BE-303: HashQL: Split MIR basic blocks by target support #8354

indietyp · 2026-02-03T20:47:17Z

🌟 What is the purpose of this PR?

Introduce a MIR execution-analysis pass that splits basic blocks into contiguous regions with uniform target support, returning per-block target affinities for downstream scheduling.

🔍 What does this change?

Add a basic-block splitting pass that remaps block IDs, inserts Goto chains between split regions, and returns target affinities.
Add unit and snapshot coverage for splitting behavior and cost remapping.
Extend execution-analysis data structures to support target bitsets/arrays and cost remapping.

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

🛡 What tests cover this?

New unit tests and snapshot coverage for the splitting pass.

❓ How to test this?

Run the hashql-mir test suite that includes execution spli

vercel · 2026-02-03T20:47:22Z

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Project	Deployment	Actions	Updated (UTC)
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cursor · 2026-02-03T20:47:23Z

PR Summary

Medium Risk
Touches MIR control-flow structure by rewriting basic blocks and remapping IDs; mistakes could miswire jumps or desync statement-cost indexing, though the change is well-covered by targeted unit and snapshot tests.

Overview
Adds a new execution-analysis pass (execution::splitting) that splits MIR basic blocks into contiguous runs of statements with identical per-target support, rewrites all BasicBlockId references, and inserts Goto chains to preserve control flow while returning per-block TargetBitSet affinities.

Refactors execution cost bookkeeping to support block splitting by introducing StatementCostVec::remap/of and switching target indexing to typed containers (TargetArray = IdArray, TargetBitSet = FiniteBitSet). Core ID utilities are extended with IdArray, a reimplemented FiniteBitSet (single-integer backing + range ops + iterator + relations), and IdSlice::windows to support the splitting algorithm.

Adds extensive unit + snapshot tests covering region counting, block/terminator rewrites, ID remapping, and cost offset remapping.

^{Written by Cursor Bugbot for commit 3655222. This will update automatically on new commits. Configure here.}

indietyp · 2026-02-03T20:48:17Z

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codecov · 2026-02-03T20:50:50Z

Codecov Report

❌ Patch coverage is 96.56020% with 28 lines in your changes missing coverage. Please review.
✅ Project coverage is 66.70%. Comparing base (1068059) to head (3655222).

Files with missing lines	Patch %	Lines
...l/mir/src/pass/analysis/execution/splitting/mod.rs	91.27%	9 Missing and 4 partials ⚠️
...mir/src/pass/analysis/execution/splitting/tests.rs	98.10%	6 Missing and 6 partials ⚠️
...l/hashql/mir/src/pass/analysis/execution/target.rs	0.00%	3 Missing ⚠️

Additional details and impacted files

@@                                     Coverage Diff                                     @@
##           bm/be-364-hashql-rework-symbol-to-be-faster-and-smaller    #8354      +/-   ##
===========================================================================================
- Coverage                                                    75.00%   66.70%   -8.31%     
===========================================================================================
  Files                                                          233      795     +562     
  Lines                                                        35772    71813   +36041     
  Branches                                                       851     3888    +3037     
===========================================================================================
+ Hits                                                         26831    47901   +21070     
- Misses                                                        8651    23364   +14713     
- Partials                                                       290      548     +258

Flag	Coverage Δ
apps.hash-ai-worker-ts	`1.41% <ø> (?)`
apps.hash-api	`0.00% <ø> (?)`
local.hash-graph-sdk	`10.88% <ø> (?)`
local.hash-isomorphic-utils	`0.00% <ø> (?)`
rust.hash-graph-api	`2.88% <ø> (ø)`
rust.hashql-ast	`87.25% <ø> (?)`
rust.hashql-compiletest	`29.69% <ø> (?)`
rust.hashql-eval	`69.13% <ø> (ø)`
rust.hashql-hir	`89.11% <ø> (ø)`
rust.hashql-mir	`90.65% <96.56%> (?)`
rust.hashql-syntax-jexpr	`94.05% <ø> (ø)`

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

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codspeed-hq · 2026-02-03T20:52:41Z

CodSpeed Performance Report

Merging this PR will not alter performance

_{Comparing bm/be-303-hashql-split-basic-blocks-depending-on-largest-available (3655222) with bm/be-364-hashql-rework-symbol-to-be-faster-and-smaller (1068059)}

Summary

✅ 41 untouched benchmarks
🗄️ 12 archived benchmarks run¹

12 benchmarks were run, but are now archived. If they were deleted in another branch, consider rebasing to remove them from the report. Instead if they were added back, click here to restore them. ↩

augmentcode · 2026-02-03T20:55:42Z

🤖 Augment PR Summary

Summary: This PR introduces a MIR execution-analysis pass that splits basic blocks into contiguous regions with uniform execution-target support, producing per-block target affinities for downstream scheduling.

Changes:

Add a new BasicBlockSplitting pass that remaps BasicBlockIds, inserts Goto chains between split regions, and returns TargetBitSet affinities.
Extend execution cost tracking with StatementCostVec::remap, per-block cost slicing (of), and allocator access.
Introduce IdArray (fixed-size, ID-indexed array) and re-implement a fixed-size FiniteBitSet for compact target bitsets.
Update target abstractions with TargetArray/TargetBitSet aliases and adjust target ID layout.
Add comprehensive unit tests and UI snapshot coverage for splitting behavior, block ID remapping, and cost remapping.

Technical Notes: The split pass relies on per-statement cost presence to derive target support, and performs an in-place basic block list expansion/swap to keep statement order stable while changing block IDs.

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augmentcode

Review completed. 2 suggestions posted.

Comment augment review to trigger a new review at any time.

augmentcode · 2026-02-03T20:55:47Z

libs/@local/hashql/core/src/id/array.rs

+        let mut index = I::MIN;
+        IdArray::from_raw(self.raw.map(|elem| {
+            let value = func(index, elem);
+            index.increment_by(1);


IdArray::map_enumerated increments index after every element; on the last element this will call increment_by(1) once past the final valid ID. If I’s valid range is tight (e.g. 0..=N-1), that trailing increment will panic even though no further IDs are needed.

Severity: medium

_{🤖 Was this useful? React with 👍 or 👎, or 🚀 if it prevented an incident/outage.}

libs/@local/hashql/mir/src/pass/analysis/execution/cost.rs

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.}

cursor · 2026-02-03T20:59:26Z

libs/@local/hashql/mir/src/pass/analysis/execution/target.rs

+    #[must_use]
+    pub const fn all() -> [Self; Self::TOTAL] {
+        [Self::POSTGRES, Self::EMBEDDING, Self::INTERPRETER]
+    }


TargetId::all() returns targets in wrong index order

Low Severity

The TargetId::all() function returns [POSTGRES, EMBEDDING, INTERPRETER] which corresponds to ID values [1, 2, 0]. This is inconsistent with the natural index ordering expected when building or indexing a TargetArray. If someone uses all() to populate an array positionally and then indexes it using TargetId values, they'll get mismatched data—for example, array[TargetId::INTERPRETER] would return data computed for POSTGRES instead.

github-actions · 2026-02-03T22:00:15Z

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	$$27.4 \mathrm{ms} \pm 151 \mathrm{μs}\left({\color{gray}3.79 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$3.25 \mathrm{ms} \pm 19.4 \mathrm{μs}\left({\color{gray}0.885 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 1001	$$12.9 \mathrm{ms} \pm 93.0 \mathrm{μs}\left({\color{red}6.89 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 3314	$$43.1 \mathrm{ms} \pm 300 \mathrm{μs}\left({\color{gray}0.700 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$14.7 \mathrm{ms} \pm 83.5 \mathrm{μs}\left({\color{gray}2.76 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 1526	$$24.4 \mathrm{ms} \pm 139 \mathrm{μs}\left({\color{gray}1.96 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 2078	$$43.3 \mathrm{ms} \pm 189 \mathrm{μs}\left({\color{gray}2.55 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$20.7 \mathrm{ms} \pm 113 \mathrm{μs}\left({\color{red}5.37 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 1033	$$28.7 \mathrm{ms} \pm 132 \mathrm{μs}\left({\color{red}5.66 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_medium

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 102	$$3.67 \mathrm{ms} \pm 23.2 \mathrm{μs}\left({\color{gray}0.751 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.83 \mathrm{ms} \pm 12.7 \mathrm{μs}\left({\color{gray}-1.027 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 51	$$3.19 \mathrm{ms} \pm 18.3 \mathrm{μs}\left({\color{gray}0.675 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 269	$$4.97 \mathrm{ms} \pm 21.3 \mathrm{μs}\left({\color{gray}-0.826 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$3.39 \mathrm{ms} \pm 16.6 \mathrm{μs}\left({\color{gray}0.652 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 107	$$3.91 \mathrm{ms} \pm 17.3 \mathrm{μs}\left({\color{gray}-0.812 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 133	$$4.27 \mathrm{ms} \pm 22.0 \mathrm{μs}\left({\color{gray}0.159 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.26 \mathrm{ms} \pm 13.4 \mathrm{μs}\left({\color{gray}-0.120 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 63	$$3.87 \mathrm{ms} \pm 19.3 \mathrm{μs}\left({\color{gray}-1.034 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_none

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 2	$$2.39 \mathrm{ms} \pm 9.48 \mathrm{μs}\left({\color{gray}-0.080 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.40 \mathrm{ms} \pm 14.4 \mathrm{μs}\left({\color{gray}3.69 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 1	$$2.42 \mathrm{ms} \pm 9.26 \mathrm{μs}\left({\color{gray}0.262 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 8	$$2.62 \mathrm{ms} \pm 12.4 \mathrm{μs}\left({\color{gray}0.040 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$2.54 \mathrm{ms} \pm 15.0 \mathrm{μs}\left({\color{gray}0.568 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 3	$$2.71 \mathrm{ms} \pm 14.1 \mathrm{μs}\left({\color{gray}-0.457 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_small

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 52	$$2.81 \mathrm{ms} \pm 15.2 \mathrm{μs}\left({\color{gray}2.19 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.42 \mathrm{ms} \pm 8.73 \mathrm{μs}\left({\color{gray}-0.368 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 25	$$2.65 \mathrm{ms} \pm 12.9 \mathrm{μs}\left({\color{gray}3.24 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 94	$$3.13 \mathrm{ms} \pm 14.0 \mathrm{μs}\left({\color{gray}-0.571 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$2.67 \mathrm{ms} \pm 13.3 \mathrm{μs}\left({\color{gray}1.01 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 26	$$2.96 \mathrm{ms} \pm 16.8 \mathrm{μs}\left({\color{gray}1.67 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 66	$$3.05 \mathrm{ms} \pm 15.8 \mathrm{μs}\left({\color{gray}1.59 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$2.64 \mathrm{ms} \pm 10.0 \mathrm{μs}\left({\color{gray}0.828 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 29	$$2.89 \mathrm{ms} \pm 15.3 \mathrm{μs}\left({\color{gray}1.50 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_complete

Function	Value	Mean	Flame graphs
entity_by_id;one_depth	1 entities	$$38.7 \mathrm{ms} \pm 160 \mathrm{μs}\left({\color{gray}-1.679 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	10 entities	$$77.0 \mathrm{ms} \pm 435 \mathrm{μs}\left({\color{red}31.7 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	25 entities	$$44.0 \mathrm{ms} \pm 155 \mathrm{μs}\left({\color{gray}-1.373 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	5 entities	$$45.6 \mathrm{ms} \pm 153 \mathrm{μs}\left({\color{gray}-0.958 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	50 entities	$$53.3 \mathrm{ms} \pm 277 \mathrm{μs}\left({\color{gray}-1.971 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	1 entities	$$41.1 \mathrm{ms} \pm 192 \mathrm{μs}\left({\color{gray}-0.197 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	10 entities	$$412 \mathrm{ms} \pm 1.66 \mathrm{ms}\left({\color{red}67.6 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	25 entities	$$94.1 \mathrm{ms} \pm 430 \mathrm{μs}\left({\color{gray}-2.240 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	5 entities	$$84.6 \mathrm{ms} \pm 321 \mathrm{μs}\left({\color{gray}-2.125 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	50 entities	$$280 \mathrm{ms} \pm 763 \mathrm{μs}\left({\color{gray}-2.337 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	1 entities	$$14.8 \mathrm{ms} \pm 70.4 \mathrm{μs}\left({\color{gray}-0.895 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	10 entities	$$14.8 \mathrm{ms} \pm 71.1 \mathrm{μs}\left({\color{gray}-0.452 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	25 entities	$$15.1 \mathrm{ms} \pm 91.2 \mathrm{μs}\left({\color{gray}0.394 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	5 entities	$$14.4 \mathrm{ms} \pm 65.3 \mathrm{μs}\left({\color{gray}-2.506 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	50 entities	$$17.7 \mathrm{ms} \pm 100.0 \mathrm{μs}\left({\color{gray}0.241 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_linkless

Function	Value	Mean	Flame graphs
entity_by_id	1 entities	$$14.3 \mathrm{ms} \pm 64.0 \mathrm{μs}\left({\color{gray}-3.454 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10 entities	$$14.5 \mathrm{ms} \pm 73.5 \mathrm{μs}\left({\color{gray}-2.829 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	100 entities	$$14.3 \mathrm{ms} \pm 65.5 \mathrm{μs}\left({\color{gray}-4.432 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	1000 entities	$$15.1 \mathrm{ms} \pm 77.1 \mathrm{μs}\left({\color{gray}0.496 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10000 entities	$$21.8 \mathrm{ms} \pm 141 \mathrm{μs}\left({\color{gray}-1.349 \mathrm{\%}}\right) $$	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`	$$29.3 \mathrm{ms} \pm 290 \mathrm{μs}\left({\color{gray}-1.158 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/book/v/1`	$$29.6 \mathrm{ms} \pm 222 \mathrm{μs}\left({\color{gray}1.82 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/building/v/1`	$$28.7 \mathrm{ms} \pm 235 \mathrm{μs}\left({\color{gray}-2.381 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/organization/v/1`	$$28.3 \mathrm{ms} \pm 254 \mathrm{μs}\left({\color{gray}-3.497 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/page/v/2`	$$29.7 \mathrm{ms} \pm 308 \mathrm{μs}\left({\color{gray}1.93 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/person/v/1`	$$29.7 \mathrm{ms} \pm 299 \mathrm{μs}\left({\color{gray}2.17 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/playlist/v/1`	$$29.1 \mathrm{ms} \pm 294 \mathrm{μs}\left({\color{gray}0.492 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/song/v/1`	$$29.6 \mathrm{ms} \pm 285 \mathrm{μs}\left({\color{gray}4.46 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/uk-address/v/1`	$$30.0 \mathrm{ms} \pm 289 \mathrm{μs}\left({\color{gray}2.15 \mathrm{\%}}\right) $$	Flame Graph

representative_read_entity_type

Function	Value	Mean	Flame graphs
get_entity_type_by_id	Account ID: `bf5a9ef5-dc3b-43cf-a291-6210c0321eba`	$$8.02 \mathrm{ms} \pm 40.2 \mathrm{μs}\left({\color{gray}0.891 \mathrm{\%}}\right) $$	Flame Graph

representative_read_multiple_entities

Function	Value	Mean	Flame graphs
entity_by_property	traversal_paths=0	0	$$45.8 \mathrm{ms} \pm 203 \mathrm{μs}\left({\color{gray}1.32 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$91.8 \mathrm{ms} \pm 452 \mathrm{μs}\left({\color{gray}-0.313 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$50.6 \mathrm{ms} \pm 322 \mathrm{μs}\left({\color{gray}-1.813 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$58.4 \mathrm{ms} \pm 362 \mathrm{μs}\left({\color{gray}-0.404 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$66.8 \mathrm{ms} \pm 384 \mathrm{μs}\left({\color{gray}-0.846 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$72.9 \mathrm{ms} \pm 442 \mathrm{μs}\left({\color{gray}-1.441 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=0	0	$$48.5 \mathrm{ms} \pm 402 \mathrm{μs}\left({\color{gray}1.01 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$75.7 \mathrm{ms} \pm 479 \mathrm{μs}\left({\color{gray}1.45 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$55.7 \mathrm{ms} \pm 434 \mathrm{μs}\left({\color{gray}1.75 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$63.0 \mathrm{ms} \pm 428 \mathrm{μs}\left({\color{gray}0.857 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$65.0 \mathrm{ms} \pm 337 \mathrm{μs}\left({\color{gray}-0.065 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$65.8 \mathrm{ms} \pm 443 \mathrm{μs}\left({\color{gray}1.56 \mathrm{\%}}\right) $$

scenarios

Function	Value	Mean	Flame graphs
full_test	query-limited	$$124 \mathrm{ms} \pm 539 \mathrm{μs}\left({\color{lightgreen}-10.841 \mathrm{\%}}\right) $$	Flame Graph
full_test	query-unlimited	$$128 \mathrm{ms} \pm 555 \mathrm{μs}\left({\color{lightgreen}-6.845 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-limited	$$102 \mathrm{ms} \pm 578 \mathrm{μs}\left({\color{gray}-1.152 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-unlimited	$$596 \mathrm{ms} \pm 3.46 \mathrm{ms}\left({\color{gray}2.81 \mathrm{\%}}\right) $$	Flame Graph

indietyp added 10 commits February 2, 2026 18:53

chore: checkpoint – massive headache

98bcee1

chore: checkpoint

4c84016

chore: checkpoint

03a23d9

chore: checkpoint

39e8aa8

feat: checkpoint

179a409

feat: use array instead

c6ce48e

chore: lints

66a1d18

feat: checkpoint

ac28cfd

feat: checkpoint

f2638fe

chore: docs

3655222

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graphite-app bot assigned indietyp Feb 3, 2026

github-actions bot added area/libs Relates to first-party libraries/crates/packages (area) type/eng > backend Owned by the @backend team area/tests New or updated tests labels Feb 3, 2026

indietyp mentioned this pull request Feb 3, 2026

BE-360: HashQL: Rework compiletest UI #8340

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BE-303: HashQL: Split MIR basic blocks by target support #8354

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BE-303: HashQL: Split MIR basic blocks by target support #8354

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indietyp commented Feb 3, 2026

🌟 What is the purpose of this PR?

🔍 What does this change?

Pre-Merge Checklist 🚀

🚢 Has this modified a publishable library?

📜 Does this require a change to the docs?

🕸️ Does this require a change to the Turbo Graph?

🛡 What tests cover this?

❓ How to test this?

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indietyp commented Feb 3, 2026

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CodSpeed Performance Report

Merging this PR will not alter performance

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TargetId::all() returns targets in wrong index order

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github-actions bot commented Feb 3, 2026

Benchmark results

@rust/hash-graph-benches – Integrations

policy_resolution_large

policy_resolution_medium

policy_resolution_none

policy_resolution_small

read_scaling_complete

read_scaling_linkless

representative_read_entity

representative_read_entity_type

representative_read_multiple_entities

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