BE-429: HashQL: Add island dependency graph with data requirement resolution by indietyp · Pull Request #8501 · hashintel/hash

indietyp · 2026-03-03T20:46:32Z

🌟 What is the purpose of this PR?

This PR implements the island dependency graph construction and scheduling system for the HashQL MIR execution engine. It builds a directed graph over computation islands, resolves data requirements between islands, and computes a topological schedule with parallelism levels for execution.

🔗 Related links

Related to the island placement and execution planning work

🔍 What does this change?

Adds first_set() method to FiniteBitSet - Returns the first set bit using trailing_zeros(), with comprehensive test coverage for empty sets, single bits, multiple bits, and wide integral types
Enhances IdVec with new utility methods - Adds from_raw(), from_domain_derive(), extend_from_slice(), append(), into_iter_enumerated(), and copy_within() methods with detailed documentation and examples
Implements island dependency graph (IslandGraph) - Creates a directed graph over IslandNodes connected by three edge types: ControlFlow (execution ordering), DataFlow (data dependencies), and Inherits (path inheritance between same-target dominators)
Adds data requirement resolution - Automatically inserts synthetic data islands when traversal paths cannot be satisfied by upstream providers, using dominator analysis to find optimal providers
Implements island scheduling (IslandSchedule) - Computes topological ordering with parallelism levels using Kahn's algorithm, allowing islands at the same level to execute concurrently
Adds comprehensive test suites - Tests cover single islands, data edges between predecessors, fetch island insertion, diamond CFG patterns, inheritance edges, data island reuse, and scheduling correctness
Enables option_into_flat_iter feature - Adds the unstable feature flag for iterator functionality

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?

Unit tests for FiniteBitSet::first_set() covering empty sets, single/multiple bits, edge cases
Integration tests for island graph construction with various CFG patterns
Tests for data requirement resolution including fetch island insertion and reuse
Schedule computation tests verifying topological ordering and parallelism levels
Tests for edge deduplication and dominator-based inheritance

❓ How to test this?

Run the test suite with cargo test
Check that island graph construction correctly identifies dependencies
Verify that data islands are inserted when traversal paths cannot be satisfied
Confirm that scheduling produces valid topological ordering with correct parallelism levels

vercel · 2026-03-03T20:46:37Z

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cursor · 2026-03-03T20:46:39Z

PR Summary

Medium Risk
Adds new execution-planning logic (dependency graph construction, dominator-based data resolution, and parallelism scheduling) that will affect how MIR islands are ordered and may introduce subtle ordering/dependency bugs despite strong unit test coverage.

Overview
Adds an island dependency graph for MIR execution planning: islands become nodes with ControlFlow, DataFlow, and Inherits edges, and requirements are resolved via dominator analysis with automatic insertion/reuse of synthetic data islands when no upstream provider exists.

Introduces scheduling on top of the graph via a topological pass that assigns parallelism levels (independent islands share a level) and re-exports the new graph/schedule types from pass::execution.

Extends core utilities to support this work: FiniteBitSet::first_set() (plus tests) for picking preferred targets, and IdVec gains allocator-friendly helpers including copy_within() and into_iter_enumerated(); traversal bitsets gain contains() helpers and more documentation, with new tests covering graph resolution and scheduling behavior.

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indietyp · 2026-03-03T20:46:51Z

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augmentcode · 2026-03-03T20:50:58Z

🤖 Augment PR Summary

Summary: Adds an island dependency graph and scheduler to the HashQL MIR execution engine, including automatic data requirement resolution across targets.

Changes:

Introduces IslandGraph to model ControlFlow, DataFlow, and Inherits dependencies between computation islands
Resolves traversal-path data requirements via dominator analysis and inserts synthetic data islands when no upstream provider exists
Adds IslandSchedule to compute a levelized topological schedule (parallelism levels) using Kahn’s algorithm
Extends core utilities: FiniteBitSet::first_set() and several IdVec helpers (construction, append/extend, enumerated iteration, copy-within)
Adds comprehensive test coverage for bitset behavior, island graph construction/resolution scenarios, and schedule level ordering

Technical Notes: Data island selection uses the first set origin target (backend-priority order), and schedule levels are derived from predecessor constraints to enable safe parallel execution.

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Review completed. 3 suggestions posted.

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

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

libs/@local/hashql/mir/src/pass/execution/island/schedule/mod.rs

libs/@local/hashql/mir/src/pass/execution/island/graph/mod.rs

cursor

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

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libs/@local/hashql/mir/src/pass/execution/island/graph/mod.rs

codspeed-hq · 2026-03-03T20:51:34Z

Merging this PR will not alter performance

✅ 80 untouched benchmarks

_{Comparing bm/be-429-hashql-per-island-entitypath-requirements-and-fetchisland (572197c) with bm/be-428-hashql-simplify-traversal-tracking-to-path-recording (e6439e0)}

codecov · 2026-03-03T21:26:07Z

Codecov Report

❌ Patch coverage is 95.29086% with 34 lines in your changes missing coverage. Please review.
✅ Project coverage is 62.94%. Comparing base (e6439e0) to head (572197c).

Files with missing lines	Patch %	Lines
.../hashql/mir/src/pass/execution/island/graph/mod.rs	91.60%	19 Missing and 2 partials ⚠️
...ashql/mir/src/pass/execution/island/graph/tests.rs	97.50%	6 Missing and 1 partial ⚠️
...shql/mir/src/pass/execution/island/schedule/mod.rs	88.46%	6 Missing ⚠️

Additional details and impacted files

@@                                        Coverage Diff                                         @@
##           bm/be-428-hashql-simplify-traversal-tracking-to-path-recording    #8501      +/-   ##
==================================================================================================
+ Coverage                                                           62.76%   62.94%   +0.18%     
==================================================================================================
  Files                                                                1316     1320       +4     
  Lines                                                              134383   135105     +722     
  Branches                                                             5499     5517      +18     
==================================================================================================
+ Hits                                                                84343    85041     +698     
- Misses                                                              49129    49150      +21     
- Partials                                                              911      914       +3

Flag	Coverage Δ
apps.hash-ai-worker-ts	`1.40% <ø> (ø)`
apps.hash-api	`0.00% <ø> (ø)`
local.hash-graph-sdk	`7.73% <ø> (ø)`
local.hash-isomorphic-utils	`0.00% <ø> (ø)`
rust.hash-graph-api	`2.64% <ø> (ø)`
rust.hashql-ast	`87.23% <ø> (ø)`
rust.hashql-compiletest	`29.69% <ø> (ø)`
rust.hashql-core	`82.38% <100.00%> (+0.02%)`	⬆️
rust.hashql-eval	`69.13% <ø> (ø)`
rust.hashql-hir	`89.06% <ø> (ø)`
rust.hashql-mir	`92.45% <95.02%> (+0.11%)`	⬆️
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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github-actions · 2026-03-03T22:02:09Z

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	$$28.0 \mathrm{ms} \pm 186 \mathrm{μs}\left({\color{gray}-0.930 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$3.57 \mathrm{ms} \pm 19.2 \mathrm{μs}\left({\color{gray}0.368 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 1001	$$12.6 \mathrm{ms} \pm 105 \mathrm{μs}\left({\color{gray}-0.168 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 3314	$$44.3 \mathrm{ms} \pm 360 \mathrm{μs}\left({\color{gray}-0.454 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$15.1 \mathrm{ms} \pm 152 \mathrm{μs}\left({\color{gray}0.662 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 1526	$$24.6 \mathrm{ms} \pm 200 \mathrm{μs}\left({\color{gray}-3.739 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 2078	$$28.7 \mathrm{ms} \pm 166 \mathrm{μs}\left({\color{gray}-1.639 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.86 \mathrm{ms} \pm 17.0 \mathrm{μs}\left({\color{gray}-0.166 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 1033	$$13.5 \mathrm{ms} \pm 88.1 \mathrm{μs}\left({\color{gray}-1.454 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_medium

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 102	$$3.96 \mathrm{ms} \pm 24.6 \mathrm{μs}\left({\color{gray}-1.148 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$3.14 \mathrm{ms} \pm 14.5 \mathrm{μs}\left({\color{gray}-0.778 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 51	$$3.49 \mathrm{ms} \pm 17.4 \mathrm{μs}\left({\color{gray}-1.361 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 269	$$5.41 \mathrm{ms} \pm 29.3 \mathrm{μs}\left({\color{gray}-0.501 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$3.81 \mathrm{ms} \pm 20.7 \mathrm{μs}\left({\color{gray}2.37 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 107	$$4.45 \mathrm{ms} \pm 24.4 \mathrm{μs}\left({\color{gray}2.56 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 133	$$4.61 \mathrm{ms} \pm 25.4 \mathrm{μs}\left({\color{gray}-1.729 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.62 \mathrm{ms} \pm 23.5 \mathrm{μs}\left({\color{gray}-0.264 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 63	$$4.24 \mathrm{ms} \pm 21.7 \mathrm{μs}\left({\color{gray}-1.297 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_none

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 2	$$2.89 \mathrm{ms} \pm 15.0 \mathrm{μs}\left({\color{gray}0.589 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.84 \mathrm{ms} \pm 16.1 \mathrm{μs}\left({\color{gray}0.440 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 1	$$2.95 \mathrm{ms} \pm 11.7 \mathrm{μs}\left({\color{gray}-0.320 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 8	$$3.21 \mathrm{ms} \pm 17.4 \mathrm{μs}\left({\color{gray}-0.191 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.03 \mathrm{ms} \pm 13.7 \mathrm{μs}\left({\color{gray}-0.789 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 3	$$3.33 \mathrm{ms} \pm 16.4 \mathrm{μs}\left({\color{gray}-0.311 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_small

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 52	$$3.22 \mathrm{ms} \pm 15.2 \mathrm{μs}\left({\color{gray}-1.351 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.96 \mathrm{ms} \pm 13.6 \mathrm{μs}\left({\color{gray}-1.611 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 25	$$3.10 \mathrm{ms} \pm 13.2 \mathrm{μs}\left({\color{gray}-1.277 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 94	$$3.70 \mathrm{ms} \pm 18.7 \mathrm{μs}\left({\color{gray}0.036 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$3.24 \mathrm{ms} \pm 18.0 \mathrm{μs}\left({\color{gray}-1.522 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 26	$$3.48 \mathrm{ms} \pm 23.3 \mathrm{μs}\left({\color{gray}-0.596 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 66	$$3.60 \mathrm{ms} \pm 24.9 \mathrm{μs}\left({\color{gray}-0.950 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.20 \mathrm{ms} \pm 13.6 \mathrm{μs}\left({\color{gray}-3.209 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 29	$$3.49 \mathrm{ms} \pm 15.9 \mathrm{μs}\left({\color{gray}-1.113 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_complete

Function	Value	Mean	Flame graphs
entity_by_id;one_depth	1 entities	$$43.9 \mathrm{ms} \pm 212 \mathrm{μs}\left({\color{gray}2.13 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	10 entities	$$79.8 \mathrm{ms} \pm 436 \mathrm{μs}\left({\color{lightgreen}-6.870 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	25 entities	$$46.9 \mathrm{ms} \pm 189 \mathrm{μs}\left({\color{gray}-2.645 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	5 entities	$$49.9 \mathrm{ms} \pm 326 \mathrm{μs}\left({\color{gray}0.891 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	50 entities	$$58.5 \mathrm{ms} \pm 343 \mathrm{μs}\left({\color{gray}-0.299 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	1 entities	$$46.1 \mathrm{ms} \pm 209 \mathrm{μs}\left({\color{gray}3.10 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	10 entities	$$420 \mathrm{ms} \pm 1.07 \mathrm{ms}\left({\color{gray}0.828 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	25 entities	$$100 \mathrm{ms} \pm 468 \mathrm{μs}\left({\color{gray}0.462 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	5 entities	$$92.1 \mathrm{ms} \pm 406 \mathrm{μs}\left({\color{gray}3.57 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	50 entities	$$297 \mathrm{ms} \pm 809 \mathrm{μs}\left({\color{gray}2.16 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	1 entities	$$16.9 \mathrm{ms} \pm 117 \mathrm{μs}\left({\color{red}5.83 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	10 entities	$$16.3 \mathrm{ms} \pm 80.0 \mathrm{μs}\left({\color{gray}0.142 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	25 entities	$$16.7 \mathrm{ms} \pm 80.2 \mathrm{μs}\left({\color{gray}1.95 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	5 entities	$$16.6 \mathrm{ms} \pm 86.5 \mathrm{μs}\left({\color{gray}1.72 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	50 entities	$$19.4 \mathrm{ms} \pm 118 \mathrm{μs}\left({\color{gray}0.516 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_linkless

Function	Value	Mean	Flame graphs
entity_by_id	1 entities	$$15.8 \mathrm{ms} \pm 69.9 \mathrm{μs}\left({\color{gray}-1.614 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10 entities	$$16.1 \mathrm{ms} \pm 78.4 \mathrm{μs}\left({\color{gray}0.723 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	100 entities	$$16.1 \mathrm{ms} \pm 95.2 \mathrm{μs}\left({\color{gray}1.17 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	1000 entities	$$16.8 \mathrm{ms} \pm 102 \mathrm{μs}\left({\color{gray}1.66 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10000 entities	$$23.9 \mathrm{ms} \pm 150 \mathrm{μs}\left({\color{gray}-0.307 \mathrm{\%}}\right) $$	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`	$$31.8 \mathrm{ms} \pm 252 \mathrm{μs}\left({\color{gray}2.41 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/book/v/1`	$$32.5 \mathrm{ms} \pm 328 \mathrm{μs}\left({\color{gray}2.01 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/building/v/1`	$$32.0 \mathrm{ms} \pm 331 \mathrm{μs}\left({\color{gray}0.301 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/organization/v/1`	$$32.6 \mathrm{ms} \pm 304 \mathrm{μs}\left({\color{gray}4.00 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/page/v/2`	$$31.2 \mathrm{ms} \pm 314 \mathrm{μs}\left({\color{gray}-0.883 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/person/v/1`	$$32.5 \mathrm{ms} \pm 344 \mathrm{μs}\left({\color{gray}1.87 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/playlist/v/1`	$$30.9 \mathrm{ms} \pm 299 \mathrm{μs}\left({\color{gray}-0.340 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/song/v/1`	$$31.2 \mathrm{ms} \pm 313 \mathrm{μs}\left({\color{gray}2.09 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/uk-address/v/1`	$$32.1 \mathrm{ms} \pm 313 \mathrm{μs}\left({\color{gray}3.18 \mathrm{\%}}\right) $$	Flame Graph

representative_read_entity_type

Function	Value	Mean	Flame graphs
get_entity_type_by_id	Account ID: `bf5a9ef5-dc3b-43cf-a291-6210c0321eba`	$$8.95 \mathrm{ms} \pm 42.2 \mathrm{μs}\left({\color{gray}1.15 \mathrm{\%}}\right) $$	Flame Graph

representative_read_multiple_entities

Function	Value	Mean	Flame graphs
entity_by_property	traversal_paths=0	0	$$91.6 \mathrm{ms} \pm 492 \mathrm{μs}\left({\color{gray}1.70 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$145 \mathrm{ms} \pm 577 \mathrm{μs}\left({\color{gray}-0.274 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$98.4 \mathrm{ms} \pm 544 \mathrm{μs}\left({\color{gray}1.00 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$107 \mathrm{ms} \pm 490 \mathrm{μs}\left({\color{gray}0.852 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$116 \mathrm{ms} \pm 511 \mathrm{μs}\left({\color{gray}0.297 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$124 \mathrm{ms} \pm 590 \mathrm{μs}\left({\color{gray}0.642 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=0	0	$$87.8 \mathrm{ms} \pm 395 \mathrm{μs}\left({\color{gray}-1.608 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$117 \mathrm{ms} \pm 491 \mathrm{μs}\left({\color{gray}-0.258 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$95.8 \mathrm{ms} \pm 551 \mathrm{μs}\left({\color{gray}-0.374 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$104 \mathrm{ms} \pm 490 \mathrm{μs}\left({\color{gray}-0.888 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$108 \mathrm{ms} \pm 562 \mathrm{μs}\left({\color{gray}0.058 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$106 \mathrm{ms} \pm 483 \mathrm{μs}\left({\color{gray}-0.833 \mathrm{\%}}\right) $$

scenarios

Function	Value	Mean	Flame graphs
full_test	query-limited	$$134 \mathrm{ms} \pm 540 \mathrm{μs}\left({\color{gray}-2.870 \mathrm{\%}}\right) $$	Flame Graph
full_test	query-unlimited	$$133 \mathrm{ms} \pm 532 \mathrm{μs}\left({\color{gray}-2.434 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-limited	$$79.9 \mathrm{ms} \pm 3.29 \mathrm{ms}\left({\color{red}21.5 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-unlimited	$$578 \mathrm{ms} \pm 872 \mathrm{μs}\left({\color{gray}1.13 \mathrm{\%}}\right) $$	Flame Graph

libs/@local/hashql/mir/src/pass/execution/island/graph/tests.rs

indietyp added 7 commits March 3, 2026 19:09

feat: core logic

a6cc82c

feat: checkpoint

92a81ac

feat: checkpoint

0b4c867

feat: checkpoint

c3009a3

feat: checkpoint

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feat: checkpoint

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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 Mar 3, 2026

graphite-app bot assigned indietyp Mar 3, 2026

This was referenced Mar 3, 2026

BE-427: Add hashql-macros crate with procedural macros for ID types and symbols #8495

Merged

BE-434: HashQL: Refactor entity storage path resolution with centralized schema mapping #8496

Merged

indietyp mentioned this pull request Mar 3, 2026

BE-428: HashQL: Simplify traversal tracking to path recording #8498

Open

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vercel bot deployed to Preview – petrinaut March 3, 2026 20:49 View deployment

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This was referenced Mar 8, 2026

BE-456: HashQL: Entity type model enrichment and graph store query extensions #8524

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BE-457: HashQL: MIR execution pipeline extensions for postgres compilation #8525

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BE-306: HashQL: PostgreSQL translation #8526

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fix: suggestions from code review

e5a7c7e

vercel bot temporarily deployed to Preview – petrinaut March 8, 2026 16:15 Inactive

fix: lint

572197c

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libs/@local/hashql/mir/src/pass/execution/island/graph/tests.rs Fixed Show fixed Hide fixed

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indietyp force-pushed the bm/be-429-hashql-per-island-entitypath-requirements-and-fetchisland branch from 922e42b to 572197c Compare March 8, 2026 17:03

indietyp force-pushed the bm/be-428-hashql-simplify-traversal-tracking-to-path-recording branch from 7014842 to e6439e0 Compare March 8, 2026 17:03

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TimDiekmann approved these changes Mar 12, 2026

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indietyp commented Mar 3, 2026

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