feat(zbugs): swap to whereScalar for zbugs filters#5529
Closed
feat(zbugs): swap to whereScalar for zbugs filters#5529
whereScalar for zbugs filters#5529Conversation
|
The latest updates on your projects. Learn more about Vercel for GitHub.
|
|
Bencher Report| Branch | mlaw/debug |
| Testbed | Linux |
Click to view all benchmark results
| Benchmark | File Size | Benchmark Result kilobytes (KB) (Result Δ%) | Upper Boundary kilobytes (KB) (Limit %) |
|---|---|---|---|
| zero-package.tgz | 📈 view plot 🚷 view threshold | 1,856.22 KB(+0.03%)Baseline: 1,855.58 KB | 1,892.70 KB (98.07%) |
| zero.js | 📈 view plot 🚷 view threshold | 246.57 KB(+0.16%)Baseline: 246.18 KB | 251.10 KB (98.20%) |
| zero.js.br | 📈 view plot 🚷 view threshold | 67.42 KB(+0.12%)Baseline: 67.34 KB | 68.68 KB (98.16%) |
|
| Branch | mlaw/debug |
| Testbed | self-hosted |
Click to view all benchmark results
| Benchmark | Throughput | Benchmark Result operations / second (ops/s) (Result Δ%) | Lower Boundary operations / second (ops/s) (Limit %) |
|---|---|---|---|
| 1 exists: track.exists(album) | 📈 view plot 🚷 view threshold | 13,507.57 ops/s(-1.69%)Baseline: 13,739.65 ops/s | 10,854.25 ops/s (80.36%) |
| 10 exists (AND) | 📈 view plot 🚷 view threshold | 196,120.25 ops/s(-2.29%)Baseline: 200,714.16 ops/s | 156,049.80 ops/s (79.57%) |
| 10 exists (OR) | 📈 view plot 🚷 view threshold | 3,751.74 ops/s(-4.91%)Baseline: 3,945.27 ops/s | 3,183.77 ops/s (84.86%) |
| 12 exists (AND) | 📈 view plot 🚷 view threshold | 174,451.16 ops/s(-1.73%)Baseline: 177,522.36 ops/s | 136,261.18 ops/s (78.11%) |
| 12 exists (OR) | 📈 view plot 🚷 view threshold | 3,113.99 ops/s(-6.81%)Baseline: 3,341.41 ops/s | 2,685.80 ops/s (86.25%) |
| 12 level nesting | 📈 view plot 🚷 view threshold | 2,749.67 ops/s(-5.14%)Baseline: 2,898.68 ops/s | 2,278.73 ops/s (82.87%) |
| 2 exists (AND): track.exists(album).exists(genre) | 📈 view plot 🚷 view threshold | 5,032.04 ops/s(-2.53%)Baseline: 5,162.62 ops/s | 4,144.47 ops/s (82.36%) |
| 3 exists (AND) | 📈 view plot 🚷 view threshold | 1,979.65 ops/s(-1.77%)Baseline: 2,015.39 ops/s | 1,630.23 ops/s (82.35%) |
| 3 exists (OR) | 📈 view plot 🚷 view threshold | 968.26 ops/s(-3.72%)Baseline: 1,005.64 ops/s | 806.30 ops/s (83.27%) |
| 5 exists (AND) | 📈 view plot 🚷 view threshold | 307.72 ops/s(-2.94%)Baseline: 317.04 ops/s | 253.63 ops/s (82.42%) |
| 5 exists (OR) | 📈 view plot 🚷 view threshold | 160.11 ops/s(-3.97%)Baseline: 166.72 ops/s | 131.19 ops/s (81.93%) |
| Nested 2 levels: track > album > artist | 📈 view plot 🚷 view threshold | 4,363.94 ops/s(-2.54%)Baseline: 4,477.77 ops/s | 3,521.91 ops/s (80.70%) |
| Nested 4 levels: playlist > tracks > album > artist | 📈 view plot 🚷 view threshold | 699.90 ops/s(-4.76%)Baseline: 734.89 ops/s | 585.78 ops/s (83.70%) |
| Nested with filters: track > album > artist (filtered) | 📈 view plot 🚷 view threshold | 3,617.67 ops/s(-3.44%)Baseline: 3,746.70 ops/s | 3,021.47 ops/s (83.52%) |
| planned: playlist.exists(tracks) | 📈 view plot 🚷 view threshold | 556.94 ops/s(-8.95%)Baseline: 611.70 ops/s | 504.34 ops/s (90.56%) |
| planned: track.exists(album) OR exists(genre) | 📈 view plot 🚷 view threshold | 165.25 ops/s(+1.25%)Baseline: 163.21 ops/s | 140.30 ops/s (84.90%) |
| planned: track.exists(album) where title="Big Ones" | 📈 view plot 🚷 view threshold | 7,528.39 ops/s(+0.70%)Baseline: 7,475.88 ops/s | 6,305.22 ops/s (83.75%) |
| planned: track.exists(album).exists(genre) | 📈 view plot 🚷 view threshold | 36.61 ops/s(-6.17%)Baseline: 39.02 ops/s | 32.47 ops/s (88.68%) |
| planned: track.exists(album).exists(genre) with filters | 📈 view plot 🚷 view threshold | 5,133.50 ops/s(-2.42%)Baseline: 5,260.63 ops/s | 4,343.35 ops/s (84.61%) |
| planned: track.exists(playlists) | 📈 view plot 🚷 view threshold | 3.74 ops/s(-5.23%)Baseline: 3.94 ops/s | 3.23 ops/s (86.45%) |
| unplanned: playlist.exists(tracks) | 📈 view plot 🚷 view threshold | 561.03 ops/s(-6.05%)Baseline: 597.18 ops/s | 489.77 ops/s (87.30%) |
| unplanned: track.exists(album) OR exists(genre) | 📈 view plot 🚷 view threshold | 42.56 ops/s(-4.24%)Baseline: 44.44 ops/s | 36.28 ops/s (85.25%) |
| unplanned: track.exists(album) where title="Big Ones" | 📈 view plot 🚷 view threshold | 52.07 ops/s(-6.32%)Baseline: 55.59 ops/s | 45.89 ops/s (88.13%) |
| unplanned: track.exists(album).exists(genre) | 📈 view plot 🚷 view threshold | 37.28 ops/s(-3.76%)Baseline: 38.74 ops/s | 32.10 ops/s (86.10%) |
| unplanned: track.exists(album).exists(genre) with filters | 📈 view plot 🚷 view threshold | 51.02 ops/s(-6.23%)Baseline: 54.40 ops/s | 45.01 ops/s (88.23%) |
| unplanned: track.exists(playlists) | 📈 view plot 🚷 view threshold | 3.77 ops/s(-4.06%)Baseline: 3.93 ops/s | 3.24 ops/s (85.81%) |
| zpg: all playlists | 📈 view plot 🚷 view threshold | 5.23 ops/s(-5.64%)Baseline: 5.54 ops/s | 4.81 ops/s (91.97%) |
| zql: all playlists | 📈 view plot 🚷 view threshold | 7.29 ops/s(-3.44%)Baseline: 7.55 ops/s | 5.82 ops/s (79.88%) |
| zql: edit for limited query, inside the bound | 📈 view plot 🚷 view threshold | 199,955.15 ops/s(-4.93%)Baseline: 210,318.45 ops/s | 172,419.95 ops/s (86.23%) |
| zql: edit for limited query, outside the bound | 📈 view plot 🚷 view threshold | 211,415.66 ops/s(-1.63%)Baseline: 214,913.29 ops/s | 169,804.12 ops/s (80.32%) |
| zql: push into limited query, inside the bound | 📈 view plot 🚷 view threshold | 103,081.44 ops/s(-3.74%)Baseline: 107,085.55 ops/s | 88,318.46 ops/s (85.68%) |
| zql: push into limited query, outside the bound | 📈 view plot 🚷 view threshold | 375,171.33 ops/s(-5.33%)Baseline: 396,284.28 ops/s | 296,887.81 ops/s (79.13%) |
| zql: push into unlimited query | 📈 view plot 🚷 view threshold | 312,012.08 ops/s(-3.33%)Baseline: 322,772.63 ops/s | 248,707.90 ops/s (79.71%) |
| zqlite: all playlists | 📈 view plot 🚷 view threshold | 1.69 ops/s(-2.93%)Baseline: 1.74 ops/s | 1.36 ops/s (80.40%) |
| zqlite: edit for limited query, inside the bound | 📈 view plot 🚷 view threshold | 75,165.84 ops/s(-0.73%)Baseline: 75,722.40 ops/s | 61,571.75 ops/s (81.91%) |
| zqlite: edit for limited query, outside the bound | 📈 view plot 🚷 view threshold | 74,863.61 ops/s(-0.18%)Baseline: 75,001.84 ops/s | 55,921.80 ops/s (74.70%) |
| zqlite: push into limited query, inside the bound | 📈 view plot 🚷 view threshold | 3,771.79 ops/s(-5.60%)Baseline: 3,995.74 ops/s | 3,544.77 ops/s (93.98%) |
| zqlite: push into limited query, outside the bound | 📈 view plot 🚷 view threshold | 84,412.25 ops/s(-3.27%)Baseline: 87,268.83 ops/s | 71,430.47 ops/s (84.62%) |
| zqlite: push into unlimited query | 📈 view plot 🚷 view threshold | 121,951.68 ops/s(-0.27%)Baseline: 122,283.21 ops/s | 95,193.39 ops/s (78.06%) |
|
| Branch | mlaw/debug |
| Testbed | self-hosted |
Click to view all benchmark results
| Benchmark | Throughput | Benchmark Result operations / second (ops/s) x 1e3 (Result Δ%) | Lower Boundary operations / second (ops/s) x 1e3 (Limit %) |
|---|---|---|---|
| src/client/custom.bench.ts > big schema | 📈 view plot 🚷 view threshold | 132.90 ops/s x 1e3(-2.87%)Baseline: 136.82 ops/s x 1e3 | 113.62 ops/s x 1e3 (85.50%) |
| src/client/zero.bench.ts > basics > All 1000 rows x 10 columns (numbers) | 📈 view plot 🚷 view threshold | 2.36 ops/s x 1e3(-3.17%)Baseline: 2.43 ops/s x 1e3 | 2.03 ops/s x 1e3 (86.03%) |
| src/client/zero.bench.ts > pk compare > pk = N | 📈 view plot 🚷 view threshold | 61.63 ops/s x 1e3(-1.87%)Baseline: 62.80 ops/s x 1e3 | 50.49 ops/s x 1e3 (81.92%) |
| src/client/zero.bench.ts > with filter > Lower rows 500 x 10 columns (numbers) | 📈 view plot 🚷 view threshold | 3.73 ops/s x 1e3(-0.52%)Baseline: 3.75 ops/s x 1e3 | 3.19 ops/s x 1e3 (85.52%) |
…nner Move scalar subquery rewriting from buildPipelineInternal (per-node) to buildPipeline (top-level), making it recursive through the full AST including related subqueries and correlated subquery conditions. Also update resolve-scalar-subqueries to recurse into correlated subquery conditions so nested scalar subqueries are properly resolved. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add experimental whereScalar() to the Query interface and implementation. This provides a convenience method for scalar subquery conditions using relationship definitions, complementing the lower-level cmp+scalar API. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Replace label_name_idx with a unique composite index on (projectID, name) to support scalar subquery resolution for label lookups by project. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Replace first() with a full stream consumption loop to avoid triggering early return on Take's #initialFetch assertion. The subquery AST already has limit: 1, so at most one row is produced. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add issueLabels and label relationships to the schema and update queries to use whereScalar instead of whereExists for project filtering, creator/ assignee lookups, and label filtering. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Contributor
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
2 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Make zbugs queries performant for terabugs by using
whereScalarThis allows:
Planner gets more accurate counts based on label ids resolved from label names.
Contains other fixes (to be split out):
existsbefore hitting the plan phaseissueLabel(projectID, name)whereScalarYou can review the commits in order to see each fix.