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* feat(engine): add addLinksBatch + addTimelineEntriesBatch via unnest()
Multi-row INSERT...SELECT FROM unnest() JOIN pages ON CONFLICT DO NOTHING
RETURNING 1. 4 array-typed bound parameters (links) or 5 (timeline)
regardless of batch size, sidesteps Postgres's 65535-parameter cap.
Returns count of rows actually inserted (excluding ON CONFLICT no-ops
and JOIN-dropped rows whose slugs don't exist).
Per-row addLink / addTimelineEntry signatures and SQL behavior unchanged.
All 10 existing call sites compile and behave identically.
Tests: 11 PGLite cases (empty batch, missing optionals, within-batch dedup,
JOIN drops missing slug, half-existing batch, batch of 100) + 9 E2E
postgres-engine cases against real Postgres+pgvector.
* fix(migrate): pre-create btree helper in v8 + v9 dedup; bump phaseASchema timeout
Production bug: v0.12.0 schema migration timed out at Supabase Management API's
60s ceiling on brains with 80K+ duplicate timeline rows. The DELETE...USING
self-join was O(n²) without an index on the dedup columns.
Fix: pre-create idx_links_dedup_helper / idx_timeline_dedup_helper on the
dedup columns BEFORE the DELETE, drop after. Turns O(n²) into O(n log n).
On 80K+ rows the migration completes in <1s instead of timing out.
Also bumps the v0.12.0 orchestrator's phaseASchema timeout 60s -> 600s as
belt-and-suspenders for unforeseen slowness.
Exports MIGRATIONS for structural test assertions.
Tests: 2 structural assertions (helper-index DDL must appear in v8/v9 SQL
in the right order — catches regression even at 0-row scale) + 2 behavioral
regression tests (1000-row dedup completes <5s).
* perf(extract): kill N+1 dedup pre-load; switch to batched writes
Production bug: gbrain extract hung 10+ minutes producing zero output on
47K-page brains. The pre-load loop called engine.getLinks(slug) (or
getTimeline) once per page across engine.listPages({limit: 100000}) — 47K
serial round-trips over the Supabase pooler before the first file was read.
Both engines already enforced uniqueness at the SQL layer
(UNIQUE(from, to, link_type) on links, idx_timeline_dedup on timeline_entries).
The in-memory dedup Set was redundant insurance that became the bottleneck.
Fix: delete the pre-load entirely. Buffer 100 candidates per file walk,
flush via engine.addLinksBatch / engine.addTimelineEntriesBatch. ~99% fewer
DB round-trips per re-extract.
Also fixes counter accuracy: 'created' now counts rows actually inserted
(via batch RETURNING 1 row count). Re-run on a fully-extracted brain
prints 'Done: 0 links' instead of lying.
Dry-run mode keeps a per-run dedup Set so duplicate candidates from N
markdown files print exactly once, not N times.
Batch errors are visible in BOTH json and human modes — silent loss of
100 rows is worse than per-row error visibility.
Tests: extract-fs.test.ts (idempotency + truthful counter + dry-run dedup
+ perf regression guard <2s).
* chore: bump version + changelog (v0.12.1)
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* docs: update CLAUDE.md for v0.12.1 (batch engine API, test counts)
Reflect what shipped in v0.12.1:
- New engine methods addLinksBatch + addTimelineEntriesBatch (PGLite via
unnest() + manual $N, postgres-engine via INSERT...SELECT FROM
unnest($1::text[], ...) JOIN pages ON CONFLICT DO NOTHING).
- extract.ts no longer pre-loads dedup set; candidates are buffered 100
at a time and flushed via the new batch methods.
- v0.12.0 orchestrator phaseASchema timeout bumped 60s to 600s.
- Test counts 1297 unit / 105 E2E to 1412 unit / 119 E2E.
- New test/extract-fs.test.ts covers the N+1 regression guard.
- BrainEngine method count 37/38 to 40.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
201 lines
9.0 KiB
TypeScript
201 lines
9.0 KiB
TypeScript
import { describe, test, expect, beforeAll, afterAll } from 'bun:test';
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import { LATEST_VERSION, runMigrations, MIGRATIONS } from '../src/core/migrate.ts';
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import { PGLiteEngine } from '../src/core/pglite-engine.ts';
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describe('migrate', () => {
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test('LATEST_VERSION is a number >= 1', () => {
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expect(typeof LATEST_VERSION).toBe('number');
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expect(LATEST_VERSION).toBeGreaterThanOrEqual(1);
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});
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test('runMigrations is exported and callable', async () => {
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expect(typeof runMigrations).toBe('function');
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});
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// Integration tests for actual migration execution require DATABASE_URL
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// and are covered in the E2E suite (test/e2e/mechanical.test.ts)
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});
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// ─────────────────────────────────────────────────────────────────
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// REGRESSION TESTS — migrations v8 + v9 perf on duplicate-heavy tables
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// ─────────────────────────────────────────────────────────────────
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//
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// Garry's production brain hit Supabase Management API's 60s ceiling because
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// the DELETE...USING self-join in migrations v8 + v9 was O(n²) without an
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// index on the dedup columns. The fix pre-creates a btree helper index
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// before the DELETE, then drops it. These tests guard against any future
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// change that re-introduces the missing helper index.
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//
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// Two-layer guard:
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// 1. Structural — assert the migration SQL literally contains the helper
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// CREATE INDEX + DROP INDEX (deterministic, fast, catches the regression
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// even at 0-row scale where wall-clock can't distinguish O(n²) from O(1)).
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// 2. Behavioral — populate 1000 duplicates and assert the migration completes
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// under the wall-clock cap. Sanity check at small scale; the structural
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// assertion is the real guard.
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describe('migrations v8 + v9 — structural guard for helper-index fix', () => {
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test('migration v8 SQL contains idx_links_dedup_helper CREATE+DROP around the DELETE', () => {
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const v8 = MIGRATIONS.find(m => m.version === 8);
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expect(v8).toBeDefined();
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const sql = v8!.sql;
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// The fix must: (a) create the helper btree, (b) DELETE...USING, (c) drop the helper, (d) add the unique constraint.
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// If anyone reorders or removes the helper-index lines, this fails.
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expect(sql).toContain('CREATE INDEX IF NOT EXISTS idx_links_dedup_helper');
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expect(sql).toContain('ON links(from_page_id, to_page_id, link_type)');
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expect(sql).toContain('DROP INDEX IF EXISTS idx_links_dedup_helper');
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expect(sql).toContain('DELETE FROM links a USING links b');
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expect(sql).toContain('ALTER TABLE links ADD CONSTRAINT links_from_to_type_unique');
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// Order matters: CREATE INDEX before DELETE, DROP INDEX after DELETE, before ADD CONSTRAINT.
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const createIdx = sql.indexOf('CREATE INDEX IF NOT EXISTS idx_links_dedup_helper');
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const deleteUsing = sql.indexOf('DELETE FROM links a USING links b');
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const dropIdx = sql.indexOf('DROP INDEX IF EXISTS idx_links_dedup_helper');
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const addConstraint = sql.indexOf('ALTER TABLE links ADD CONSTRAINT links_from_to_type_unique');
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expect(createIdx).toBeLessThan(deleteUsing);
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expect(deleteUsing).toBeLessThan(dropIdx);
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expect(dropIdx).toBeLessThan(addConstraint);
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});
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test('migration v9 SQL contains idx_timeline_dedup_helper CREATE+DROP around the DELETE', () => {
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const v9 = MIGRATIONS.find(m => m.version === 9);
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expect(v9).toBeDefined();
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const sql = v9!.sql;
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expect(sql).toContain('CREATE INDEX IF NOT EXISTS idx_timeline_dedup_helper');
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expect(sql).toContain('ON timeline_entries(page_id, date, summary)');
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expect(sql).toContain('DROP INDEX IF EXISTS idx_timeline_dedup_helper');
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expect(sql).toContain('DELETE FROM timeline_entries a USING timeline_entries b');
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expect(sql).toContain('CREATE UNIQUE INDEX IF NOT EXISTS idx_timeline_dedup');
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const createHelper = sql.indexOf('CREATE INDEX IF NOT EXISTS idx_timeline_dedup_helper');
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const deleteUsing = sql.indexOf('DELETE FROM timeline_entries a USING timeline_entries b');
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const dropHelper = sql.indexOf('DROP INDEX IF EXISTS idx_timeline_dedup_helper');
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const createUnique = sql.indexOf('CREATE UNIQUE INDEX IF NOT EXISTS idx_timeline_dedup');
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expect(createHelper).toBeLessThan(deleteUsing);
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expect(deleteUsing).toBeLessThan(dropHelper);
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expect(dropHelper).toBeLessThan(createUnique);
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});
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});
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describe('migrate: v8 (links_dedup) regression — must be fast on 1K duplicate rows', () => {
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let engine: PGLiteEngine;
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beforeAll(async () => {
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engine = new PGLiteEngine();
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await engine.connect({});
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await engine.initSchema();
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});
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afterAll(async () => {
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await engine.disconnect();
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});
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test('1000 duplicate links dedup completes in <5s and leaves table deduped', async () => {
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// Set up: drop the unique constraint so duplicates can be inserted, then reset
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// version so v8 re-runs. Schema-embedded.ts already has the constraint, so
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// initSchema() above set it up; explicit DROP makes the test premise valid.
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const db = (engine as any).db;
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await db.exec(`ALTER TABLE links DROP CONSTRAINT IF EXISTS links_from_to_type_unique`);
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// Two pages so the FK is satisfied
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await engine.putPage('p/from', { type: 'concept', title: 'F', compiled_truth: '', timeline: '' });
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await engine.putPage('p/to', { type: 'concept', title: 'T', compiled_truth: '', timeline: '' });
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const fromId = (await db.query(`SELECT id FROM pages WHERE slug = 'p/from'`)).rows[0].id;
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const toId = (await db.query(`SELECT id FROM pages WHERE slug = 'p/to'`)).rows[0].id;
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// Insert 1000 duplicates of the same (from, to, type) row
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for (let i = 0; i < 1000; i++) {
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await db.query(
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`INSERT INTO links (from_page_id, to_page_id, link_type, context) VALUES ($1, $2, $3, $4)`,
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[fromId, toId, 'mention', `dup-${i}`]
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);
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}
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const beforeCount = (await db.query(`SELECT COUNT(*)::int AS c FROM links`)).rows[0].c;
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expect(beforeCount).toBe(1000);
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// Reset version to 7 so v8 + v9 + v10 re-run
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await engine.setConfig('version', '7');
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// Run migrations and assert wall-clock + correctness
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const start = Date.now();
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await runMigrations(engine);
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const elapsedMs = Date.now() - start;
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expect(elapsedMs).toBeLessThan(5000);
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const afterCount = (await db.query(`SELECT COUNT(*)::int AS c FROM links`)).rows[0].c;
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expect(afterCount).toBe(1); // deduped to one row
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// Unique constraint reinstated
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const constraints = (await db.query(`
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SELECT conname FROM pg_constraint
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WHERE conrelid = 'links'::regclass AND contype = 'u'
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`)).rows;
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expect(constraints.some((c: { conname: string }) => c.conname === 'links_from_to_type_unique')).toBe(true);
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// Helper index was dropped after dedup
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const helperIdx = (await db.query(`
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SELECT indexname FROM pg_indexes
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WHERE tablename = 'links' AND indexname = 'idx_links_dedup_helper'
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`)).rows;
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expect(helperIdx.length).toBe(0);
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});
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});
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describe('migrate: v9 (timeline_dedup_index) regression — must be fast on 1K duplicate rows', () => {
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let engine: PGLiteEngine;
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beforeAll(async () => {
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engine = new PGLiteEngine();
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await engine.connect({});
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await engine.initSchema();
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});
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afterAll(async () => {
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await engine.disconnect();
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});
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test('1000 duplicate timeline entries dedup completes in <5s and leaves table deduped', async () => {
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const db = (engine as any).db;
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await db.exec(`DROP INDEX IF EXISTS idx_timeline_dedup`);
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await engine.putPage('p/timeline', { type: 'concept', title: 'TL', compiled_truth: '', timeline: '' });
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const pageId = (await db.query(`SELECT id FROM pages WHERE slug = 'p/timeline'`)).rows[0].id;
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// Insert 1000 duplicates of the same (page_id, date, summary) row
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for (let i = 0; i < 1000; i++) {
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await db.query(
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`INSERT INTO timeline_entries (page_id, date, source, summary, detail) VALUES ($1, $2::date, $3, $4, $5)`,
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[pageId, '2024-01-15', `src-${i}`, 'Founded NovaMind', `detail-${i}`]
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);
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}
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const beforeCount = (await db.query(`SELECT COUNT(*)::int AS c FROM timeline_entries`)).rows[0].c;
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expect(beforeCount).toBe(1000);
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await engine.setConfig('version', '7');
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const start = Date.now();
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await runMigrations(engine);
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const elapsedMs = Date.now() - start;
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expect(elapsedMs).toBeLessThan(5000);
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const afterCount = (await db.query(`SELECT COUNT(*)::int AS c FROM timeline_entries`)).rows[0].c;
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expect(afterCount).toBe(1);
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const uniqueIdx = (await db.query(`
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SELECT indexname FROM pg_indexes
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WHERE tablename = 'timeline_entries' AND indexname = 'idx_timeline_dedup'
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`)).rows;
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expect(uniqueIdx.length).toBe(1);
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const helperIdx = (await db.query(`
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SELECT indexname FROM pg_indexes
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WHERE tablename = 'timeline_entries' AND indexname = 'idx_timeline_dedup_helper'
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`)).rows;
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expect(helperIdx.length).toBe(0);
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});
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});
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