BE-599: Compute entity summary aggregations in SQL by TimDiekmann · Pull Request #8864 · hashintel/hash

TimDiekmann · 2026-06-12T14:40:39Z

🌟 What is the purpose of this PR?

When any of the include* summary flags is set, queryEntities re-ran the full filtered query unbounded (no DISTINCT, no LIMIT) and streamed every matching row to the client to fold counts there.

This PR computes the summaries (total count, per-web, per-creator, per-edition-creator, per-type counts) in SQL instead: the compiled filter query is wrapped into a deduplicated hits CTE feeding one UNION ALL aggregate branch per requested dimension, so only the aggregate rows cross the wire.

🔗 Related links

BE-599

🚫 Blocked by

BE-596: Materialize entity aggregates into entity_edition_cache #8854

🔍 What does this change?

New module postgres/knowledge/entity/summary.rs: EntitySummaryQuery::new(compiler, params) adds the required selections (or returns None when no summary is requested), statement() wraps the compiled query into the aggregate statement, decode() routes the result rows into EntitySummaries via a Dimension discriminant enum.
The per-type counts unnest the direct-type prefix of the entity_edition_cache arrays (from BE-596: Materialize entity aggregates into entity_edition_cache #8854) instead of joining the type tables.
Deduplication is per entity identity: plain (hashable) DISTINCT when only entity-scoped columns are selected, DISTINCT ON (web_id, entity_uuid, draft_id) when edition-scoped columns (edition provenance, type arrays) are present — interval temporal axes can match multiple editions per entity, and a plain DISTINCT over edition-scoped columns would inflate the counts.
Behaviour fix: includeTypeTitles: true without any other summary flag now returns type titles; previously the summary pass silently never ran for it.
decode returns Result instead of panicking on unexpected row shapes (e.g. a NULL actor ID from malformed provenance JSON).
query/mod.rs: test_helper is pub(crate) so the new module's unit tests can reuse trim_whitespace.

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

⚠️ Known issues

The summary query inherits the type-chain joins from the compiled filter; BE-597 (next PR in the stack) replaces those with array predicates and multiplies the win.
DISTINCT ON picks an arbitrary edition per entity for the edition-scoped dimensions under interval temporal axes — same nondeterminism as the previous client-side HashMap fold.

🐾 Next steps

BE-597: array-based type filtering in the SelectCompiler (stacked on this PR).
Integration tests covering the include* flags (incl. multi-edition entities under interval axes).

🛡 What tests cover this?

New unit tests in summary.rs pinning the generated aggregate SQL (all dimensions incl. DISTINCT ON, count-only) and the dimension discriminant round-trip.
Existing integration tests covering queryEntities/queryEntitySubgraph responses in CI.

❓ How to test this?

Checkout the branch, start the graph with a seeded database.
Run a queryEntitySubgraph request with includeCount/includeWebIds/includeCreatedByIds/includeEditionCreatedByIds/includeTypeIds/includeTypeTitles set.
Confirm the summary fields match the values on the base branch and the query no longer streams all matching rows.

vercel · 2026-06-12T14:40:46Z

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cursor · 2026-06-12T14:40:48Z

PR Summary

Medium Risk
Changes core read-path SQL and deduplication semantics for edition-scoped summaries under interval temporal axes; large-query behavior shifts but outputs are intended to match prior aggregation.

Overview
Moves queryEntities / queryEntitySubgraph summary fields (count, per-web, per-creator, per-edition-creator, per-type) from client-side folding over every matching row to PostgreSQL aggregation via new EntitySummaryQuery in summary.rs.

The compiled filter query is wrapped in a deduplicated hits CTE (DISTINCT or DISTINCT ON entity identity when edition-scoped columns are needed), then UNION ALL branches aggregate each requested dimension; per-type counts use unnest(versioned_urls[1:direct_types]) from the edition cache instead of type-table joins.

query_entities_impl now runs this aggregate query before the limited entity fetch. includeTypeTitles alone now triggers the summary pass (titles-only no longer skipped). Summary decoding errors on bad rows instead of panicking. Adds unit tests for generated SQL and an integration test for all include_* flags.

^{Reviewed by Cursor Bugbot for commit 22de6ab. Bugbot is set up for automated code reviews on this repo. Configure here.}

Copilot

Pull request overview

This PR moves entity-query summary aggregation (the various include_* summary flags) from client-side folding over an unbounded result stream to server-side SQL aggregation, reducing the amount of data streamed back and improving performance on large datasets.

Changes:

Add knowledge/entity/summary.rs to build a deduplicated hits CTE and compute requested summary dimensions via UNION ALL aggregate branches, plus decode the resulting rows into EntitySummaries.
Update knowledge/entity/mod.rs to use the SQL-side summary query and to ensure includeTypeTitles alone triggers the summary pass (so titles are returned).
Expose query::test_helper as pub(crate) (still #[cfg(test)]) so the new module’s unit tests can reuse trim_whitespace.

Reviewed changes

Copilot reviewed 3 out of 3 changed files in this pull request and generated 1 comment.

File	Description
libs/@local/graph/postgres-store/src/store/postgres/query/mod.rs	Makes `test_helper` accessible within the crate during tests for reuse by new summary unit tests.
libs/@local/graph/postgres-store/src/store/postgres/knowledge/entity/summary.rs	New SQL-side summary aggregation/query builder + decoder + unit tests for statement generation and dimension discriminant round-trip.
libs/@local/graph/postgres-store/src/store/postgres/knowledge/entity/mod.rs	Replaces client-side summary folding with SQL aggregate query execution + decoding; fixes `includeTypeTitles`-only behavior.

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codecov · 2026-06-12T14:47:46Z

Codecov Report

❌ Patch coverage is 67.98246% with 73 lines in your changes missing coverage. Please review.
✅ Project coverage is 59.21%. Comparing base (db769d6) to head (df62a4e).

Files with missing lines	Patch %	Lines
...ore/src/store/postgres/knowledge/entity/summary.rs	67.98%	71 Missing and 2 partials ⚠️

Additional details and impacted files

@@                                            Coverage Diff                                            @@
##           t/be-596-materialize-the-aggregate-views-in-the-entity-subgraph-query    #8864      +/-   ##
=========================================================================================================
+ Coverage                                                                  59.17%   59.21%   +0.03%     
=========================================================================================================
  Files                                                                       1346     1347       +1     
  Lines                                                                     130111   130290     +179     
  Branches                                                                    5885     5894       +9     
=========================================================================================================
+ Hits                                                                       76995    77150     +155     
- Misses                                                                     52210    52232      +22     
- Partials                                                                     906      908       +2

Flag	Coverage Δ
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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	`2.51% <ø> (ø)`
rust.hash-graph-postgres-store	`27.65% <67.98%> (+0.60%)`	⬆️
rust.hashql-compiletest	`28.26% <ø> (ø)`
rust.hashql-eval	`75.72% <ø> (ø)`

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github-actions · 2026-06-12T16:27:35Z

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	$$25.7 \mathrm{ms} \pm 159 \mathrm{μs}\left({\color{gray}-1.224 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$3.44 \mathrm{ms} \pm 19.0 \mathrm{μs}\left({\color{gray}-1.092 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 1001	$$12.7 \mathrm{ms} \pm 105 \mathrm{μs}\left({\color{gray}1.50 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 3314	$$43.2 \mathrm{ms} \pm 363 \mathrm{μs}\left({\color{gray}1.26 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$14.5 \mathrm{ms} \pm 111 \mathrm{μs}\left({\color{lightgreen}-6.563 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 1526	$$24.4 \mathrm{ms} \pm 164 \mathrm{μs}\left({\color{gray}0.090 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 2078	$$27.5 \mathrm{ms} \pm 220 \mathrm{μs}\left({\color{gray}2.12 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.89 \mathrm{ms} \pm 30.5 \mathrm{μs}\left({\color{gray}0.415 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 1033	$$14.2 \mathrm{ms} \pm 111 \mathrm{μs}\left({\color{gray}2.95 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_medium

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 102	$$3.84 \mathrm{ms} \pm 26.4 \mathrm{μs}\left({\color{gray}2.08 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$3.04 \mathrm{ms} \pm 19.9 \mathrm{μs}\left({\color{gray}0.423 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 51	$$3.44 \mathrm{ms} \pm 20.5 \mathrm{μs}\left({\color{gray}1.42 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 269	$$5.18 \mathrm{ms} \pm 39.1 \mathrm{μs}\left({\color{gray}1.43 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$3.57 \mathrm{ms} \pm 22.2 \mathrm{μs}\left({\color{gray}1.55 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 107	$$4.28 \mathrm{ms} \pm 47.7 \mathrm{μs}\left({\color{gray}3.31 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 133	$$4.37 \mathrm{ms} \pm 26.3 \mathrm{μs}\left({\color{gray}-4.171 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.63 \mathrm{ms} \pm 28.0 \mathrm{μs}\left({\color{gray}3.74 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 63	$$4.15 \mathrm{ms} \pm 41.3 \mathrm{μs}\left({\color{gray}-2.845 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_none

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 2	$$2.64 \mathrm{ms} \pm 14.4 \mathrm{μs}\left({\color{lightgreen}-11.170 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.56 \mathrm{ms} \pm 15.9 \mathrm{μs}\left({\color{gray}-3.850 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 1	$$2.65 \mathrm{ms} \pm 21.6 \mathrm{μs}\left({\color{lightgreen}-5.820 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 8	$$2.91 \mathrm{ms} \pm 14.9 \mathrm{μs}\left({\color{gray}-4.607 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.22 \mathrm{ms} \pm 23.7 \mathrm{μs}\left({\color{red}9.70 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 3	$$3.14 \mathrm{ms} \pm 38.7 \mathrm{μs}\left({\color{lightgreen}-5.265 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_small

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 52	$$3.05 \mathrm{ms} \pm 19.2 \mathrm{μs}\left({\color{gray}1.24 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.76 \mathrm{ms} \pm 15.7 \mathrm{μs}\left({\color{gray}-0.366 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 25	$$2.99 \mathrm{ms} \pm 20.3 \mathrm{μs}\left({\color{gray}0.112 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 94	$$3.37 \mathrm{ms} \pm 20.1 \mathrm{μs}\left({\color{gray}0.594 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$2.98 \mathrm{ms} \pm 16.2 \mathrm{μs}\left({\color{gray}-0.118 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 26	$$3.28 \mathrm{ms} \pm 19.7 \mathrm{μs}\left({\color{gray}0.062 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 66	$$3.31 \mathrm{ms} \pm 19.6 \mathrm{μs}\left({\color{gray}-0.005 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$2.98 \mathrm{ms} \pm 16.7 \mathrm{μs}\left({\color{gray}1.12 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 29	$$3.32 \mathrm{ms} \pm 20.5 \mathrm{μs}\left({\color{gray}1.65 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_complete

Function	Value	Mean	Flame graphs
entity_by_id;one_depth	1 entities	$$57.5 \mathrm{ms} \pm 329 \mathrm{μs}\left({\color{gray}0.118 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	10 entities	$$49.5 \mathrm{ms} \pm 300 \mathrm{μs}\left({\color{gray}-0.142 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	25 entities	$$52.9 \mathrm{ms} \pm 425 \mathrm{μs}\left({\color{gray}0.041 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	5 entities	$$48.3 \mathrm{ms} \pm 301 \mathrm{μs}\left({\color{gray}-0.412 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	50 entities	$$64.4 \mathrm{ms} \pm 705 \mathrm{μs}\left({\color{gray}-0.248 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	1 entities	$$65.2 \mathrm{ms} \pm 370 \mathrm{μs}\left({\color{gray}-3.164 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	10 entities	$$58.2 \mathrm{ms} \pm 373 \mathrm{μs}\left({\color{gray}-1.457 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	25 entities	$$111 \mathrm{ms} \pm 615 \mathrm{μs}\left({\color{gray}-1.890 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	5 entities	$$50.3 \mathrm{ms} \pm 286 \mathrm{μs}\left({\color{lightgreen}-9.787 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	50 entities	$$285 \mathrm{ms} \pm 1.29 \mathrm{ms}\left({\color{lightgreen}-7.816 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	1 entities	$$22.8 \mathrm{ms} \pm 135 \mathrm{μs}\left({\color{gray}-4.266 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	10 entities	$$24.2 \mathrm{ms} \pm 165 \mathrm{μs}\left({\color{lightgreen}-5.751 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	25 entities	$$22.9 \mathrm{ms} \pm 149 \mathrm{μs}\left({\color{gray}-2.335 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	5 entities	$$22.8 \mathrm{ms} \pm 188 \mathrm{μs}\left({\color{lightgreen}-6.588 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	50 entities	$$27.4 \mathrm{ms} \pm 160 \mathrm{μs}\left({\color{gray}0.029 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_linkless

Function	Value	Mean	Flame graphs
entity_by_id	1 entities	$$22.2 \mathrm{ms} \pm 130 \mathrm{μs}\left({\color{gray}-2.985 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10 entities	$$22.3 \mathrm{ms} \pm 138 \mathrm{μs}\left({\color{gray}-1.389 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	100 entities	$$22.2 \mathrm{ms} \pm 104 \mathrm{μs}\left({\color{gray}-0.087 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	1000 entities	$$22.0 \mathrm{ms} \pm 162 \mathrm{μs}\left({\color{gray}0.781 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10000 entities	$$22.8 \mathrm{ms} \pm 134 \mathrm{μs}\left({\color{gray}-0.534 \mathrm{\%}}\right) $$	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`	$$24.7 \mathrm{ms} \pm 137 \mathrm{μs}\left({\color{gray}3.07 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/book/v/1`	$$24.8 \mathrm{ms} \pm 149 \mathrm{μs}\left({\color{gray}3.46 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/building/v/1`	$$24.9 \mathrm{ms} \pm 121 \mathrm{μs}\left({\color{red}6.00 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/organization/v/1`	$$24.8 \mathrm{ms} \pm 142 \mathrm{μs}\left({\color{red}5.16 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/page/v/2`	$$25.2 \mathrm{ms} \pm 162 \mathrm{μs}\left({\color{gray}-1.054 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/person/v/1`	$$24.8 \mathrm{ms} \pm 135 \mathrm{μs}\left({\color{gray}4.55 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/playlist/v/1`	$$25.1 \mathrm{ms} \pm 221 \mathrm{μs}\left({\color{red}6.62 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/song/v/1`	$$24.8 \mathrm{ms} \pm 139 \mathrm{μs}\left({\color{red}5.33 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/uk-address/v/1`	$$25.3 \mathrm{ms} \pm 162 \mathrm{μs}\left({\color{gray}-2.307 \mathrm{\%}}\right) $$	Flame Graph

representative_read_entity_type

Function	Value	Mean	Flame graphs
get_entity_type_by_id	Account ID: `bf5a9ef5-dc3b-43cf-a291-6210c0321eba`	$$8.59 \mathrm{ms} \pm 55.2 \mathrm{μs}\left({\color{gray}1.46 \mathrm{\%}}\right) $$	Flame Graph

representative_read_multiple_entities

Function	Value	Mean	Flame graphs
entity_by_property	traversal_paths=0	0	$$62.7 \mathrm{ms} \pm 464 \mathrm{μs}\left({\color{gray}0.110 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$112 \mathrm{ms} \pm 826 \mathrm{μs}\left({\color{gray}-1.230 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$70.0 \mathrm{ms} \pm 473 \mathrm{μs}\left({\color{gray}0.497 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$77.4 \mathrm{ms} \pm 481 \mathrm{μs}\left({\color{gray}-4.557 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$87.5 \mathrm{ms} \pm 790 \mathrm{μs}\left({\color{gray}-1.914 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$92.1 \mathrm{ms} \pm 791 \mathrm{μs}\left({\color{gray}-0.131 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=0	0	$$81.5 \mathrm{ms} \pm 445 \mathrm{μs}\left({\color{gray}-0.707 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$113 \mathrm{ms} \pm 689 \mathrm{μs}\left({\color{gray}1.26 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$88.6 \mathrm{ms} \pm 601 \mathrm{μs}\left({\color{gray}-0.411 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$97.3 \mathrm{ms} \pm 514 \mathrm{μs}\left({\color{gray}-0.499 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$101 \mathrm{ms} \pm 751 \mathrm{μs}\left({\color{gray}0.734 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$100 \mathrm{ms} \pm 589 \mathrm{μs}\left({\color{gray}-0.078 \mathrm{\%}}\right) $$

scenarios

Function	Value	Mean	Flame graphs
full_test	query-limited	$$143 \mathrm{ms} \pm 594 \mathrm{μs}\left({\color{gray}0.893 \mathrm{\%}}\right) $$	Flame Graph
full_test	query-unlimited	$$153 \mathrm{ms} \pm 699 \mathrm{μs}\left({\color{gray}-0.887 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-limited	$$57.5 \mathrm{ms} \pm 310 \mathrm{μs}\left({\color{red}27.8 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-unlimited	$$584 \mathrm{ms} \pm 1.08 \mathrm{ms}\left({\color{gray}-0.239 \mathrm{\%}}\right) $$	Flame Graph

Compute the entity summary aggregations in SQL instead of client-side

df62a4e

Copilot AI review requested due to automatic review settings June 12, 2026 14:40

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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 Jun 12, 2026

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Comment thread libs/@local/graph/postgres-store/src/store/postgres/knowledge/entity/mod.rs

Add integration test for summary aggregations

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BE-597: Array-based type filtering in the SelectCompiler #8866

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BE-599: Compute entity summary aggregations in SQL#8864

BE-599: Compute entity summary aggregations in SQL#8864
TimDiekmann wants to merge 2 commits into
t/be-596-materialize-the-aggregate-views-in-the-entity-subgraph-queryfrom
t/be-599-compute-the-entity-summary-aggregations-in-sql-instead-of

TimDiekmann commented Jun 12, 2026 •

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github-actions Bot commented Jun 12, 2026

@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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TimDiekmann commented Jun 12, 2026 • edited Loading Uh oh! There was an error while loading. Please reload this page.

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🌟 What is the purpose of this PR?

🔗 Related links

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🔍 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?

⚠️ Known issues

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🛡 What tests cover this?

❓ How to test this?

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PR Summary

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github-actions Bot commented Jun 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

scenarios

Uh oh!

Reviewers

Assignees

Labels

Milestone

Development

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2 participants

TimDiekmann commented Jun 12, 2026 •

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vercel Bot commented Jun 12, 2026 •

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cursor Bot commented Jun 12, 2026 •

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codecov Bot commented Jun 12, 2026 •

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