BE-614: HashQL: Generate synthetic closure bodies for intrinsics used as first-class values

[indietyp]

🌟 What is the purpose of this PR?

Allows intrinsics to be used in value position (passed as arguments, bound to variables) by generating synthetic MIR wrapper bodies during reification. Previously, intrinsics like <= could only appear at call sites where specialization rewrites them. Now they can flow through higher-order functions:

let apply = fn (a, b, f) = (f a b) in
(apply 2 3 <=)

🔍 What does this change?

Synthetic body generation:

• Synthetics struct in CrossCompileState manages creation and caching of wrapper bodies
• SyntheticBuilder generates MIR bodies with fat closure ABI (unit env as first parameter)
• T! macro for matching qualified paths against ConstantSymbol arrays: &T![::core::cmp::gt] in slice patterns, sym::path::core::cmp::gt::CONST for the name
• Dispatch table covers all first-classable intrinsics (comparison, boolean, arithmetic, bitwise) with local binary!/unary! macros deriving path and name from the same segments

Thin-call specialization:

• rvalue_call_thin_specialize recognizes Call(Thin, Qualified(intrinsic), []) (the administrative thunk-force from the thunking phase) and produces the closure aggregate directly, skipping thunk body generation
• Type unwrapping handles the thunking phase's () -> ClosureType wrapper to extract the actual signature

Intrinsic classification:

• First-classable: comparison (gt, lt, gte, lte, eq, ne), boolean (and, or, not), arithmetic (add, sub), bitwise (and, or, not)
• Unconstructible MIR ops (BinOp variants with ! payload): mul, div, rem, mod, pow, xor, shl, shr
• No MIR ops: sqrt, cbrt, root
• Not first-classable (syntactic forms): graph::head::entities, graph::body::filter, graph::tail::collect produce a specific user-facing diagnostic

Diagnostics:

• intrinsic_not_first_class: user-facing error for graph intrinsics in value position
• synthetic_binary_arity_mismatch / synthetic_unary_arity_mismatch: ICE for monomorphized type invariant violations

Pre-Merge Checklist 🚀

🚢 Has this modified a publishable library?

This PR:

• does not modify any publishable blocks or libraries, or modifications do not need publishing

📜 Does this require a change to the docs?

The changes in this PR:

• are internal and do not require a docs change

🕸️ Does this require a change to the Turbo Graph?

The changes in this PR:

• do not affect the execution graph

⚠️ Known issues

• Bare intrinsic at module root ("<=" as the entire program) is not supported. The thunking phase does not wrap the root body when it is a variable, so it never reaches the synthetic machinery. Tracked with a run: skip test.

🐾 Next steps

• Untyped property access (the original motivation for this work)
• Module system support for root-level qualified paths (BE-67)

🛡 What tests cover this?

Compiletests (8 new):

• reify/synthetic-intrinsic-value: basic synthetic body generation and thin-call specialization
• reify/synthetic-intrinsic-reused: same intrinsic used twice shares one body (caching)
• reify/synthetic-intrinsic-multiple: different intrinsics get separate bodies
• reify/synthetic-graph-not-first-class: graph intrinsic in value position produces error
• reify/synthetic-intrinsic-bare: bare intrinsic at root (run: skip)
• interpret/synthetic-intrinsic-value: end-to-end correctness (evaluates to true)
• post_inline/synthetic-intrinsic-hof: full optimization cascade with constants (collapses to return true)
• post_inline/synthetic-intrinsic-hof-dynamic: HOF with dynamic inputs collapses to bare x <= y

❓ How to test this?

cargo run --package hashql-compiletest -- run --filter "test(synthetic)"

📹 Demo

The post_inline/synthetic-intrinsic-hof-dynamic test shows the full cascade. A higher-order function receiving <= as a value with dynamic inputs:

Initial:  construct closure for <=, pass to apply, call through fat pointer
Final:    %0 = input LOAD x
          %1 = input LOAD y
          %2 = %0 <= %1
          return %2

All indirection eliminated. Indistinguishable from writing ["<=", x, y] directly.

[vercel]

The latest updates on your projects. Learn more about Vercel for GitHub.

Project	Deployment	Actions	Updated (UTC)
hash	Error		Jun 30, 2026 12:48pm

2 Skipped Deployments

Project	Deployment	Actions	Updated (UTC)
hashdotdesign-tokens	Ignored	Preview	Jun 30, 2026 12:48pm
petrinaut	Skipped		Jun 30, 2026 12:48pm

[cursor]

PR Summary

Medium Risk
Touches core MIR reification and closure/call lowering; behavior is well-covered by compiletests but wrong intrinsic dispatch or ABI could affect all HashQL compilation paths.

Overview
Enables intrinsics in value position (e.g. passing <= into a higher-order function) by generating cached synthetic MIR closure bodies during HIR→MIR reification, instead of treating qualified paths as unsupported.

A new Synthetics layer in reify matches known ::core::… paths, builds fat-closure ABI bodies (Source::Synthetic) for cmp/bool/math/bits ops, and optionally wraps them in thunks. operand on qualified variables resolves through synthetics to FnPtr thunks; rvalue_call_thin_specialize beta-reduces administrative Call(Thin, Qualified, []) into closure aggregates. Graph intrinsics in value position get intrinsic_not_first_class; unknown paths still fall back to the existing external-modules diagnostic without duplicates when a synthetic error was already emitted.

Supporting tweaks: From<ConstantSymbol> for Symbol, sym::lhs/sym::rhs, scratch.reset() after reify in graph compile, and compiletests for reify/interpret/post-inline behavior.

^{Reviewed by Cursor Bugbot for commit 85c859a. Bugbot is set up for automated code reviews on this repo. Configure here.}

[indietyp]

Warning

This pull request is not mergeable via GitHub because a downstack PR is open. Once all requirements are satisfied, merge this PR as a stack on Graphite.
Learn more

• BE-614: HashQL: Generate synthetic closure bodies for intrinsics used as first-class values #8895 👈 (View in Graphite)
• BE-615: HashQL: Introduce the concept of synthetic closures in the MIR #8894
• BE-607: HashQL: Refactor ModuleRegistry into builder/immutable split with allocator-generic stdlib construction #8887
• BE-538: HashQL: Permission system integration #8882
• BE-71: HashQL: Consolidate AST special-form expansion stages into one #8870
• BE-481: HashQL: Reify null and empty tuple as unit constants #8853
• BE-537, BE-537: hgraph: REST /hashql endpoint with E2E tests #8827
• BE-592: HashQL: Remove old eval graph path and core value types #8841
• BE-590: hgraph: Refactor entity query handlers into entity/query submodule #8840
• BE-587, BE-588: HashQL: Introduce CodeGenerationContext/CodeExecutionContext split and eval-stage Interner #8839
• BE-581, BE-589: HashQL: Introduce pass::lower/pass::place pipeline facades and fix cached constructor closure bug #8838
• BE-585, BE-591: HashQL: Add MIR interpreter test suite and refactor diagnostic categories #8837
• BE-583, BE-584, BE-586: HashQL: Add HeapPool, improve spans, and propagate Critical severity through diagnostics #8836
• BE-582: HashQL: Change opaque types from invariant to covariant #8835
• main

This stack of pull requests is managed by Graphite. Learn more about stacking.

[cursor]

Cursor Bugbot has reviewed your changes and found 1 potential issue.

^{❌ Bugbot Autofix is OFF. To automatically fix reported issues with cloud agents, enable autofix in the Cursor dashboard.}

^{Reviewed by Cursor Bugbot for commit 48906c1. Configure here.}

[codecov]

Codecov Report

❌ Patch coverage is 0% with 3 lines in your changes missing coverage. Please review.
⚠️ Please upload report for BASE (bm/be-615-hashql-introduce-synthetic-closures-and-trivial-closure@f03d9a1). Learn more about missing BASE report.

Files with missing lines	Patch %	Lines
libs/@local/hashql/core/src/symbol/mod.rs	0.00%	3 Missing ⚠️

Additional details and impacted files

@@                                         Coverage Diff                                          @@
##             bm/be-615-hashql-introduce-synthetic-closures-and-trivial-closure    #8895   +/-   ##
====================================================================================================
  Coverage                                                                     ?   81.98%           
====================================================================================================
  Files                                                                        ?      168           
  Lines                                                                        ?    25146           
  Branches                                                                     ?      717           
====================================================================================================
  Hits                                                                         ?    20616           
  Misses                                                                       ?     4323           
  Partials                                                                     ?      207           

Flag	Coverage Δ
rust.hashql-core	79.27% <0.00%> (?)
rust.hashql-syntax-jexpr	94.04% <ø> (?)

Flags with carried forward coverage won't be shown. Click here to find out more.

☔ View full report in Codecov by Harness.
📢 Have feedback on the report? Share it here.

🚀 New features to boost your workflow:

• ❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.
• 📦 JS Bundle Analysis: Save yourself from yourself by tracking and limiting bundle sizes in JS merges.

[codspeed-hq]

Merging this PR will degrade performance by 27.89%

❌ 1 regressed benchmark
✅ 55 untouched benchmarks
⏩ 24 skipped benchmarks¹

Warning

Please fix the performance issues or acknowledge them on CodSpeed.

Performance Changes

	Benchmark	BASE	HEAD	Efficiency
❌	pattern_match_constant	150.8 ns	209.2 ns	-27.89%

Tip

Investigate this regression by commenting @codspeedbot fix this regression on this PR, or directly use the CodSpeed MCP with your agent.

---

_{Comparing bm/be-614-hashql-generate-synthetic-mir-bodies-for-intrinsics-in-value (85c859a) with bm/be-615-hashql-introduce-synthetic-closures-and-trivial-closure (f03d9a1)}

Footnotes

1. 24 benchmarks were skipped, so the baseline results were used instead. If they were deleted from the codebase, click here and archive them to remove them from the performance reports. ↩

[Copilot]

Pull request overview

Copilot reviewed 25 out of 25 changed files in this pull request and generated 3 comments.

[github-actions]

Benchmark results

@rust/hash-graph-benches – Integrations

policy_resolution_large

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 2002	$$26.7 \mathrm{ms} \pm 174 \mathrm{μs}\left({\color{gray}1.88 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$3.41 \mathrm{ms} \pm 17.7 \mathrm{μs}\left({\color{gray}-3.213 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 1001	$$12.7 \mathrm{ms} \pm 100 \mathrm{μs}\left({\color{gray}0.770 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 3314	$$44.2 \mathrm{ms} \pm 383 \mathrm{μs}\left({\color{gray}1.66 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$15.0 \mathrm{ms} \pm 114 \mathrm{μs}\left({\color{gray}-1.675 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 1526	$$24.3 \mathrm{ms} \pm 171 \mathrm{μs}\left({\color{gray}-0.931 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 2078	$$27.9 \mathrm{ms} \pm 142 \mathrm{μs}\left({\color{gray}3.96 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.97 \mathrm{ms} \pm 60.1 \mathrm{μs}\left({\color{gray}2.47 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 1033	$$14.0 \mathrm{ms} \pm 87.7 \mathrm{μs}\left({\color{red}5.06 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_medium

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 102	$$3.73 \mathrm{ms} \pm 23.5 \mathrm{μs}\left({\color{gray}0.336 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$3.03 \mathrm{ms} \pm 16.0 \mathrm{μs}\left({\color{lightgreen}-12.233 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 51	$$3.35 \mathrm{ms} \pm 14.9 \mathrm{μs}\left({\color{gray}-3.334 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 269	$$5.21 \mathrm{ms} \pm 50.3 \mathrm{μs}\left({\color{gray}0.634 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$3.59 \mathrm{ms} \pm 17.3 \mathrm{μs}\left({\color{gray}-1.337 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 107	$$4.16 \mathrm{ms} \pm 31.4 \mathrm{μs}\left({\color{gray}0.974 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 133	$$4.37 \mathrm{ms} \pm 28.0 \mathrm{μs}\left({\color{gray}-0.558 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.50 \mathrm{ms} \pm 17.3 \mathrm{μs}\left({\color{gray}1.33 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 63	$$4.09 \mathrm{ms} \pm 31.2 \mathrm{μs}\left({\color{gray}1.34 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_none

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 2	$$2.72 \mathrm{ms} \pm 13.4 \mathrm{μs}\left({\color{gray}3.05 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.54 \mathrm{ms} \pm 15.3 \mathrm{μs}\left({\color{gray}1.50 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 1	$$2.69 \mathrm{ms} \pm 16.4 \mathrm{μs}\left({\color{gray}4.16 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 8	$$2.97 \mathrm{ms} \pm 14.6 \mathrm{μs}\left({\color{gray}2.06 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$2.78 \mathrm{ms} \pm 16.3 \mathrm{μs}\left({\color{gray}4.49 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 3	$$2.96 \mathrm{ms} \pm 18.1 \mathrm{μs}\left({\color{gray}3.56 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_small

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 52	$$3.03 \mathrm{ms} \pm 19.1 \mathrm{μs}\left({\color{gray}1.26 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.77 \mathrm{ms} \pm 18.6 \mathrm{μs}\left({\color{gray}0.026 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 25	$$2.96 \mathrm{ms} \pm 13.2 \mathrm{μs}\left({\color{gray}-0.949 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 94	$$3.39 \mathrm{ms} \pm 20.4 \mathrm{μs}\left({\color{gray}-1.993 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$2.94 \mathrm{ms} \pm 12.4 \mathrm{μs}\left({\color{gray}-0.704 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 26	$$3.26 \mathrm{ms} \pm 14.2 \mathrm{μs}\left({\color{gray}-0.252 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 66	$$3.33 \mathrm{ms} \pm 18.0 \mathrm{μs}\left({\color{gray}0.506 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$2.99 \mathrm{ms} \pm 16.9 \mathrm{μs}\left({\color{gray}1.48 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 29	$$3.35 \mathrm{ms} \pm 26.9 \mathrm{μs}\left({\color{gray}0.723 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_complete

Function	Value	Mean	Flame graphs
entity_by_id;one_depth	1 entities	$$42.8 \mathrm{ms} \pm 204 \mathrm{μs}\left({\color{gray}3.20 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	10 entities	$$33.4 \mathrm{ms} \pm 203 \mathrm{μs}\left({\color{lightgreen}-15.538 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	25 entities	$$36.3 \mathrm{ms} \pm 170 \mathrm{μs}\left({\color{lightgreen}-13.426 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	5 entities	$$32.1 \mathrm{ms} \pm 180 \mathrm{μs}\left({\color{lightgreen}-13.664 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	50 entities	$$42.7 \mathrm{ms} \pm 226 \mathrm{μs}\left({\color{lightgreen}-22.029 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	1 entities	$$50.0 \mathrm{ms} \pm 312 \mathrm{μs}\left({\color{lightgreen}-18.260 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	10 entities	$$41.2 \mathrm{ms} \pm 261 \mathrm{μs}\left({\color{lightgreen}-22.645 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	25 entities	$$93.4 \mathrm{ms} \pm 408 \mathrm{μs}\left({\color{lightgreen}-12.795 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	5 entities	$$35.0 \mathrm{ms} \pm 233 \mathrm{μs}\left({\color{lightgreen}-37.989 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	50 entities	$$276 \mathrm{ms} \pm 933 \mathrm{μs}\left({\color{lightgreen}-8.745 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	1 entities	$$10.5 \mathrm{ms} \pm 56.8 \mathrm{μs}\left({\color{lightgreen}-23.522 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	10 entities	$$10.6 \mathrm{ms} \pm 65.7 \mathrm{μs}\left({\color{lightgreen}-20.076 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	25 entities	$$10.7 \mathrm{ms} \pm 66.0 \mathrm{μs}\left({\color{lightgreen}-21.553 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	5 entities	$$10.4 \mathrm{ms} \pm 80.4 \mathrm{μs}\left({\color{lightgreen}-23.806 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	50 entities	$$10.7 \mathrm{ms} \pm 61.5 \mathrm{μs}\left({\color{lightgreen}-25.985 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_linkless

Function	Value	Mean	Flame graphs
entity_by_id	1 entities	$$10.5 \mathrm{ms} \pm 73.6 \mathrm{μs}\left({\color{lightgreen}-24.301 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10 entities	$$10.7 \mathrm{ms} \pm 50.2 \mathrm{μs}\left({\color{lightgreen}-21.928 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	100 entities	$$10.9 \mathrm{ms} \pm 66.7 \mathrm{μs}\left({\color{lightgreen}-22.613 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	1000 entities	$$11.1 \mathrm{ms} \pm 69.5 \mathrm{μs}\left({\color{lightgreen}-20.782 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10000 entities	$$10.9 \mathrm{ms} \pm 70.0 \mathrm{μs}\left({\color{lightgreen}-25.492 \mathrm{\%}}\right) $$	Flame Graph

representative_read_entity

Function	Value	Mean	Flame graphs
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/block/v/1	$$11.0 \mathrm{ms} \pm 101 \mathrm{μs}\left({\color{lightgreen}-23.437 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/book/v/1	$$11.1 \mathrm{ms} \pm 69.7 \mathrm{μs}\left({\color{lightgreen}-22.183 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/building/v/1	$$11.0 \mathrm{ms} \pm 57.4 \mathrm{μs}\left({\color{lightgreen}-14.912 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/organization/v/1	$$11.3 \mathrm{ms} \pm 75.1 \mathrm{μs}\left({\color{lightgreen}-20.391 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/page/v/2	$$10.9 \mathrm{ms} \pm 63.8 \mathrm{μs}\left({\color{lightgreen}-17.833 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/person/v/1	$$11.0 \mathrm{ms} \pm 56.2 \mathrm{μs}\left({\color{lightgreen}-22.408 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/playlist/v/1	$$11.3 \mathrm{ms} \pm 58.7 \mathrm{μs}\left({\color{lightgreen}-18.877 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/song/v/1	$$11.0 \mathrm{ms} \pm 71.3 \mathrm{μs}\left({\color{lightgreen}-22.823 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/uk-address/v/1	$$11.2 \mathrm{ms} \pm 75.0 \mathrm{μs}\left({\color{lightgreen}-16.767 \mathrm{\%}}\right) $$	Flame Graph

representative_read_entity_type

Function	Value	Mean	Flame graphs
get_entity_type_by_id	Account ID: bf5a9ef5-dc3b-43cf-a291-6210c0321eba	$$8.63 \mathrm{ms} \pm 50.6 \mathrm{μs}\left({\color{lightgreen}-16.663 \mathrm{\%}}\right) $$	Flame Graph

representative_read_multiple_entities

Function	Value	Mean	Flame graphs
entity_by_property	traversal_paths=0	0	$$60.5 \mathrm{ms} \pm 393 \mathrm{μs}\left({\color{lightgreen}-10.956 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$109 \mathrm{ms} \pm 532 \mathrm{μs}\left({\color{lightgreen}-15.839 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$68.6 \mathrm{ms} \pm 926 \mathrm{μs}\left({\color{lightgreen}-8.120 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$77.9 \mathrm{ms} \pm 608 \mathrm{μs}\left({\color{lightgreen}-8.637 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$82.5 \mathrm{ms} \pm 563 \mathrm{μs}\left({\color{lightgreen}-13.460 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$88.9 \mathrm{ms} \pm 547 \mathrm{μs}\left({\color{lightgreen}-13.593 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=0	0	$$45.0 \mathrm{ms} \pm 282 \mathrm{μs}\left({\color{lightgreen}-11.268 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$74.3 \mathrm{ms} \pm 389 \mathrm{μs}\left({\color{lightgreen}-11.610 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$52.0 \mathrm{ms} \pm 425 \mathrm{μs}\left({\color{lightgreen}-9.563 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$62.5 \mathrm{ms} \pm 338 \mathrm{μs}\left({\color{lightgreen}-10.507 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$63.8 \mathrm{ms} \pm 302 \mathrm{μs}\left({\color{lightgreen}-11.557 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$64.1 \mathrm{ms} \pm 275 \mathrm{μs}\left({\color{lightgreen}-10.835 \mathrm{\%}}\right) $$

scenarios

Function	Value	Mean	Flame graphs
full_test	query-limited	$$125 \mathrm{ms} \pm 595 \mathrm{μs}\left({\color{gray}-4.932 \mathrm{\%}}\right) $$	Flame Graph
full_test	query-unlimited	$$136 \mathrm{ms} \pm 449 \mathrm{μs}\left({\color{gray}-3.805 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-limited	$$23.6 \mathrm{ms} \pm 120 \mathrm{μs}\left({\color{red}29.6 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-unlimited	$$529 \mathrm{ms} \pm 894 \mathrm{μs}\left({\color{gray}-2.114 \mathrm{\%}}\right) $$	Flame Graph

[Copilot]

Pull request overview

Copilot reviewed 25 out of 25 changed files in this pull request and generated 2 comments.