derekbrown
GraphQL Performance Issues (using Absinthe)
Hey everyone! New to the forum, not new to Elixir. ![]()
In any case, recently had a discussion with @benwilson512 on overhead during GQL requests, and then saw a related question in the Absinthe channel on Slack, so decided to open it up here for input/guidance.
Problem
We’ve been tracing our API’s performance in Datadog and have seen some oddities that we can’t quite diagnose. Pictures are worth 1000 words, so here are some flame graphs for one request that demonstrates the issue:
The overall flame graph
1st Flame: Token Auth (in our Context)
2nd Flame: GQL Resolution
What’s happening in the gaps after auth/context and after the actual resolution?
This is just one request, but many of our requests have this shape, where the majority of the request has something unknown happening for at least 50ms or so. In some cases, we have 100ms or so unaccounted for, usually on the tail-end of the request post-resolution.
Environment
- App is released via
mix releaseto AWS (EC2 machine) and deployed behind an ELB (https). - Elixir 1.9.1, Erlang 22, Absinthe v1.5.0, Absinthe Plug v1.5.0-rc2, Absinthe Phoenix 1.5.0-rc.0
- The app is behind a Phoenix Router, Phoenix Endpoint, but is an API server.
Is anyone else seeing things like this? Happy to answer any other questions to help figure this out!
Most Liked
benwilson512
Awesome. Do note that once OTP 24 is released we’ve seen significant improvements from the JIT as well, so we expect the overhead to drop a further ~60% from that alone.
benwilson512
One key thing to check on is what your scalars are doing. Scalars are serialized in the result phase, which happens entirely after the resolution phase. In the past, poorly optimized serialization functions have lead to lengthy post-resolution times.
To dig in further, some additional metrics would be handy. Can you provide an example query document? How large is the result JSON in bytes? How large is the schema (approximated by MyAppWeb.Schema.__absinthe_types__ |> map_size)?
benwilson512
Hi @derekbrown I still need some sense of the size of the returned document. This will help diagnose time spent after the resolution phase constructing the actual JSON result.
While
I recommend using Telemetry to provide a few more data points, specifically the [:operation, :start] event would be very helpful because right now although it is likely that Absinthe starts work immediately after the context is set, in theory there could be other plugs or issues within Absinthe.Plug that are introducing delay. See Telemetry — absinthe v1.11.0 for details.
The document is relatively small, so processing on the document should happen pretty quickly. I’m going to take that document and create a project with a similar schema to see if we can reproduce the observed performance issues.
derekbrown
Update: I’ve been able to add Absinthe Telemetry events to the tracer, per reply above from @benwilson512 . Below are some observations and pretty pictures. I’ve tried to keep the same query here from the original post, for some apples-to-apples comparison. Hope this all helps.
- You’ll notice there’s a significant reduction in speed. The query document remains the same, along with the response size, more or less (if anything, the response is likely bigger). Part of this is attributed to some logic/DB work we’ve been doing underneath the query, and some of it is directly attributed to the
.uniqissue I mentioned earlier. Hope that helps anyone else with looking to increase performance.
Overall shape of the query. The first flame of spans is the context loading, followed by the operation.start event, followed by the first resolution.start event. We’ll zoom in subsequent screenshots, but there’s a significant gap between those two events, and after the operation.stop event.
Context to Operation Start. There’s a miniscule gap (≈300µs) between context being added and the operation starting, but not significant enough for us to blink.
Operation Start. The span on the right of the screenshot is the first resolution.start event, which is followed by the fetch_messages query in the overall screenshot above. Would we expect there to be a ≈6ms delay or so between operation start and resolution start?
Operation Stop. There’s a ≈10ms gap after operation.stop that’s unaccounted for. I’ll dig into what could be happening there (perhaps other plugs?). I don’t assume so there’s any cleanup or anything that Absinthe would be doing after the operation, is there?
Edits
Maybe a clue, or could be a rabbit trail: it seems that the delay to context matters whether or not it’s a query or mutation. The gap from trace start to context being added is much less for mutations.- The above is a rabbit trail. Doesn’t seem to be anything deterministic causing the delay before Context gets called.
benwilson512
The offer to investigate any runnable example stands! Do make sure to check out the persistent_term backend Absinthe.Schema.PersistentTerm — absinthe v1.11.0 which we’re promoting out of the Experimental namespace in the next release. It has proven to be both faster and easier to work with.
I’m seeing the original post was on Absinthe 1.5.0, and we definitely fixed an N^2 regression in our variable handling somewhere in a release between that and latest. Hopefully you’ve updated since!















