BE-515: HashQL: Remove `OFFSET 0` materialization fence from generated query by indietyp · Pull Request #8650 · hashintel/hash

indietyp · 2026-04-21T17:07:51Z

🌟 What is the purpose of this PR?

HashQL: Remove `OFFSET 0` materialization fence from generated SQL

Problem

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

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

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

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

🚢 Has this modified a publishable library?

This PR:

does not modify any publishable blocks or libraries, or modifications do not need publishing

📜 Does this require a change to the docs?

The changes in this PR:

are internal and do not require a docs change

🕸️ Does this require a change to the Turbo Graph?

The changes in this PR:

do not affect the execution graph

🛡 What tests cover this?

Existing test coverage for the HashQL eval Postgres module.

❓ How to test this?

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

vercel · 2026-04-21T17:07:56Z

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Project	Deployment	Actions	Updated (UTC)
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indietyp · 2026-04-21T17:08:23Z

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codecov · 2026-04-21T17:14:02Z

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 63.77%. Comparing base (5f2a3af) to head (a0db929).

Additional details and impacted files

@@                                            Coverage Diff                                            @@
##           bm/be-514-hashql-solver-iterate-forwardbackward-passes-to-convergence    #8650      +/-   ##
=========================================================================================================
- Coverage                                                                  63.85%   63.77%   -0.09%     
=========================================================================================================
  Files                                                                       1358     1358              
  Lines                                                                     143835   143501     -334     
  Branches                                                                    5649     5639      -10     
=========================================================================================================
- Hits                                                                       91847    91515     -332     
+ Misses                                                                     51015    51013       -2     
  Partials                                                                     973      973

Flag	Coverage Δ
apps.hash-ai-worker-ts	`1.40% <ø> (ø)`
apps.hash-api	`0.00% <ø> (ø)`
local.hash-graph-sdk	`9.63% <ø> (ø)`
local.hash-isomorphic-utils	`0.00% <ø> (ø)`
rust.hash-graph-api	`2.52% <ø> (ø)`
rust.hashql-compiletest	`28.26% <ø> (ø)`
rust.hashql-eval	`79.70% <ø> (-0.01%)`	⬇️

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codspeed-hq · 2026-04-21T17:16:37Z

Merging this PR will not alter performance

✅ 80 untouched benchmarks

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

cursor · 2026-04-29T15:42:56Z

PR Summary

Medium Risk
Changes the shape of generated SQL in a performance-sensitive area; behavior should be equivalent but query plans (and thus latency) can shift, including potential regressions for simple filters.

Overview
Removes the OFFSET 0 materialization fence from Postgres island CROSS JOIN LATERAL continuation subqueries, changing the generated SQL to allow the planner to inline the subquery rather than forcing per-row materialization.

Updates continuation-related documentation/comments and rewrites all affected Postgres UI test snapshots/stdouts to match the new unfenced LATERAL SQL shape.

^{Reviewed by Cursor Bugbot for commit a0db929. Bugbot is set up for automated code reviews on this repo. Configure here.}

augmentcode · 2026-04-29T17:29:53Z

🤖 Augment PR Summary

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

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

augmentcode

Review completed. 1 suggestion posted.

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

cursor

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

^{❌ Bugbot Autofix is OFF. To automatically fix reported issues with cloud agents, enable autofix in the Cursor dashboard.}

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

cursor · 2026-04-30T10:05:48Z

 //!
 //! Each postgres island in a filter body produces a `CROSS JOIN LATERAL` subquery
-//! that evaluates its CASE tree once per row (via `OFFSET 0`) and returns a
+//! that evaluates its CASE tree once per row  and returns a


Double space in doc comment after editing

Low Severity

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

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

github-actions · 2026-04-30T12:59:28Z

Benchmark results

@rust/hash-graph-benches – Integrations

policy_resolution_large

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 2002	$$26.4 \mathrm{ms} \pm 119 \mathrm{μs}\left({\color{gray}2.32 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.84 \mathrm{ms} \pm 14.1 \mathrm{μs}\left({\color{gray}0.338 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 1001	$$11.6 \mathrm{ms} \pm 65.6 \mathrm{μs}\left({\color{gray}1.71 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 3314	$$37.4 \mathrm{ms} \pm 310 \mathrm{μs}\left({\color{gray}-1.409 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$11.4 \mathrm{ms} \pm 92.6 \mathrm{μs}\left({\color{gray}2.28 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 1526	$$20.6 \mathrm{ms} \pm 140 \mathrm{μs}\left({\color{gray}-2.779 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 2078	$$26.7 \mathrm{ms} \pm 202 \mathrm{μs}\left({\color{gray}-0.927 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.11 \mathrm{ms} \pm 14.1 \mathrm{μs}\left({\color{gray}0.042 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 1033	$$12.5 \mathrm{ms} \pm 80.1 \mathrm{μs}\left({\color{gray}1.00 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_medium

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

policy_resolution_none

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

policy_resolution_small

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

read_scaling_complete

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

read_scaling_linkless

Function	Value	Mean	Flame graphs
entity_by_id	1 entities	$$16.4 \mathrm{ms} \pm 66.1 \mathrm{μs}\left({\color{gray}1.35 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10 entities	$$16.7 \mathrm{ms} \pm 85.8 \mathrm{μs}\left({\color{gray}2.27 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	100 entities	$$16.5 \mathrm{ms} \pm 85.1 \mathrm{μs}\left({\color{gray}-0.156 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	1000 entities	$$17.2 \mathrm{ms} \pm 67.1 \mathrm{μs}\left({\color{gray}-1.500 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10000 entities	$$24.0 \mathrm{ms} \pm 151 \mathrm{μs}\left({\color{gray}1.54 \mathrm{\%}}\right) $$	Flame Graph

representative_read_entity

Function	Value	Mean	Flame graphs
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/block/v/1`	$$31.5 \mathrm{ms} \pm 230 \mathrm{μs}\left({\color{gray}2.07 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/book/v/1`	$$31.7 \mathrm{ms} \pm 245 \mathrm{μs}\left({\color{gray}3.72 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/building/v/1`	$$29.9 \mathrm{ms} \pm 244 \mathrm{μs}\left({\color{lightgreen}-5.757 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/organization/v/1`	$$30.7 \mathrm{ms} \pm 277 \mathrm{μs}\left({\color{gray}-0.301 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/page/v/2`	$$30.8 \mathrm{ms} \pm 266 \mathrm{μs}\left({\color{gray}-3.183 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/person/v/1`	$$31.0 \mathrm{ms} \pm 286 \mathrm{μs}\left({\color{gray}-2.494 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/playlist/v/1`	$$31.6 \mathrm{ms} \pm 327 \mathrm{μs}\left({\color{gray}2.65 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/song/v/1`	$$32.0 \mathrm{ms} \pm 328 \mathrm{μs}\left({\color{gray}-2.764 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/uk-address/v/1`	$$31.5 \mathrm{ms} \pm 297 \mathrm{μs}\left({\color{gray}-1.020 \mathrm{\%}}\right) $$	Flame Graph

representative_read_entity_type

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

representative_read_multiple_entities

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

scenarios

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

chore: remove OFFSET 0

e19dfe9

indietyp mentioned this pull request Apr 21, 2026

BE-514: HashQL: implement iterative adjustment passes in placement solver #8635

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indietyp force-pushed the bm/be-515-hashql-remove-offset-0-materialization-fence-from-generated branch from 7a113b5 to c5c10fa Compare April 30, 2026 09:02

indietyp force-pushed the bm/be-514-hashql-solver-iterate-forwardbackward-passes-to-convergence branch from 0ca8770 to b02766e Compare April 30, 2026 09:02

vercel Bot temporarily deployed to Preview – petrinaut April 30, 2026 09:02 Inactive

indietyp force-pushed the bm/be-515-hashql-remove-offset-0-materialization-fence-from-generated branch from c5c10fa to 526e21d Compare April 30, 2026 09:04

indietyp force-pushed the bm/be-514-hashql-solver-iterate-forwardbackward-passes-to-convergence branch from b02766e to f2b4e96 Compare April 30, 2026 09:04

vercel Bot temporarily deployed to Preview – petrinaut April 30, 2026 09:04 Inactive

indietyp force-pushed the bm/be-515-hashql-remove-offset-0-materialization-fence-from-generated branch from 526e21d to 2cf065b Compare April 30, 2026 09:06

indietyp force-pushed the bm/be-514-hashql-solver-iterate-forwardbackward-passes-to-convergence branch from f2b4e96 to 1c2cf8c Compare April 30, 2026 09:06

vercel Bot temporarily deployed to Preview – petrinaut April 30, 2026 09:06 Inactive

cursor Bot reviewed Apr 30, 2026

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indietyp commented Apr 21, 2026

🌟 What is the purpose of this PR?

HashQL: Remove OFFSET 0 materialization fence from generated SQL

Problem

🚢 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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codspeed-hq Bot commented Apr 21, 2026

Merging this PR will not alter performance

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augmentcode Bot commented Apr 29, 2026

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cursor Bot Apr 30, 2026

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Double space in doc comment after editing

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github-actions Bot commented Apr 30, 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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HashQL: Remove `OFFSET 0` materialization fence from generated SQL

vercel Bot commented Apr 21, 2026 •

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indietyp commented Apr 21, 2026 •

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codecov Bot commented Apr 21, 2026 •

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cursor Bot commented Apr 29, 2026 •

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