Queryify has_attr to improve performance

[camelid]

Inspired by #127144 (review)
and previous success in #94897.

r? @compiler-errors

[camelid]

@bors try @rust-timer queue

[camelid]

@bors try

[bors]

⌛ Trying commit a75363e with merge 53af5a5...

[fmease]

Suggested change

	pub fn has_attr_query(tcx: TyCtxt<'_>, key: (DefId, Symbol)) -> bool {
	let (did, attr) = key;
	pub fn has_attr_query(tcx: TyCtxt<'_>, (did, attr): (DefId, Symbol)) -> bool {

[camelid]

Thanks, I'll change that after the perf run. I forgot to change it from the query declaration's signature 😅

[bors]

☀️ Try build successful - checks-actions
Build commit: 53af5a5 (53af5a5241258dccb46c7775eee0cecbaafaff7e)

[rust-timer]

Finished benchmarking commit (53af5a5): comparison URL.

Overall result: ❌ regressions - ACTION NEEDED

Benchmarking this pull request likely means that it is perf-sensitive, so we're automatically marking it as not fit for rolling up. While you can manually mark this PR as fit for rollup, we strongly recommend not doing so since this PR may lead to changes in compiler perf.

Next Steps: If you can justify the regressions found in this try perf run, please indicate this with @rustbot label: +perf-regression-triaged along with sufficient written justification. If you cannot justify the regressions please fix the regressions and do another perf run. If the next run shows neutral or positive results, the label will be automatically removed.

@bors rollup=never
@rustbot label: -S-waiting-on-perf +perf-regression

Instruction count

This is a highly reliable metric that was used to determine the overall result at the top of this comment.

	mean	range	count
Regressions ❌ (primary)	1.5%	[0.2%, 4.7%]	165
Regressions ❌ (secondary)	2.2%	[0.4%, 5.5%]	72
Improvements ✅ (primary)	-	-	0
Improvements ✅ (secondary)	-2.0%	[-2.0%, -2.0%]	1
All ❌✅ (primary)	1.5%	[0.2%, 4.7%]	165

Max RSS (memory usage)

Results (primary 3.8%, secondary 7.1%)

This is a less reliable metric that may be of interest but was not used to determine the overall result at the top of this comment.

	mean	range	count
Regressions ❌ (primary)	3.8%	[1.0%, 13.5%]	34
Regressions ❌ (secondary)	7.1%	[4.5%, 11.5%]	9
Improvements ✅ (primary)	-	-	0
Improvements ✅ (secondary)	-	-	0
All ❌✅ (primary)	3.8%	[1.0%, 13.5%]	34

Cycles

Results (primary 2.6%, secondary 4.0%)

This is a less reliable metric that may be of interest but was not used to determine the overall result at the top of this comment.

	mean	range	count
Regressions ❌ (primary)	2.6%	[0.9%, 6.1%]	70
Regressions ❌ (secondary)	4.0%	[2.3%, 7.5%]	30
Improvements ✅ (primary)	-	-	0
Improvements ✅ (secondary)	-	-	0
All ❌✅ (primary)	2.6%	[0.9%, 6.1%]	70

Binary size

This benchmark run did not return any relevant results for this metric.

Bootstrap: 697.442s -> 697.826s (0.06%)
Artifact size: 324.64 MiB -> 324.63 MiB (-0.00%)

[camelid]

Hmm how could this cause such major regressions across the board? Is the extra overheard of the query system really that much?

[cjgillot]

Yes, that's the query overhead.

As a general rule, a query should either:

• take sufficiently long to make memorization + incr caching worth it;
• allow to hide enough information to avoid recomputing the caller query.

[camelid]

Makes sense, thanks!