BE-513: HashQL: Rework dynamic aggregate size estimation by indietyp · Pull Request #8697 · hashintel/hash

indietyp · 2026-05-04T14:23:48Z

🌟 What is the purpose of this PR?

The size estimation analysis previously treated all aggregate kinds (structs, tuples, lists, dicts, closures) identically — summing operand footprints and accumulating cardinality as if every aggregate were a flat collection. This was incorrect: a struct or tuple is a single composite value with cardinality 1, while a list or dict is a true collection whose cardinality equals its element count.

This PR introduces type-aware aggregate footprint evaluation. Structs and tuples now correctly report cardinality 1 with units equal to the sum of their fields' materialized sizes. Lists report per-element units (joined across elements) with cardinality equal to the element count. Dicts compute per-pair units (key + value combined) with cardinality equal to the pair count. Closures combine their function pointer and environment footprints into a single scalar value.

To support this, a materialize() method is introduced on Footprint that collapses a footprint's (units, cardinality) pair into a single total information estimate. This is needed when a value with its own cardinality (e.g. a list) is embedded as a field of a composite type — the field's contribution to the parent's units must account for the full information content of the nested value, not just its per-element size.

🔍 What does this change?

Replaces the single generic RValue::Aggregate handler in eval_rvalue with a dedicated eval_rvalue_aggregate method that dispatches on AggregateKind.
Struct/Tuple: sums the materialize()d footprints of all operands and sets cardinality to 1.
List: joins per-element materialized units and sets cardinality to the literal element count.
Dict: joins per-pair materialized units (key + value combined via saturating_mul_add) and sets cardinality to the pair count.
Closure: combines function pointer and environment footprints into a single scalar (cardinality 1).
Opaque: retains the previous behaviour of summing raw footprints.
Adds Footprint::materialize() which multiplies units by cardinality to produce a total information estimate, with case-specific handling for constant×constant (exact), affine units×constant cardinality (scale coefficients by cardinality upper bound), and affine×affine (element-wise coefficient multiplication as a linear under-approximation).
Adds Footprint::one(units) constructor for footprints with cardinality exactly 1.
Adds Estimate::saturating_coeff_mul for element-wise coefficient multiplication between two estimates.
Adds InformationRange::saturating_mul_cardinality for range-level multiplication of information by cardinality, saturating to unbounded on overflow.
Adds Eval::into_footprint as a consuming counterpart to Eval::as_ref.
Fixes the snapshot for struct_aggregate_sums_operands and tuple_aggregate_sums_operands, which previously reported cardinality 2 for a two-field struct/tuple; both now correctly report cardinality 1.

🛡 What tests cover this?

New integration tests: list_aggregate_per_element_units, dict_aggregate_per_pair_units, tuple_many_fields_cardinality_one, and struct_materializes_list_parameter, each with corresponding snapshot files.
New unit tests in footprint.rs covering all four materialize() branches: scalar identity, constant×constant, affine units×constant cardinality, constant units×affine cardinality, and both-affine same-parameter.
New unit tests in range.rs covering saturating_mul_cardinality: exact multiplication, identity by 1, empty inputs, unbounded cardinality, and overflow to unbounded.

❓ How to test this?

Run cargo test -p hashql-mir and confirm all tests pass.
Review the new and updated snapshots under libs/@local/hashql/mir/tests/ui/pass/size-estimation/ to verify the reported units and cardinality values match the expected semantics for each aggregate kind.

vercel · 2026-05-04T14:23:53Z

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cursor · 2026-05-04T14:23:57Z

PR Summary

Medium Risk
Changes core size-estimation math and aggregate handling, which can alter optimization/planning decisions that depend on these estimates. Added coverage reduces risk, but edge cases around affine materialization and unbounded ranges could shift results.

Overview
Reworks dynamic aggregate footprint evaluation so RValue::Aggregate is dispatched by AggregateKind instead of treating all aggregates as flat collections.

Structs/tuples now sum materialized field sizes with cardinality fixed to 1, while lists/dicts compute per-element/per-pair units (via join over materialized operands) with cardinality set to the literal element/pair count; closures combine fn ptr + env into a single scalar footprint, and opaque aggregates keep the prior “sum raw operands” behavior.

Adds supporting math/utilities: Footprint::materialize() (collapse units × cardinality), Footprint::one(), Estimate::saturating_coeff_mul(), InformationRange::saturating_mul_cardinality(), and Eval::into_footprint(). Updates/extends tests and UI snapshots to reflect corrected cardinalities and new aggregate behaviors.

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indietyp · 2026-05-04T14:24:09Z

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codspeed-hq · 2026-05-04T14:29:56Z

Merging this PR will degrade performance by 11.34%

⚠️

Different runtime environments detected

Some benchmarks with significant performance changes were compared across different runtime environments,
which may affect the accuracy of the results.

Open the report in CodSpeed to investigate

❌ 4 regressed benchmarks
✅ 20 untouched benchmarks
⏩ 56 skipped benchmarks¹

⚠️ Please fix the performance issues or acknowledge them on CodSpeed.

Performance Changes

	Benchmark	`BASE`	`HEAD`	Efficiency
❌	`entity_projections`	64.9 µs	73.2 µs	-11.34%
❌	`fibonacci_recursive[16]`	1.8 ms	2.1 ms	-10.86%
❌	`diamond`	16.2 µs	18 µs	-10.03%
❌	`fibonacci_recursive[24]`	85.9 ms	96.4 ms	-10.9%

_{Comparing bm/be-513-hashql-size-estimation-aggregate-cardinality-is-wrong-for (393f316) with main (a18ae88)²}

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. ↩
No successful run was found on bm/be-512-hashql-switchint-allow-cross-backend-transitions (43c449a) during the generation of this report, so main (a18ae88) was used instead as the comparison base. There might be some changes unrelated to this pull request in this report. ↩

codecov · 2026-05-04T14:31:44Z

Codecov Report

❌ Patch coverage is 91.07143% with 30 lines in your changes missing coverage. Please review.
✅ Project coverage is 68.64%. Comparing base (43c449a) to head (393f316).

Files with missing lines	Patch %	Lines
...l/mir/src/pass/analysis/size_estimation/dynamic.rs	73.49%	22 Missing ⚠️
...mir/src/pass/analysis/size_estimation/footprint.rs	92.15%	4 Missing and 4 partials ⚠️

Additional details and impacted files

@@                                      Coverage Diff                                       @@
##           bm/be-512-hashql-switchint-allow-cross-backend-transitions    #8697      +/-   ##
==============================================================================================
+ Coverage                                                       68.56%   68.64%   +0.08%     
==============================================================================================
  Files                                                            1061     1061              
  Lines                                                          106420   106748     +328     
  Branches                                                         4986     4993       +7     
==============================================================================================
+ Hits                                                            72963    73277     +314     
- Misses                                                          32706    32717      +11     
- Partials                                                          751      754       +3

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)`
rust.hashql-mir	`91.88% <91.07%> (+0.04%)`	⬆️

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cursor

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

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github-actions · 2026-05-12T15:13:47Z

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	$$25.9 \mathrm{ms} \pm 156 \mathrm{μs}\left({\color{gray}0.593 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$3.41 \mathrm{ms} \pm 12.7 \mathrm{μs}\left({\color{gray}-0.341 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 1001	$$12.3 \mathrm{ms} \pm 69.3 \mathrm{μs}\left({\color{gray}-1.566 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 3314	$$42.7 \mathrm{ms} \pm 279 \mathrm{μs}\left({\color{gray}-1.140 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$14.7 \mathrm{ms} \pm 109 \mathrm{μs}\left({\color{gray}-1.714 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 1526	$$24.0 \mathrm{ms} \pm 135 \mathrm{μs}\left({\color{gray}-1.385 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 2078	$$26.9 \mathrm{ms} \pm 143 \mathrm{μs}\left({\color{gray}0.886 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.77 \mathrm{ms} \pm 18.7 \mathrm{μs}\left({\color{gray}1.95 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 1033	$$13.5 \mathrm{ms} \pm 88.7 \mathrm{μs}\left({\color{gray}0.517 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_medium

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 102	$$3.75 \mathrm{ms} \pm 26.4 \mathrm{μs}\left({\color{gray}0.953 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.99 \mathrm{ms} \pm 13.1 \mathrm{μs}\left({\color{gray}0.503 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 51	$$3.35 \mathrm{ms} \pm 15.9 \mathrm{μs}\left({\color{gray}0.275 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 269	$$5.14 \mathrm{ms} \pm 35.5 \mathrm{μs}\left({\color{gray}2.10 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$3.60 \mathrm{ms} \pm 19.1 \mathrm{μs}\left({\color{gray}0.839 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 107	$$4.11 \mathrm{ms} \pm 22.7 \mathrm{μs}\left({\color{gray}0.891 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 133	$$4.38 \mathrm{ms} \pm 36.8 \mathrm{μs}\left({\color{gray}2.47 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.46 \mathrm{ms} \pm 15.1 \mathrm{μs}\left({\color{gray}0.903 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 63	$$4.06 \mathrm{ms} \pm 25.0 \mathrm{μs}\left({\color{gray}0.569 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_none

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 2	$$2.68 \mathrm{ms} \pm 11.4 \mathrm{μs}\left({\color{gray}-0.131 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.48 \mathrm{ms} \pm 10.4 \mathrm{μs}\left({\color{gray}-1.775 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 1	$$2.62 \mathrm{ms} \pm 11.8 \mathrm{μs}\left({\color{gray}-1.630 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 8	$$2.96 \mathrm{ms} \pm 15.2 \mathrm{μs}\left({\color{gray}-0.118 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$2.75 \mathrm{ms} \pm 12.2 \mathrm{μs}\left({\color{gray}-0.114 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 3	$$2.89 \mathrm{ms} \pm 10.1 \mathrm{μs}\left({\color{gray}-2.217 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_small

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 52	$$3.00 \mathrm{ms} \pm 15.8 \mathrm{μs}\left({\color{gray}-0.163 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.72 \mathrm{ms} \pm 16.0 \mathrm{μs}\left({\color{gray}-1.232 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 25	$$2.98 \mathrm{ms} \pm 17.9 \mathrm{μs}\left({\color{gray}0.073 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 94	$$3.35 \mathrm{ms} \pm 18.5 \mathrm{μs}\left({\color{gray}-1.000 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$2.97 \mathrm{ms} \pm 14.7 \mathrm{μs}\left({\color{gray}-0.103 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 26	$$3.28 \mathrm{ms} \pm 16.5 \mathrm{μs}\left({\color{gray}-0.340 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 66	$$3.23 \mathrm{ms} \pm 12.4 \mathrm{μs}\left({\color{gray}-1.670 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$2.95 \mathrm{ms} \pm 15.2 \mathrm{μs}\left({\color{gray}-0.265 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 29	$$3.32 \mathrm{ms} \pm 22.2 \mathrm{μs}\left({\color{gray}0.384 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_complete

Function	Value	Mean	Flame graphs
entity_by_id;one_depth	1 entities	$$54.5 \mathrm{ms} \pm 286 \mathrm{μs}\left({\color{gray}-2.047 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	10 entities	$$46.1 \mathrm{ms} \pm 177 \mathrm{μs}\left({\color{gray}-1.258 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	25 entities	$$50.3 \mathrm{ms} \pm 196 \mathrm{μs}\left({\color{gray}-1.758 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	5 entities	$$44.5 \mathrm{ms} \pm 243 \mathrm{μs}\left({\color{gray}-0.455 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	50 entities	$$61.7 \mathrm{ms} \pm 345 \mathrm{μs}\left({\color{gray}-1.840 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	1 entities	$$61.5 \mathrm{ms} \pm 289 \mathrm{μs}\left({\color{gray}-0.750 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	10 entities	$$56.8 \mathrm{ms} \pm 289 \mathrm{μs}\left({\color{gray}0.091 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	25 entities	$$103 \mathrm{ms} \pm 447 \mathrm{μs}\left({\color{gray}-0.715 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	5 entities	$$46.7 \mathrm{ms} \pm 224 \mathrm{μs}\left({\color{gray}-0.036 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	50 entities	$$323 \mathrm{ms} \pm 1.16 \mathrm{ms}\left({\color{red}18.7 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	1 entities	$$19.9 \mathrm{ms} \pm 114 \mathrm{μs}\left({\color{gray}2.74 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	10 entities	$$20.5 \mathrm{ms} \pm 98.1 \mathrm{μs}\left({\color{gray}1.56 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	25 entities	$$20.9 \mathrm{ms} \pm 117 \mathrm{μs}\left({\color{gray}2.39 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	5 entities	$$19.6 \mathrm{ms} \pm 107 \mathrm{μs}\left({\color{gray}-0.028 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	50 entities	$$25.5 \mathrm{ms} \pm 130 \mathrm{μs}\left({\color{gray}-0.236 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_linkless

Function	Value	Mean	Flame graphs
entity_by_id	1 entities	$$19.5 \mathrm{ms} \pm 86.6 \mathrm{μs}\left({\color{gray}-1.069 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10 entities	$$19.7 \mathrm{ms} \pm 89.9 \mathrm{μs}\left({\color{gray}-0.020 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	100 entities	$$19.9 \mathrm{ms} \pm 100 \mathrm{μs}\left({\color{gray}0.619 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	1000 entities	$$20.4 \mathrm{ms} \pm 109 \mathrm{μs}\left({\color{gray}0.479 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10000 entities	$$27.2 \mathrm{ms} \pm 194 \mathrm{μs}\left({\color{gray}-1.151 \mathrm{\%}}\right) $$	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`	$$34.7 \mathrm{ms} \pm 266 \mathrm{μs}\left({\color{gray}-2.176 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/book/v/1`	$$34.5 \mathrm{ms} \pm 292 \mathrm{μs}\left({\color{gray}1.67 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/building/v/1`	$$34.5 \mathrm{ms} \pm 296 \mathrm{μs}\left({\color{gray}0.673 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/organization/v/1`	$$35.3 \mathrm{ms} \pm 239 \mathrm{μs}\left({\color{gray}0.036 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/page/v/2`	$$34.3 \mathrm{ms} \pm 242 \mathrm{μs}\left({\color{gray}-2.167 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/person/v/1`	$$34.6 \mathrm{ms} \pm 200 \mathrm{μs}\left({\color{gray}-0.888 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/playlist/v/1`	$$34.8 \mathrm{ms} \pm 290 \mathrm{μs}\left({\color{gray}-1.280 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/song/v/1`	$$34.4 \mathrm{ms} \pm 245 \mathrm{μs}\left({\color{gray}0.344 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/uk-address/v/1`	$$34.4 \mathrm{ms} \pm 271 \mathrm{μs}\left({\color{gray}-0.035 \mathrm{\%}}\right) $$	Flame Graph

representative_read_entity_type

Function	Value	Mean	Flame graphs
get_entity_type_by_id	Account ID: `bf5a9ef5-dc3b-43cf-a291-6210c0321eba`	$$8.52 \mathrm{ms} \pm 46.5 \mathrm{μs}\left({\color{gray}0.048 \mathrm{\%}}\right) $$	Flame Graph

representative_read_multiple_entities

Function	Value	Mean	Flame graphs
entity_by_property	traversal_paths=0	0	$$92.4 \mathrm{ms} \pm 486 \mathrm{μs}\left({\color{gray}1.04 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$146 \mathrm{ms} \pm 795 \mathrm{μs}\left({\color{gray}0.406 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$99.1 \mathrm{ms} \pm 637 \mathrm{μs}\left({\color{gray}0.235 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$110 \mathrm{ms} \pm 589 \mathrm{μs}\left({\color{gray}-0.278 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$116 \mathrm{ms} \pm 845 \mathrm{μs}\left({\color{gray}-0.577 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$124 \mathrm{ms} \pm 519 \mathrm{μs}\left({\color{gray}-0.237 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=0	0	$$103 \mathrm{ms} \pm 504 \mathrm{μs}\left({\color{gray}-0.135 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$132 \mathrm{ms} \pm 515 \mathrm{μs}\left({\color{gray}0.566 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$111 \mathrm{ms} \pm 534 \mathrm{μs}\left({\color{gray}1.19 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$121 \mathrm{ms} \pm 528 \mathrm{μs}\left({\color{gray}1.89 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$123 \mathrm{ms} \pm 494 \mathrm{μs}\left({\color{gray}2.15 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$123 \mathrm{ms} \pm 1.08 \mathrm{ms}\left({\color{gray}2.17 \mathrm{\%}}\right) $$

scenarios

Function	Value	Mean	Flame graphs
full_test	query-limited	$$190 \mathrm{ms} \pm 1.53 \mathrm{ms}\left({\color{gray}-0.804 \mathrm{\%}}\right) $$	Flame Graph
full_test	query-unlimited	$$155 \mathrm{ms} \pm 434 \mathrm{μs}\left({\color{lightgreen}-23.971 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-limited	$$39.9 \mathrm{ms} \pm 169 \mathrm{μs}\left({\color{gray}-2.309 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-unlimited	$$575 \mathrm{ms} \pm 923 \mathrm{μs}\left({\color{gray}1.57 \mathrm{\%}}\right) $$	Flame Graph

fix: estimation for aggregates

af539d3

vercel Bot temporarily deployed to Preview – petrinaut May 4, 2026 14:23 Inactive

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 May 4, 2026

graphite-app Bot assigned indietyp May 4, 2026

indietyp mentioned this pull request May 4, 2026

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

Open

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indietyp force-pushed the bm/be-513-hashql-size-estimation-aggregate-cardinality-is-wrong-for branch from d52594c to ae2d3af Compare May 4, 2026 14:24

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Comment thread libs/@local/hashql/mir/src/pass/analysis/size_estimation/footprint.rs

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Comment thread libs/@local/hashql/mir/src/pass/analysis/size_estimation/estimate.rs

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fix: suggestion from code review

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Comment thread libs/@local/hashql/mir/src/pass/analysis/size_estimation/footprint.rs Fixed

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fix: lint

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chore: truncate instead of resize on mul

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Comment thread libs/@local/hashql/mir/src/pass/analysis/size_estimation/footprint.rs

indietyp force-pushed the bm/be-512-hashql-switchint-allow-cross-backend-transitions branch from 5eeec53 to 91d9bc3 Compare May 8, 2026 08:33

indietyp force-pushed the bm/be-513-hashql-size-estimation-aggregate-cardinality-is-wrong-for branch from 598d416 to a64c0f8 Compare May 8, 2026 08:33

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indietyp force-pushed the bm/be-512-hashql-switchint-allow-cross-backend-transitions branch from 91d9bc3 to f2fc415 Compare May 11, 2026 10:58

indietyp force-pushed the bm/be-513-hashql-size-estimation-aggregate-cardinality-is-wrong-for branch from a64c0f8 to 80db587 Compare May 11, 2026 10:58

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Comment thread libs/@local/hashql/mir/src/pass/analysis/size_estimation/footprint.rs

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indietyp force-pushed the bm/be-512-hashql-switchint-allow-cross-backend-transitions branch from f2fc415 to 43c449a Compare May 12, 2026 13:58

indietyp force-pushed the bm/be-513-hashql-size-estimation-aggregate-cardinality-is-wrong-for branch from 80db587 to 393f316 Compare May 12, 2026 13:58

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Conversation

indietyp commented May 4, 2026

🌟 What is the purpose of this PR?

🔍 What does this change?

🛡 What tests cover this?

❓ How to test this?

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PR Summary

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indietyp commented May 4, 2026 • edited Loading Uh oh! There was an error while loading. Please reload this page.

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codspeed-hq Bot commented May 4, 2026 • edited Loading Uh oh! There was an error while loading. Please reload this page.

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Merging this PR will degrade performance by 11.34%

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github-actions Bot commented May 12, 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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