Update npm package js-yaml to v4.3.1 [SECURITY]

[hash-dependencies]

This PR contains the following updates:

Package	Change	Age	Confidence
js-yaml	4.3.0 → 4.3.1

---

JS-YAML: Quadratic CPU consumption in !!omap resolution (3.x and 4.x) — CVE-2026-59870 fix not backported

GHSA-5p4m-2wfm-xmqj

More information

Details

Quadratic CPU consumption in !!omap resolution (js-yaml 3.x and 4.x)

Summary

resolveYamlOmap() enforces key uniqueness for !!omap sequences with a linear
scan (objectKeys.indexOf(...)) inside the per-element loop, making resolution
O(n²) in the number of entries. A modestly sized YAML document therefore
consumes disproportionate CPU inside yaml.load(), giving a denial of service
against any consumer that parses untrusted YAML.

!!omap is registered in the default schema
(lib/schema/default.js → require('../type/omap')), so a plain
yaml.load(untrustedInput) with no options is affected — no custom schema or
non-default configuration is required.

This is the same weakness as CVE-2026-59870 / GHSA-724g-mxrg-4qvm, which was
fixed in the 5.x line in 5.2.1. That fix was never backported: both currently
maintained legacy lines still carry the original implementation.

Affected versions

Line	Latest tested	Status
3.x	3.15.0	Affected — objectKeys.indexOf(pairKey) at lib/type/omap.js:29
4.x	4.3.0	Affected — objectKeys.indexOf(pairKey) at lib/type/omap.js:30
5.x	5.2.2	Not affected — fixed in 5.2.1 (uses a Set)

Both figures are the newest release of each line at the time of writing, so
this is not a "you are on an old version" issue.

Details

lib/type/omap.js (js-yaml 4.3.0):

if (objectKeys.indexOf(pairKey) === -1) objectKeys.push(pairKey)
else return false

objectKeys grows by one element per entry, and Array.prototype.indexOf is a
linear scan, so resolving an n-entry !!omap performs roughly
1 + 2 + … + n comparisons — quadratic in n. The work happens synchronously
inside yaml.load(), blocking the event loop for its whole duration.

The 5.x line already solves exactly this by tracking seen keys in a Set
(src/tag/sequence/omap.ts):

if (carrier.seen.has(key)) return 'duplicate key in ordered map'
carrier.seen.add(key)

Proof of concept

// poc.js  —  node poc.js
const yaml = require('js-yaml');
const doc = n => '!!omap\n' + Array.from({length: n}, (_, i) => `- k${i}: ${i}`).join('\n') + '\n';

for (const n of [10000, 20000, 40000, 80000]) {
  const d = doc(n), t = Date.now();
  yaml.load(d);                      // default schema, no options
  console.log(`n=${n} bytes=${d.length} load=${Date.now() - t}ms`);
}

Measured (node v20.20.2, default heap, no flags)

js-yaml 4.3.0

n=10000  bytes=137787   load=54ms
n=20000  bytes=297787   load=169ms
n=40000  bytes=617787   load=646ms
n=80000  bytes=1257787  load=2607ms

js-yaml 3.15.0

n=10000  bytes=137787   load=53ms
n=20000  bytes=297787   load=166ms
n=40000  bytes=617787   load=641ms
n=80000  bytes=1257787  load=2567ms

Runtime grows by a factor of ~4 for each doubling of n, which is the
signature of O(n²) (linear growth would be ~2×).

Scaling further: a 2.48 MB document with 150,000 entries blocked
yaml.load() for 10.8 seconds.

Impact

Any service that parses attacker-influenced YAML with js-yaml 3.x or 4.x can be
stalled with a small input. Because the loop is synchronous, a single request
blocks the Node.js event loop and stalls every other request in the process —
so the amplification is per-process, not just per-request.

Suggested severity: consistent with CVE-2026-59870 (the same weakness in
5.x), i.e. Availability-only impact, network attack vector, no privileges or
user interaction required.

Suggested fix

Mirror the 5.x fix — replace the linear scan with a Set:

// lib/type/omap.js
const seen = new Set()
// ...
if (seen.has(pairKey)) return false
seen.add(pairKey)

This preserves the existing duplicate-key rejection semantics exactly while
making resolution O(n). A maxOmapLength-style cap would also work, but the
Set matches what 5.x already ships and requires no new option.

References

• CVE-2026-59870 / GHSA-724g-mxrg-4qvm — same weakness in 5.0.0–5.2.0, fixed in 5.2.1
• lib/type/omap.js (3.x, 4.x) — the affected resolver
• lib/schema/default.js — registers !!omap in the default schema

Discovery

Found by an automated static-analysis and executed-proof-of-concept scanner run
against js-yaml 4.2.0, then manually verified against 3.15.0 and 4.3.0 by
executing the proof of concept above. All timings in this report were measured
on the current releases of each line, not on the version originally scanned.

Severity

• CVSS Score: 7.5 / 10 (High)
• Vector String: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

References

• https://github.com/nodeca/js-yaml/security/advisories/GHSA-5p4m-2wfm-xmqj
• https://github.com/advisories/GHSA-5p4m-2wfm-xmqj

This data is provided by the GitHub Advisory Database (CC-BY 4.0).

---

Release Notes

nodeca/js-yaml (js-yaml)

v4.3.1

Compare Source

---

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This PR has been generated by Mend Renovate.

[vercel]

The latest updates on your projects. Learn more about Vercel for GitHub.

Project	Deployment	Actions	Updated (UTC)
hash	Error		Aug 7, 2026 6:38am
hashdotdesign-tokens	Error		Aug 7, 2026 6:38am
petrinaut	Error		Aug 7, 2026 6:38am

[hash-dependencies]

⚠️ Artifact update problem

Renovate failed to update an artifact related to this branch. You probably do not want to merge this PR as-is.

♻ Renovate will retry this branch, including artifacts, only when one of the following happens:

• any of the package files in this branch needs updating, or
• the branch becomes conflicted, or
• you click the rebase/retry checkbox if found above, or
• you rename this PR's title to start with "rebase!" to trigger it manually

The artifact failure details are included below:

File name: yarn.lock

error This project's package.json defines "packageManager": "yarn@4.16.0". However the current global version of Yarn is 1.22.22.

Presence of the "packageManager" field indicates that the project is meant to be used with Corepack, a tool included by default with all official Node.js distributions starting from 16.9 and 14.19.
Corepack must currently be enabled by running corepack enable in your terminal. For more information, check out https://yarnpkg.com/corepack.

[cursor]

PR Summary

Low Risk
Patch-level dependency bump with no source changes; low integration risk aside from verifying lockfile/install consistency.

Overview
Bumps js-yaml from 4.3.0 to 4.3.1 across direct dependencies (@apps/hash-api, @local/repo-chores, @tests/hash-playwright) and the root resolutions entry for @redocly/openapi-core/js-yaml.

This is a dependency-only change (no application code). It addresses GHSA-5p4m-2wfm-xmqj (quadratic CPU use when resolving !!omap during yaml.load() on untrusted YAML).

^{Reviewed by Cursor Bugbot for commit 9d964dc. Bugbot is set up for automated code reviews on this repo. Configure here.}

[cursor]

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

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[cursor]

Lockfile omits security bump

High Severity

package.json files now request js-yaml@4.3.1, but yarn.lock still pins js-yaml@4.3.0 for the workspace packages and the shared resolution. Under Yarn 4, installs either fail on the lockfile mismatch or keep the vulnerable 4.3.0 build, so the intended CVE fix does not land.

Additional Locations (2)

• libs/@local/repo-chores/node/package.json#L26-L27
• package.json#L86-L87

 

^{Reviewed by Cursor Bugbot for commit 9d964dc. Configure here.}

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 59.57%. Comparing base (c072f0d) to head (9d964dc).
⚠️ Report is 2 commits behind head on main.

Additional details and impacted files

@@           Coverage Diff           @@
##             main    #9175   +/-   ##
=======================================
  Coverage   59.57%   59.57%           
=======================================
  Files        1413     1413           
  Lines      138053   138053           
  Branches     6510     6510           
=======================================
  Hits        82241    82241           
  Misses      54770    54770           
  Partials     1042     1042           

Flag	Coverage Δ
apps.hash-ai-worker-ts	1.99% <ø> (ø)
blockprotocol.type-system	40.84% <ø> (ø)
local.claude-hooks	0.00% <ø> (ø)
local.harpc-client	51.49% <ø> (ø)
local.hash-backend-utils	3.27% <ø> (ø)
local.hash-graph-sdk	10.02% <ø> (ø)
local.hash-isomorphic-utils	12.25% <ø> (ø)
rust.antsi	2.36% <ø> (ø)
rust.error-stack	90.81% <ø> (ø)
rust.harpc-codec	84.70% <ø> (ø)
rust.harpc-net	96.21% <ø> (ø)
rust.harpc-tower	67.03% <ø> (ø)
rust.harpc-types	0.00% <ø> (ø)
rust.harpc-wire-protocol	92.23% <ø> (ø)
rust.hash-codec	72.76% <ø> (ø)
rust.hash-graph-api	7.36% <ø> (ø)
rust.hash-graph-authorization	62.59% <ø> (ø)
rust.hash-graph-embeddings	91.88% <ø> (ø)
rust.hash-graph-postgres-store	29.66% <ø> (ø)
rust.hash-graph-store	42.16% <ø> (ø)
rust.hash-graph-temporal-versioning	47.95% <ø> (ø)
rust.hash-graph-types	0.00% <ø> (ø)
rust.hash-graph-validation	84.71% <ø> (ø)
rust.hashql-ast	89.63% <ø> (ø)
rust.hashql-compiletest	28.39% <ø> (ø)
rust.hashql-core	78.98% <ø> (ø)
rust.hashql-diagnostics	72.51% <ø> (ø)
rust.hashql-eval	79.82% <ø> (ø)
rust.hashql-hir	89.09% <ø> (ø)
rust.hashql-mir	87.92% <ø> (ø)
rust.hashql-syntax-jexpr	94.04% <ø> (ø)

Flags with carried forward coverage won't be shown. Click here to find out more.

☔ View full report in Codecov by Harness.
📢 Have feedback on the report? Share it here.

🚀 New features to boost your workflow:

• ❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.
• 📦 JS Bundle Analysis: Save yourself from yourself by tracking and limiting bundle sizes in JS merges.

[codspeed-hq]

Merging this PR will degrade performance by 15.38%

⚠️ 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

❌ 2 regressed benchmarks
✅ 96 untouched benchmarks

Warning

Please fix the performance issues or acknowledge them on CodSpeed.

Performance Changes

	Benchmark	BASE	HEAD	Efficiency
❌	bit_matrix/dense/iter_row[64]	140.8 ns	170 ns	-17.16%
❌	bit_matrix/dense/iter_row[200]	185.8 ns	215 ns	-13.57%

Tip

Investigate this regression by commenting @codspeedbot fix this regression on this PR, or directly use the CodSpeed MCP with your agent.

---

_{Comparing deps/js/npm-js-yaml-vulnerability (9d964dc) with main (271284a)}

[github-actions]

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	$$28.3 \mathrm{ms} \pm 195 \mathrm{μs}\left({\color{gray}-1.030 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$3.70 \mathrm{ms} \pm 35.8 \mathrm{μs}\left({\color{gray}-2.342 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 1002	$$13.7 \mathrm{ms} \pm 128 \mathrm{μs}\left({\color{gray}-1.591 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 3314	$$44.1 \mathrm{ms} \pm 374 \mathrm{μs}\left({\color{gray}-0.625 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$15.7 \mathrm{ms} \pm 160 \mathrm{μs}\left({\color{gray}-0.924 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 1527	$$25.5 \mathrm{ms} \pm 256 \mathrm{μs}\left({\color{gray}0.147 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 2078	$$29.2 \mathrm{ms} \pm 224 \mathrm{μs}\left({\color{gray}-1.296 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$4.28 \mathrm{ms} \pm 30.2 \mathrm{μs}\left({\color{gray}3.27 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 1033	$$14.9 \mathrm{ms} \pm 105 \mathrm{μs}\left({\color{gray}-2.333 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_medium

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 102	$$3.91 \mathrm{ms} \pm 27.8 \mathrm{μs}\left({\color{gray}1.10 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$3.14 \mathrm{ms} \pm 29.4 \mathrm{μs}\left({\color{gray}2.09 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 52	$$3.55 \mathrm{ms} \pm 23.7 \mathrm{μs}\left({\color{gray}3.50 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 269	$$5.44 \mathrm{ms} \pm 35.7 \mathrm{μs}\left({\color{gray}1.58 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$3.66 \mathrm{ms} \pm 24.1 \mathrm{μs}\left({\color{gray}-0.011 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 108	$$4.37 \mathrm{ms} \pm 33.2 \mathrm{μs}\left({\color{gray}2.55 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 133	$$4.61 \mathrm{ms} \pm 37.1 \mathrm{μs}\left({\color{gray}2.24 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.48 \mathrm{ms} \pm 19.9 \mathrm{μs}\left({\color{gray}-1.731 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 63	$$4.24 \mathrm{ms} \pm 31.8 \mathrm{μs}\left({\color{gray}0.886 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_none

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 2	$$2.67 \mathrm{ms} \pm 14.2 \mathrm{μs}\left({\color{gray}-0.445 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.55 \mathrm{ms} \pm 17.3 \mathrm{μs}\left({\color{gray}-1.507 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 2	$$2.69 \mathrm{ms} \pm 18.0 \mathrm{μs}\left({\color{gray}2.81 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 8	$$2.99 \mathrm{ms} \pm 30.0 \mathrm{μs}\left({\color{gray}3.13 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$2.71 \mathrm{ms} \pm 13.9 \mathrm{μs}\left({\color{gray}0.788 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 3	$$2.95 \mathrm{ms} \pm 19.1 \mathrm{μs}\left({\color{gray}0.962 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_small

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 52	$$3.16 \mathrm{ms} \pm 23.8 \mathrm{μs}\left({\color{gray}1.33 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.85 \mathrm{ms} \pm 18.5 \mathrm{μs}\left({\color{gray}1.59 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 26	$$3.10 \mathrm{ms} \pm 19.9 \mathrm{μs}\left({\color{gray}3.59 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 94	$$3.58 \mathrm{ms} \pm 35.4 \mathrm{μs}\left({\color{gray}1.95 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$3.05 \mathrm{ms} \pm 22.0 \mathrm{μs}\left({\color{gray}0.127 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 27	$$3.39 \mathrm{ms} \pm 28.5 \mathrm{μs}\left({\color{gray}2.73 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 66	$$3.43 \mathrm{ms} \pm 24.1 \mathrm{μs}\left({\color{gray}-1.017 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.03 \mathrm{ms} \pm 19.8 \mathrm{μs}\left({\color{gray}-0.448 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 29	$$3.43 \mathrm{ms} \pm 31.4 \mathrm{μs}\left({\color{gray}0.650 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_complete

Function	Value	Mean	Flame graphs
entity_by_id;one_depth	1 entities	$$43.4 \mathrm{ms} \pm 233 \mathrm{μs}\left({\color{gray}-2.267 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	10 entities	$$34.3 \mathrm{ms} \pm 214 \mathrm{μs}\left({\color{gray}-2.306 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	25 entities	$$37.3 \mathrm{ms} \pm 261 \mathrm{μs}\left({\color{gray}-1.737 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	5 entities	$$33.0 \mathrm{ms} \pm 271 \mathrm{μs}\left({\color{gray}-4.075 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	50 entities	$$47.1 \mathrm{ms} \pm 226 \mathrm{μs}\left({\color{red}7.00 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	1 entities	$$51.8 \mathrm{ms} \pm 271 \mathrm{μs}\left({\color{gray}-0.315 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	10 entities	$$43.4 \mathrm{ms} \pm 264 \mathrm{μs}\left({\color{gray}3.48 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	25 entities	$$96.1 \mathrm{ms} \pm 535 \mathrm{μs}\left({\color{gray}1.32 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	5 entities	$$36.4 \mathrm{ms} \pm 241 \mathrm{μs}\left({\color{gray}0.571 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	50 entities	$$283 \mathrm{ms} \pm 988 \mathrm{μs}\left({\color{lightgreen}-8.621 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	1 entities	$$11.7 \mathrm{ms} \pm 76.1 \mathrm{μs}\left({\color{gray}0.162 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	10 entities	$$11.5 \mathrm{ms} \pm 69.8 \mathrm{μs}\left({\color{gray}-3.043 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	25 entities	$$11.6 \mathrm{ms} \pm 64.7 \mathrm{μs}\left({\color{gray}0.144 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	5 entities	$$11.7 \mathrm{ms} \pm 75.8 \mathrm{μs}\left({\color{gray}-0.437 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	50 entities	$$11.2 \mathrm{ms} \pm 71.0 \mathrm{μs}\left({\color{gray}-4.090 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_linkless

Function	Value	Mean	Flame graphs
entity_by_id	1 entities	$$11.1 \mathrm{ms} \pm 66.2 \mathrm{μs}\left({\color{gray}-4.000 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10 entities	$$11.4 \mathrm{ms} \pm 78.8 \mathrm{μs}\left({\color{gray}-2.159 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	100 entities	$$12.0 \mathrm{ms} \pm 63.1 \mathrm{μs}\left({\color{gray}1.49 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	1000 entities	$$12.0 \mathrm{ms} \pm 74.6 \mathrm{μs}\left({\color{gray}-0.095 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10000 entities	$$12.0 \mathrm{ms} \pm 83.8 \mathrm{μs}\left({\color{gray}-0.768 \mathrm{\%}}\right) $$	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	$$12.1 \mathrm{ms} \pm 74.9 \mathrm{μs}\left({\color{gray}-0.175 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/book/v/1	$$12.4 \mathrm{ms} \pm 87.1 \mathrm{μs}\left({\color{gray}1.07 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/building/v/1	$$11.9 \mathrm{ms} \pm 78.9 \mathrm{μs}\left({\color{gray}-3.110 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/organization/v/1	$$12.1 \mathrm{ms} \pm 79.9 \mathrm{μs}\left({\color{gray}-2.185 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/page/v/2	$$12.4 \mathrm{ms} \pm 65.5 \mathrm{μs}\left({\color{gray}1.31 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/person/v/1	$$12.2 \mathrm{ms} \pm 77.8 \mathrm{μs}\left({\color{gray}-0.865 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/playlist/v/1	$$12.0 \mathrm{ms} \pm 74.9 \mathrm{μs}\left({\color{gray}-3.679 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/song/v/1	$$12.0 \mathrm{ms} \pm 81.6 \mathrm{μs}\left({\color{gray}-2.330 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/uk-address/v/1	$$12.5 \mathrm{ms} \pm 87.0 \mathrm{μs}\left({\color{gray}3.22 \mathrm{\%}}\right) $$	Flame Graph

representative_read_entity_type

Function	Value	Mean	Flame graphs
get_entity_type_by_id	Account ID: bf5a9ef5-dc3b-43cf-a291-6210c0321eba	$$8.80 \mathrm{ms} \pm 46.4 \mathrm{μs}\left({\color{gray}-4.855 \mathrm{\%}}\right) $$	Flame Graph

representative_read_multiple_entities

Function	Value	Mean	Flame graphs
entity_by_property	traversal_paths=0	0	$$63.5 \mathrm{ms} \pm 490 \mathrm{μs}\left({\color{gray}-3.387 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$116 \mathrm{ms} \pm 607 \mathrm{μs}\left({\color{gray}-1.597 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$71.3 \mathrm{ms} \pm 633 \mathrm{μs}\left({\color{gray}-0.588 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$81.5 \mathrm{ms} \pm 501 \mathrm{μs}\left({\color{gray}-0.729 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$89.8 \mathrm{ms} \pm 629 \mathrm{μs}\left({\color{gray}-2.510 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$95.3 \mathrm{ms} \pm 682 \mathrm{μs}\left({\color{gray}-2.731 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=0	0	$$46.4 \mathrm{ms} \pm 242 \mathrm{μs}\left({\color{gray}0.057 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$76.1 \mathrm{ms} \pm 467 \mathrm{μs}\left({\color{gray}3.30 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$51.9 \mathrm{ms} \pm 362 \mathrm{μs}\left({\color{gray}-1.943 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$61.5 \mathrm{ms} \pm 417 \mathrm{μs}\left({\color{gray}1.07 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$63.5 \mathrm{ms} \pm 342 \mathrm{μs}\left({\color{gray}0.329 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$63.9 \mathrm{ms} \pm 471 \mathrm{μs}\left({\color{gray}1.52 \mathrm{\%}}\right) $$

scenarios

Function	Value	Mean	Flame graphs
full_test	query-limited	$$129 \mathrm{ms} \pm 666 \mathrm{μs}\left({\color{red}10.1 \mathrm{\%}}\right) $$	Flame Graph
full_test	query-unlimited	$$139 \mathrm{ms} \pm 760 \mathrm{μs}\left({\color{red}6.90 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-limited	$$20.5 \mathrm{ms} \pm 130 \mathrm{μs}\left({\color{lightgreen}-18.328 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-unlimited	$$535 \mathrm{ms} \pm 1.52 \mathrm{ms}\left({\color{gray}1.17 \mathrm{\%}}\right) $$	Flame Graph