BE-515: HashQL: Remove OFFSET 0 materialization fence from generated query

[indietyp]

🌟 What is the purpose of this PR?

HashQL: Remove OFFSET 0 materialization fence from generated SQL

Problem

Each PostgreSQL island is wrapped in a CROSS JOIN LATERAL subquery. The subquery previously included OFFSET 0 as a materialization fence to prevent PostgreSQL's planner from inlining the CASE tree expression and duplicating it across each composite field access in the SELECT list.

The planner's cost estimate favors the fenced plan (lower estimated cost), but empirical benchmarks show the opposite for queries with conditional CASE trees:

Query	Change (fenced → unfenced)
all_entities	−11% (improved)
filter_by_uuid	+10% (regressed)
diamond_cfg	−5% (improved)
sequential_filters	−72% (improved)
stress_test	−77% (improved)

For multi-body queries with conditional branches, the materialization overhead exceeds the duplication cost by 3–4×. The fence helps modestly for simple single-expression queries without branching (filter_by_uuid), but is catastrophic for the common case.

🚢 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?

• Existing test coverage for the HashQL eval Postgres module.

❓ How to test this?

1. Checkout the branch.
2. Run the existing test suite.
3. Confirm all tests pass and query behavior is unchanged.

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[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-513: HashQL: Rework dynamic aggregate size estimation #8697
• BE-512: HashQL: Allow cross-backend transitions for SwitchInt terminators #8696
• BE-524: HashQL: Remove island schedule module #8694
• BE-525: HashQL: Remove implicit type-widening from Integer operations, and make comparison size aware #8693
• BE-515: HashQL: Remove OFFSET 0 materialization fence from generated query #8650 👈 (View in Graphite)
• BE-514: HashQL: implement iterative adjustment passes in placement solver #8635
• BE-500, BE-501: HashQL: Unify mixed parameter resolution in data dependency analysis #8607
• BE-494: HashQL: Loop-breaker selection for recursive inlining #8600
• BE-482: HashQL: Remove logical not from MIR and fix postgres boolean lowering #8595
• BE-474: HashQL: Take into account terminator target eligibility in execution backend placement #8587
• BE-455: HashQL: Introduce evaluation orchestrator #8586
• BE-523: HashQL: Suspendable interpreter with structured values and input system #8675
• BE-522: HashQL: Expand stdlib type system with temporal types #8674
• BE-306: HashQL: PostgreSQL translation #8526
• BE-457: HashQL: MIR execution pipeline extensions for postgres compilation #8525
• BE-456: HashQL: Entity type model enrichment and graph store query extensions #8524
• BE-429: HashQL: Add island dependency graph with data requirement resolution #8501
• BE-428: HashQL: Simplify traversal tracking to path recording #8498
• BE-434: HashQL: Refactor entity storage path resolution with centralized schema mapping #8496
• BE-427: Add hashql-macros crate with procedural macros for ID types and symbols #8495
• main

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

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 53.92%. Comparing base (c95bdd2) to head (58bba8c).

Additional details and impacted files

@@                                            Coverage Diff                                             @@
##           bm/be-514-hashql-solver-iterate-forwardbackward-passes-to-convergence    #8650       +/-   ##
==========================================================================================================
- Coverage                                                                  66.19%   53.92%   -12.28%     
==========================================================================================================
  Files                                                                        934      778      -156     
  Lines                                                                      84690    57232    -27458     
  Branches                                                                    4468     3839      -629     
==========================================================================================================
- Hits                                                                       56063    30863    -25200     
+ Misses                                                                     28071    26041     -2030     
+ Partials                                                                     556      328      -228     

Flag	Coverage Δ
apps.hash-ai-worker-ts	1.41% <ø> (ø)
apps.hash-api	0.00% <ø> (ø)
local.hash-backend-utils	0.00% <ø> (ø)
local.hash-graph-sdk	9.63% <ø> (ø)
local.hash-isomorphic-utils	0.00% <ø> (ø)
rust.hash-graph-api	2.52% <ø> (ø)
rust.hashql-compiletest	28.26% <ø> (ø)
rust.hashql-eval	79.70% <ø> (-0.01%)	⬇️
rust.hashql-mir	?

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[codspeed-hq]

Merging this PR will not alter performance

✅ 80 untouched benchmarks

---

_{Comparing bm/be-515-hashql-remove-offset-0-materialization-fence-from-generated (9db238d) with bm/be-514-hashql-solver-iterate-forwardbackward-passes-to-convergence (dadf2c4)}

[augmentcode]

🤖 Augment PR Summary

Summary: Removes the OFFSET 0 materialization fence from generated Postgres lateral subqueries in HashQL evaluation.
Why: This avoids unnecessary materialization overhead and aligns the generated SQL with benchmark results showing better performance for multi-branch CASE-tree queries.

_{🤖 Was this summary useful? React with 👍 or 👎}

[augmentcode]

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[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 caff769. Configure here.}

[cursor]

Double space in doc comment after editing

Low Severity

After removing "(via OFFSET 0)" from the doc comment, a double space remains between "once per row" and "and returns a" on line 4. Minor formatting artifact from the edit.

 

^{Reviewed by Cursor Bugbot for commit caff769. Configure here.}

[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	$$26.4 \mathrm{ms} \pm 119 \mathrm{μs}\left({\color{gray}2.32 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.84 \mathrm{ms} \pm 14.1 \mathrm{μs}\left({\color{gray}0.338 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 1001	$$11.6 \mathrm{ms} \pm 65.6 \mathrm{μs}\left({\color{gray}1.71 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 3314	$$37.4 \mathrm{ms} \pm 310 \mathrm{μs}\left({\color{gray}-1.409 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$11.4 \mathrm{ms} \pm 92.6 \mathrm{μs}\left({\color{gray}2.28 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 1526	$$20.6 \mathrm{ms} \pm 140 \mathrm{μs}\left({\color{gray}-2.779 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 2078	$$26.7 \mathrm{ms} \pm 202 \mathrm{μs}\left({\color{gray}-0.927 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.11 \mathrm{ms} \pm 14.1 \mathrm{μs}\left({\color{gray}0.042 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 1033	$$12.5 \mathrm{ms} \pm 80.1 \mathrm{μs}\left({\color{gray}1.00 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_medium

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 102	$$3.13 \mathrm{ms} \pm 18.6 \mathrm{μs}\left({\color{gray}-0.256 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.47 \mathrm{ms} \pm 21.2 \mathrm{μs}\left({\color{gray}3.60 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 51	$$2.74 \mathrm{ms} \pm 14.2 \mathrm{μs}\left({\color{gray}0.667 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 269	$$4.45 \mathrm{ms} \pm 19.2 \mathrm{μs}\left({\color{gray}0.975 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$2.89 \mathrm{ms} \pm 11.9 \mathrm{μs}\left({\color{gray}0.448 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 107	$$3.43 \mathrm{ms} \pm 16.9 \mathrm{μs}\left({\color{gray}0.935 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 133	$$3.74 \mathrm{ms} \pm 20.5 \mathrm{μs}\left({\color{gray}0.334 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$2.81 \mathrm{ms} \pm 10.7 \mathrm{μs}\left({\color{gray}-1.841 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 63	$$3.35 \mathrm{ms} \pm 15.0 \mathrm{μs}\left({\color{gray}0.251 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_none

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 2	$$2.13 \mathrm{ms} \pm 11.5 \mathrm{μs}\left({\color{gray}0.766 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.02 \mathrm{ms} \pm 9.69 \mathrm{μs}\left({\color{gray}0.472 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 1	$$2.11 \mathrm{ms} \pm 8.24 \mathrm{μs}\left({\color{gray}-0.122 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 8	$$2.33 \mathrm{ms} \pm 10.1 \mathrm{μs}\left({\color{gray}0.248 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$2.20 \mathrm{ms} \pm 12.3 \mathrm{μs}\left({\color{gray}0.504 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 3	$$2.32 \mathrm{ms} \pm 12.0 \mathrm{μs}\left({\color{gray}0.407 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_small

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 52	$$2.46 \mathrm{ms} \pm 13.5 \mathrm{μs}\left({\color{gray}1.43 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.22 \mathrm{ms} \pm 9.64 \mathrm{μs}\left({\color{gray}0.814 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 25	$$2.40 \mathrm{ms} \pm 10.7 \mathrm{μs}\left({\color{gray}-0.511 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 94	$$2.78 \mathrm{ms} \pm 16.0 \mathrm{μs}\left({\color{gray}0.816 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$2.38 \mathrm{ms} \pm 9.85 \mathrm{μs}\left({\color{gray}0.705 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 26	$$2.64 \mathrm{ms} \pm 13.2 \mathrm{μs}\left({\color{gray}0.980 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 66	$$2.67 \mathrm{ms} \pm 11.9 \mathrm{μs}\left({\color{gray}-0.239 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$2.39 \mathrm{ms} \pm 13.2 \mathrm{μs}\left({\color{gray}1.12 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 29	$$2.67 \mathrm{ms} \pm 12.9 \mathrm{μs}\left({\color{gray}0.709 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_complete

Function	Value	Mean	Flame graphs
entity_by_id;one_depth	1 entities	$$47.7 \mathrm{ms} \pm 178 \mathrm{μs}\left({\color{gray}-0.693 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	10 entities	$$39.6 \mathrm{ms} \pm 153 \mathrm{μs}\left({\color{gray}0.294 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	25 entities	$$42.7 \mathrm{ms} \pm 177 \mathrm{μs}\left({\color{gray}-0.910 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	5 entities	$$37.5 \mathrm{ms} \pm 170 \mathrm{μs}\left({\color{gray}-1.279 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	50 entities	$$54.5 \mathrm{ms} \pm 240 \mathrm{μs}\left({\color{gray}0.825 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	1 entities	$$53.9 \mathrm{ms} \pm 188 \mathrm{μs}\left({\color{gray}-4.059 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	10 entities	$$48.0 \mathrm{ms} \pm 191 \mathrm{μs}\left({\color{gray}1.26 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	25 entities	$$85.1 \mathrm{ms} \pm 322 \mathrm{μs}\left({\color{lightgreen}-7.476 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	5 entities	$$38.8 \mathrm{ms} \pm 149 \mathrm{μs}\left({\color{gray}-1.812 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	50 entities	$$280 \mathrm{ms} \pm 887 \mathrm{μs}\left({\color{gray}-3.002 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	1 entities	$$16.7 \mathrm{ms} \pm 82.5 \mathrm{μs}\left({\color{gray}3.22 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	10 entities	$$17.4 \mathrm{ms} \pm 75.1 \mathrm{μs}\left({\color{gray}0.597 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	25 entities	$$17.6 \mathrm{ms} \pm 102 \mathrm{μs}\left({\color{gray}1.27 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	5 entities	$$16.5 \mathrm{ms} \pm 83.6 \mathrm{μs}\left({\color{gray}-2.517 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	50 entities	$$20.8 \mathrm{ms} \pm 183 \mathrm{μs}\left({\color{gray}2.51 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_linkless

Function	Value	Mean	Flame graphs
entity_by_id	1 entities	$$16.4 \mathrm{ms} \pm 66.1 \mathrm{μs}\left({\color{gray}1.35 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10 entities	$$16.7 \mathrm{ms} \pm 85.8 \mathrm{μs}\left({\color{gray}2.27 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	100 entities	$$16.5 \mathrm{ms} \pm 85.1 \mathrm{μs}\left({\color{gray}-0.156 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	1000 entities	$$17.2 \mathrm{ms} \pm 67.1 \mathrm{μs}\left({\color{gray}-1.500 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10000 entities	$$24.0 \mathrm{ms} \pm 151 \mathrm{μs}\left({\color{gray}1.54 \mathrm{\%}}\right) $$	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	$$31.5 \mathrm{ms} \pm 230 \mathrm{μs}\left({\color{gray}2.07 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/book/v/1	$$31.7 \mathrm{ms} \pm 245 \mathrm{μs}\left({\color{gray}3.72 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/building/v/1	$$29.9 \mathrm{ms} \pm 244 \mathrm{μs}\left({\color{lightgreen}-5.757 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/organization/v/1	$$30.7 \mathrm{ms} \pm 277 \mathrm{μs}\left({\color{gray}-0.301 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/page/v/2	$$30.8 \mathrm{ms} \pm 266 \mathrm{μs}\left({\color{gray}-3.183 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/person/v/1	$$31.0 \mathrm{ms} \pm 286 \mathrm{μs}\left({\color{gray}-2.494 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/playlist/v/1	$$31.6 \mathrm{ms} \pm 327 \mathrm{μs}\left({\color{gray}2.65 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/song/v/1	$$32.0 \mathrm{ms} \pm 328 \mathrm{μs}\left({\color{gray}-2.764 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/uk-address/v/1	$$31.5 \mathrm{ms} \pm 297 \mathrm{μs}\left({\color{gray}-1.020 \mathrm{\%}}\right) $$	Flame Graph

representative_read_entity_type

Function	Value	Mean	Flame graphs
get_entity_type_by_id	Account ID: bf5a9ef5-dc3b-43cf-a291-6210c0321eba	$$6.92 \mathrm{ms} \pm 30.1 \mathrm{μs}\left({\color{gray}-1.928 \mathrm{\%}}\right) $$	Flame Graph

representative_read_multiple_entities

Function	Value	Mean	Flame graphs
entity_by_property	traversal_paths=0	0	$$91.6 \mathrm{ms} \pm 393 \mathrm{μs}\left({\color{gray}-1.702 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$137 \mathrm{ms} \pm 600 \mathrm{μs}\left({\color{gray}0.151 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$98.1 \mathrm{ms} \pm 386 \mathrm{μs}\left({\color{gray}0.639 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$110 \mathrm{ms} \pm 383 \mathrm{μs}\left({\color{gray}3.92 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$113 \mathrm{ms} \pm 498 \mathrm{μs}\left({\color{gray}1.60 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$119 \mathrm{ms} \pm 631 \mathrm{μs}\left({\color{gray}-2.127 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=0	0	$$97.5 \mathrm{ms} \pm 359 \mathrm{μs}\left({\color{gray}-0.790 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$123 \mathrm{ms} \pm 626 \mathrm{μs}\left({\color{gray}-0.543 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$104 \mathrm{ms} \pm 459 \mathrm{μs}\left({\color{gray}-1.952 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$112 \mathrm{ms} \pm 495 \mathrm{μs}\left({\color{gray}-0.463 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$113 \mathrm{ms} \pm 510 \mathrm{μs}\left({\color{gray}-1.020 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$112 \mathrm{ms} \pm 465 \mathrm{μs}\left({\color{gray}-1.924 \mathrm{\%}}\right) $$

scenarios

Function	Value	Mean	Flame graphs
full_test	query-limited	$$161 \mathrm{ms} \pm 702 \mathrm{μs}\left({\color{gray}-2.337 \mathrm{\%}}\right) $$	Flame Graph
full_test	query-unlimited	$$131 \mathrm{ms} \pm 479 \mathrm{μs}\left({\color{gray}-2.120 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-limited	$$35.4 \mathrm{ms} \pm 129 \mathrm{μs}\left({\color{gray}-1.476 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-unlimited	$$493 \mathrm{ms} \pm 819 \mathrm{μs}\left({\color{gray}1.36 \mathrm{\%}}\right) $$	Flame Graph