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fix(server): face search migration sometimes failing (#10827) 

* turn it off and back on

* handle missing smart search embedding column

* handle missing face embedding column

* simplify

* Revert "simplify"

This reverts commit 8322af0baf.

* fix migration
pull/10842/head
Mert 2024-07-03 22:02:43 +07:00 committed by GitHub
parent 2b8942026c
commit 0b88bef157
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GPG Key ID: B5690EEEBB952194
1 changed files with 43 additions and 18 deletions
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61
server/src/migrations/1718486162779-AddFaceSearchRelation.ts
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@ -9,25 +9,50 @@ export class AddFaceSearchRelation1718486162779 implements MigrationInterface {
await queryRunner.query(`SET vectors.pgvector_compatibility=on`);
}
const hasEmbeddings = async (tableName: string): Promise<boolean> => {
const columns = await queryRunner.query(
`SELECT column_name as name
FROM information_schema.columns
WHERE table_name = '${tableName}'`);
return columns.some((column: { name: string }) => column.name === 'embedding');
}
const hasAssetEmbeddings = await hasEmbeddings('smart_search');
if (!hasAssetEmbeddings) {
await queryRunner.query(`TRUNCATE smart_search`);
await queryRunner.query(`ALTER TABLE smart_search ADD COLUMN IF NOT EXISTS embedding vector(512) NOT NULL`);
}
await queryRunner.query(`
CREATE TABLE face_search (
"faceId" uuid PRIMARY KEY REFERENCES asset_faces(id) ON DELETE CASCADE,
embedding vector(512) NOT NULL )`);
CREATE TABLE face_search (
"faceId" uuid PRIMARY KEY REFERENCES asset_faces(id) ON DELETE CASCADE,
embedding vector(512) NOT NULL )`);
await queryRunner.query(`ALTER TABLE face_search ALTER COLUMN embedding SET STORAGE EXTERNAL`);
await queryRunner.query(`ALTER TABLE smart_search ALTER COLUMN embedding SET STORAGE EXTERNAL`);
await queryRunner.query(`
INSERT INTO face_search("faceId", embedding)
SELECT id, embedding
FROM asset_faces faces`);
const hasFaceEmbeddings = await hasEmbeddings('asset_faces')
if (hasFaceEmbeddings) {
await queryRunner.query(`
INSERT INTO face_search("faceId", embedding)
SELECT id, embedding
FROM asset_faces faces`);
}
await queryRunner.query(`ALTER TABLE asset_faces DROP COLUMN IF EXISTS embedding`);
await queryRunner.query(`ALTER TABLE asset_faces DROP COLUMN "embedding"`);
await queryRunner.query(`ALTER TABLE face_search ALTER COLUMN embedding SET DATA TYPE real[]`);
await queryRunner.query(`ALTER TABLE face_search ALTER COLUMN embedding SET DATA TYPE vector(512)`);
await queryRunner.query(`
CREATE INDEX IF NOT EXISTS clip_index ON smart_search
USING hnsw (embedding vector_cosine_ops)
WITH (ef_construction = 300, m = 16)`);
await queryRunner.query(`
CREATE INDEX face_index ON face_search
USING hnsw (embedding vector_cosine_ops)
WITH (ef_construction = 300, m = 16)`);
CREATE INDEX face_index ON face_search
USING hnsw (embedding vector_cosine_ops)
WITH (ef_construction = 300, m = 16)`);
}
public async down(queryRunner: QueryRunner): Promise<void> {
@ -40,15 +65,15 @@ export class AddFaceSearchRelation1718486162779 implements MigrationInterface {
await queryRunner.query(`ALTER TABLE face_search ALTER COLUMN embedding SET STORAGE DEFAULT`);
await queryRunner.query(`ALTER TABLE smart_search ALTER COLUMN embedding SET STORAGE DEFAULT`);
await queryRunner.query(`
UPDATE asset_faces
SET embedding = fs.embedding
FROM face_search fs
WHERE id = fs."faceId"`);
UPDATE asset_faces
SET embedding = fs.embedding
FROM face_search fs
WHERE id = fs."faceId"`);
await queryRunner.query(`DROP TABLE face_search`);
await queryRunner.query(`
CREATE INDEX face_index ON asset_faces
USING hnsw (embedding vector_cosine_ops)
WITH (ef_construction = 300, m = 16)`);
CREATE INDEX face_index ON asset_faces
USING hnsw (embedding vector_cosine_ops)
WITH (ef_construction = 300, m = 16)`);
}
}