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graphile-worker is not intended to replace extremely high performance dedicated job queues, it's intended to be a very easy way to get a reasonably performant job queue up and running with Node.js and PostgreSQL. But this doesn't mean it's a slouch by any means it achieves an average latency from triggering a job in one process to executing it in another of under 3ms, and a 12-core database server can queue around 99,600 jobs per second and can process around 11,800 jobs per second.

graphile-worker is horizontally scalable to a point. Each instance has a customizable worker pool, this pool defaults to size 1 (only one job at a time on this worker) but depending on the nature of your tasks (i.e. assuming they're not compute-heavy) you will likely want to set this higher to benefit from Node.js' concurrency. If your tasks are compute heavy you may still wish to set it higher and then using Node's child_process (or Node v11's worker_threads) to share the compute load over multiple cores without significantly impacting the main worker's run loop. Note, however, that Graphile Worker is limited by the performance of the underlying Postgres database, and when you hit this limit performance will start to go down (rather than up) as you add more workers.

To test performance, you can run yarn perfTest. This runs three tests:

  1. a startup/shutdown test to see how fast the worker can startup and exit if there's no jobs queued (this includes connecting to the database and ensuring the migrations are up to date)
  2. a load test by default this will run 20,000 trivial jobs with a parallelism of 4 (i.e. 4 node processes) and a concurrency of 10 (i.e. 10 concurrent jobs running on each node process), but you can configure this in perfTest/run.js. (These settings were optimized for a 12-core hyper-threading machine running both the tests and the database locally.)
  3. a latency test determining how long between issuing an add_job command and the task itself being executed.

perfTest results:

The test was ran on a 12-core AMD Ryzen 3900 with an M.2 SSD, running both the workers and the database (and a tonne of Chrome tabs, electron apps, and what not). Jobs=20000, parallelism=4, concurrency=10.


  • Startup/shutdown: 110ms
  • Jobs per second: 11,851
  • Average latency: 2.66ms (min: 2.39ms, max: 12.09ms)
Timing startup/shutdown time...
... it took 110ms

Scheduling 20000 jobs
Adding jobs: 200.84ms
... it took 287ms

Timing 20000 job execution...
Found 999!

... it took 1797ms
Jobs per second: 11851.90

Testing latency...
[core] INFO: Worker connected and looking for jobs... (task names: 'latency')
Beginning latency test
Latencies - min: 2.39ms, max: 12.09ms, avg: 2.66ms

TODO: post perfTest results in a more reasonable configuration, e.g. using an RDS PostgreSQL server and a worker running on EC2.

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