See: https://github.com/grafana/k6/issues/2685
It might be interesting to think about taking into consideration decompression time when thinking about performance, but In general I think doing so is surprising and I wasted a lot of time trying to figure out why my optimizations to the compression codepath weren't improving things to the degree I expected
The downside here is we lose error reporting, so you'll need to only set
discardResponseBodies: true after the query has been tested.
PR-URL: https://github.com/hasura/graphql-engine-mono/pull/5940
GitOrigin-RevId: 82a589a59b93f10ffb5391e4a3190459fb6e613b
### Description
This PR adds a new benchmarl set named `deep_schema`, that is made to replicate one very specific edge-case: schemas that have deeply nested remote relationships. Our schema-building code is, in essence, "depth-first", and there are a lot of subtleties in the way we jump across remote relationship boundaries: this set will allows us to better understand the performance implications of technical decisions we make wrt. schema building.
This set, unlike others, does not declare any query: we are, for now, only interested in the schema building, which is tested with an ad-hoc script.
## Remaining work
There are several points worth discussing, wrt. this PR:
- should we make the schema larger, to make measures more consistent?
- should we extend this idea of measuring schema build performance to other sets?
- how do we extend the report to include this new information?
PR-URL: https://github.com/hasura/graphql-engine-mono/pull/5517
GitOrigin-RevId: 9d8f4fddb9bbdca5ef85f3d22337b992acf13bce
…rking metadata operations
And add an initial benchmark for replace_metadata, to unblock some
performance improvements to that op in a PR to be merged after this.
This is an MVP just to have something in CI to reference when optimizing
metadata operations. See TODO for roadmap.
PR-URL: https://github.com/hasura/graphql-engine-mono/pull/3673
Co-authored-by: jkachmar <8461423+jkachmar@users.noreply.github.com>
GitOrigin-RevId: 968d1f92ca79c78ad90b2304d2214069bc739621
