BE-524: HashQL: Remove island schedule module by indietyp · Pull Request #8694 · hashintel/hash

indietyp · 2026-05-04T10:40:00Z

🌟 What is the purpose of this PR?

The island::schedule module, which provided topological scheduling with parallelism level assignment for execution islands, has been removed. This includes the IslandSchedule and ScheduledIsland types, the schedule and schedule_in methods on IslandGraph, and all associated tests. The scheduling functionality is no longer needed or has been superseded by an alternative approach.

🔍 What does this change?

Removes the schedule submodule from island/mod.rs
Deletes island/schedule/mod.rs, which contained the IslandSchedule and ScheduledIsland types along with the Kahn's algorithm-based topological level assignment implementation
Deletes island/schedule/tests.rs, which contained tests for level ordering, contiguity, and full node coverage of the schedule
Removes the public re-exports of IslandSchedule and ScheduledIsland from pass/execution/mod.rs

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?

The tests that previously covered the scheduling logic have been removed alongside the implementation.

❓ How to test this?

Checkout the branch
Run cargo test in libs/@local/hashql/mir
Confirm that the build succeeds and no references to IslandSchedule or ScheduledIsland remain

vercel · 2026-05-04T10:40:04Z

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cursor · 2026-05-04T10:40:07Z

PR Summary

Medium Risk
Removes the island::schedule implementation and its public exports, which can break downstream callers and reduces test coverage for island ordering behavior.

Overview
This PR deletes the island::schedule module, including the IslandGraph::schedule/schedule_in APIs and the IslandSchedule/ScheduledIsland types used to compute a topological, parallelism-level schedule of execution islands.

It also removes all schedule-related tests and stops re-exporting these types from pass::execution, leaving only the island graph construction/analysis surfaces.

^{Reviewed by Cursor Bugbot for commit 94254d8. Bugbot is set up for automated code reviews on this repo. Configure here.}

indietyp · 2026-05-04T10:40:40Z

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augmentcode · 2026-05-04T10:41:19Z

🤖 Augment PR Summary

Summary: Removes the deprecated/unused HashQL MIR island scheduling implementation and its public surface area.

Changes:

Drops the pass::execution::island::schedule submodule from island/mod.rs
Deletes the scheduling implementation (IslandGraph::schedule/schedule_in) and the related types (IslandSchedule, ScheduledIsland)
Removes the schedule unit tests that validated ordering/level semantics
Removes the re-exports of IslandSchedule/ScheduledIsland from pass::execution

Technical Notes: This PR is primarily an API/code deletion; downstream code must no longer rely on the removed scheduling helpers and should use the newer/superseding execution approach instead.

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codspeed-hq · 2026-05-04T10:46:00Z

Merging this PR will not alter performance

✅ 24 untouched benchmarks
⏩ 56 skipped benchmarks¹

_{Comparing bm/be-524-hashql-remove-island-dag (94254d8) with bm/be-525-hashql-remove-implicit-type-widening-into-num-for-int (80c753b)}

56 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. ↩

codecov · 2026-05-04T11:46:22Z

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 21.16%. Comparing base (80c753b) to head (94254d8).

Additional details and impacted files

@@                                       Coverage Diff                                        @@
##           bm/be-525-hashql-remove-implicit-type-widening-into-num-for-int    #8694   +/-   ##
================================================================================================
  Coverage                                                            21.16%   21.16%           
================================================================================================
  Files                                                                  544      544           
  Lines                                                                26213    26213           
  Branches                                                              2994     2994           
================================================================================================
  Hits                                                                  5548     5548           
  Misses                                                               20589    20589           
  Partials                                                                76       76

Flag	Coverage Δ
apps.hash-ai-worker-ts	`1.41% <ø> (ø)`
apps.hash-api	`0.00% <ø> (ø)`
local.hash-backend-utils	`2.81% <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> (ø)`

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github-actions · 2026-05-04T13:03:32Z

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	$$27.5 \mathrm{ms} \pm 178 \mathrm{μs}\left({\color{gray}-1.622 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$3.41 \mathrm{ms} \pm 15.3 \mathrm{μs}\left({\color{gray}-1.973 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 1001	$$12.4 \mathrm{ms} \pm 93.3 \mathrm{μs}\left({\color{gray}-0.017 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 3314	$$43.9 \mathrm{ms} \pm 317 \mathrm{μs}\left({\color{gray}1.97 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$14.1 \mathrm{ms} \pm 98.8 \mathrm{μs}\left({\color{gray}-1.014 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 1526	$$24.0 \mathrm{ms} \pm 195 \mathrm{μs}\left({\color{gray}0.639 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 2078	$$28.4 \mathrm{ms} \pm 170 \mathrm{μs}\left({\color{gray}0.047 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.73 \mathrm{ms} \pm 19.7 \mathrm{μs}\left({\color{gray}-1.456 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 1033	$$13.5 \mathrm{ms} \pm 105 \mathrm{μs}\left({\color{gray}-0.773 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_medium

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 102	$$3.76 \mathrm{ms} \pm 25.6 \mathrm{μs}\left({\color{gray}-1.137 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.96 \mathrm{ms} \pm 16.5 \mathrm{μs}\left({\color{gray}-1.827 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 51	$$3.33 \mathrm{ms} \pm 21.8 \mathrm{μs}\left({\color{gray}-1.075 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 269	$$5.14 \mathrm{ms} \pm 37.9 \mathrm{μs}\left({\color{gray}-2.210 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$3.52 \mathrm{ms} \pm 20.2 \mathrm{μs}\left({\color{gray}-0.719 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 107	$$4.12 \mathrm{ms} \pm 30.7 \mathrm{μs}\left({\color{gray}-0.584 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 133	$$4.45 \mathrm{ms} \pm 29.0 \mathrm{μs}\left({\color{gray}0.159 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.47 \mathrm{ms} \pm 24.8 \mathrm{μs}\left({\color{gray}-0.789 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 63	$$4.13 \mathrm{ms} \pm 29.0 \mathrm{μs}\left({\color{gray}0.907 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_none

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 2	$$2.62 \mathrm{ms} \pm 15.1 \mathrm{μs}\left({\color{gray}-3.025 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.52 \mathrm{ms} \pm 13.0 \mathrm{μs}\left({\color{gray}-0.856 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 1	$$2.59 \mathrm{ms} \pm 15.9 \mathrm{μs}\left({\color{gray}-4.187 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 8	$$2.85 \mathrm{ms} \pm 11.9 \mathrm{μs}\left({\color{gray}-4.344 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$2.66 \mathrm{ms} \pm 15.5 \mathrm{μs}\left({\color{gray}-3.542 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 3	$$2.86 \mathrm{ms} \pm 15.5 \mathrm{μs}\left({\color{gray}-3.826 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_small

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 52	$$3.05 \mathrm{ms} \pm 14.9 \mathrm{μs}\left({\color{gray}0.197 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.76 \mathrm{ms} \pm 12.5 \mathrm{μs}\left({\color{gray}-0.816 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 25	$$3.00 \mathrm{ms} \pm 14.9 \mathrm{μs}\left({\color{gray}-1.312 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 94	$$3.49 \mathrm{ms} \pm 21.7 \mathrm{μs}\left({\color{gray}1.27 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$3.01 \mathrm{ms} \pm 15.6 \mathrm{μs}\left({\color{gray}-1.230 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 26	$$3.34 \mathrm{ms} \pm 16.1 \mathrm{μs}\left({\color{gray}-0.505 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 66	$$3.39 \mathrm{ms} \pm 17.5 \mathrm{μs}\left({\color{gray}0.991 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$2.95 \mathrm{ms} \pm 16.6 \mathrm{μs}\left({\color{gray}-1.428 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 29	$$3.40 \mathrm{ms} \pm 23.2 \mathrm{μs}\left({\color{gray}-0.106 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_complete

Function	Value	Mean	Flame graphs
entity_by_id;one_depth	1 entities	$$54.8 \mathrm{ms} \pm 312 \mathrm{μs}\left({\color{gray}0.040 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	10 entities	$$46.1 \mathrm{ms} \pm 184 \mathrm{μs}\left({\color{gray}-1.727 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	25 entities	$$50.3 \mathrm{ms} \pm 273 \mathrm{μs}\left({\color{gray}-1.316 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	5 entities	$$44.4 \mathrm{ms} \pm 220 \mathrm{μs}\left({\color{gray}-2.045 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	50 entities	$$63.4 \mathrm{ms} \pm 367 \mathrm{μs}\left({\color{gray}-2.580 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	1 entities	$$61.6 \mathrm{ms} \pm 303 \mathrm{μs}\left({\color{gray}-1.864 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	10 entities	$$56.8 \mathrm{ms} \pm 347 \mathrm{μs}\left({\color{gray}-1.303 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	25 entities	$$104 \mathrm{ms} \pm 486 \mathrm{μs}\left({\color{gray}-2.340 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	5 entities	$$46.7 \mathrm{ms} \pm 237 \mathrm{μs}\left({\color{gray}-1.427 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	50 entities	$$325 \mathrm{ms} \pm 803 \mathrm{μs}\left({\color{red}8.23 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	1 entities	$$19.3 \mathrm{ms} \pm 109 \mathrm{μs}\left({\color{gray}-4.018 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	10 entities	$$20.8 \mathrm{ms} \pm 118 \mathrm{μs}\left({\color{gray}1.69 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	25 entities	$$20.6 \mathrm{ms} \pm 121 \mathrm{μs}\left({\color{gray}-0.504 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	5 entities	$$19.6 \mathrm{ms} \pm 105 \mathrm{μs}\left({\color{gray}-3.205 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	50 entities	$$25.5 \mathrm{ms} \pm 109 \mathrm{μs}\left({\color{gray}-3.623 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_linkless

Function	Value	Mean	Flame graphs
entity_by_id	1 entities	$$19.6 \mathrm{ms} \pm 132 \mathrm{μs}\left({\color{gray}-2.719 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10 entities	$$19.6 \mathrm{ms} \pm 121 \mathrm{μs}\left({\color{gray}-3.968 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	100 entities	$$20.1 \mathrm{ms} \pm 99.1 \mathrm{μs}\left({\color{gray}-0.849 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	1000 entities	$$20.3 \mathrm{ms} \pm 110 \mathrm{μs}\left({\color{lightgreen}-5.576 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10000 entities	$$26.9 \mathrm{ms} \pm 197 \mathrm{μs}\left({\color{gray}-3.748 \mathrm{\%}}\right) $$	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`	$$35.8 \mathrm{ms} \pm 312 \mathrm{μs}\left({\color{gray}-4.116 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/book/v/1`	$$36.6 \mathrm{ms} \pm 298 \mathrm{μs}\left({\color{gray}-3.236 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/building/v/1`	$$34.7 \mathrm{ms} \pm 387 \mathrm{μs}\left({\color{lightgreen}-5.088 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/organization/v/1`	$$33.8 \mathrm{ms} \pm 302 \mathrm{μs}\left({\color{lightgreen}-6.939 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/page/v/2`	$$35.7 \mathrm{ms} \pm 312 \mathrm{μs}\left({\color{gray}-4.210 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/person/v/1`	$$35.6 \mathrm{ms} \pm 284 \mathrm{μs}\left({\color{gray}-1.268 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/playlist/v/1`	$$35.8 \mathrm{ms} \pm 268 \mathrm{μs}\left({\color{gray}-1.861 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/song/v/1`	$$35.1 \mathrm{ms} \pm 275 \mathrm{μs}\left({\color{gray}-4.655 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/uk-address/v/1`	$$35.0 \mathrm{ms} \pm 294 \mathrm{μs}\left({\color{gray}0.119 \mathrm{\%}}\right) $$	Flame Graph

representative_read_entity_type

Function	Value	Mean	Flame graphs
get_entity_type_by_id	Account ID: `bf5a9ef5-dc3b-43cf-a291-6210c0321eba`	$$8.66 \mathrm{ms} \pm 51.4 \mathrm{μs}\left({\color{gray}-2.044 \mathrm{\%}}\right) $$	Flame Graph

representative_read_multiple_entities

Function	Value	Mean	Flame graphs
entity_by_property	traversal_paths=0	0	$$92.7 \mathrm{ms} \pm 558 \mathrm{μs}\left({\color{lightgreen}-5.231 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$148 \mathrm{ms} \pm 549 \mathrm{μs}\left({\color{lightgreen}-5.203 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$99.4 \mathrm{ms} \pm 508 \mathrm{μs}\left({\color{lightgreen}-6.176 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$113 \mathrm{ms} \pm 618 \mathrm{μs}\left({\color{gray}-3.971 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$119 \mathrm{ms} \pm 533 \mathrm{μs}\left({\color{gray}-3.197 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$127 \mathrm{ms} \pm 481 \mathrm{μs}\left({\color{gray}-4.758 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=0	0	$$103 \mathrm{ms} \pm 511 \mathrm{μs}\left({\color{gray}-4.341 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$133 \mathrm{ms} \pm 663 \mathrm{μs}\left({\color{gray}-4.253 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$110 \mathrm{ms} \pm 524 \mathrm{μs}\left({\color{lightgreen}-5.021 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$119 \mathrm{ms} \pm 619 \mathrm{μs}\left({\color{gray}-4.629 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$121 \mathrm{ms} \pm 579 \mathrm{μs}\left({\color{gray}-4.861 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$121 \mathrm{ms} \pm 540 \mathrm{μs}\left({\color{gray}-4.833 \mathrm{\%}}\right) $$

scenarios

Function	Value	Mean	Flame graphs
full_test	query-limited	$$183 \mathrm{ms} \pm 830 \mathrm{μs}\left({\color{red}33.9 \mathrm{\%}}\right) $$	Flame Graph
full_test	query-unlimited	$$169 \mathrm{ms} \pm 2.47 \mathrm{ms}\left({\color{red}15.1 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-limited	$$40.7 \mathrm{ms} \pm 234 \mathrm{μs}\left({\color{gray}-2.118 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-unlimited	$$554 \mathrm{ms} \pm 1.33 \mathrm{ms}\left({\color{gray}-2.201 \mathrm{\%}}\right) $$	Flame Graph

feat: remove schedule island

94254d8

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github-actions Bot added area/libs Relates to first-party libraries/crates/packages (area) type/eng > backend Owned by the @backend team labels May 4, 2026

indietyp mentioned this pull request May 4, 2026

BE-525: HashQL: Remove implicit type-widening from Integer operations, and make comparison size aware #8693

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BE-512: HashQL: Allow cross-backend transitions for SwitchInt terminators #8696

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indietyp mentioned this pull request May 4, 2026

BE-513: HashQL: Rework dynamic aggregate size estimation #8697

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indietyp commented May 4, 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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PR Summary

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augmentcode Bot commented May 4, 2026

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Merging this PR will not alter performance

Footnotes

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Codecov Report

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github-actions Bot commented May 4, 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

scenarios

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Reviewers

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1 participant

vercel Bot commented May 4, 2026 •

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indietyp commented May 4, 2026 •

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