.

Thread priority on Linux systems​

On Unix systems that support [nice(2)][https://linux.die.net/man/2/nice] and Windows, Piscina is capable of setting the priority of every worker in the pool. To use this mechanism, an additional optional native addon dependency (@napi-rs/nice, npm i @napi-rs/nice) is required. Once [@napi-rs/nice][https://www.npmjs.com/package/@napi-rs/nice] is installed, creating a Piscinainstance with theniceIncrement configuration option will set the priority for the pool:

const Piscina = require('piscina')
const { WindowsThreadPriority } = require('@napi-rs/nice')
const pool = new Piscina({
  worker: '/absolute/path/to/worker.js',
  niceIncrement:
    process.platform !== 'win32'
      ? 20
      : WindowsThreadPriority.ThreadPriorityHighest,
})

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][].

Multiple Thread Pools and Embedding Piscina as a Dependency​

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.