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const tsquery = require('pg-tsquery')() const stream = require('stream') const Promise = require('bluebird') const pipeline = Promise.promisify(stream.pipeline)
/* global WIKI */
module.exports = { async activate() { if (WIKI.config.db.type !== 'postgres') { throw new WIKI.Error.SearchActivationFailed('Must use PostgreSQL database to activate this engine!') } }, async deactivate() { WIKI.logger.info(`(SEARCH/POSTGRES) Dropping index tables...`) await WIKI.models.knex.schema.dropTable('pagesWords') await WIKI.models.knex.schema.dropTable('pagesVector') WIKI.logger.info(`(SEARCH/POSTGRES) Index tables have been dropped.`) }, /** * INIT */ async init() { WIKI.logger.info(`(SEARCH/POSTGRES) Initializing...`)
// -> Create Search Index
const indexExists = await WIKI.models.knex.schema.hasTable('pagesVector') if (!indexExists) { WIKI.logger.info(`(SEARCH/POSTGRES) Creating Pages Vector table...`) await WIKI.models.knex.schema.createTable('pagesVector', table => { table.increments() table.string('path') table.string('locale') table.string('title') table.string('description') table.specificType('tokens', 'TSVECTOR') table.text('content') }) } // -> Create Words Index
const wordsExists = await WIKI.models.knex.schema.hasTable('pagesWords') if (!wordsExists) { WIKI.logger.info(`(SEARCH/POSTGRES) Creating Words Suggestion Index...`) await WIKI.models.knex.raw(`
CREATE TABLE "pagesWords" AS SELECT word FROM ts_stat( 'SELECT to_tsvector(''simple'', "title") || to_tsvector(''simple'', "description") || to_tsvector(''simple'', "content") FROM "pagesVector"' )`)
await WIKI.models.knex.raw('CREATE EXTENSION IF NOT EXISTS pg_trgm') await WIKI.models.knex.raw(`CREATE INDEX "pageWords_idx" ON "pagesWords" USING GIN (word gin_trgm_ops)`) }
WIKI.logger.info(`(SEARCH/POSTGRES) Initialization completed.`) }, /** * QUERY * * @param {String} q Query * @param {Object} opts Additional options */ async query(q, opts) { try { let suggestions = [] const results = await WIKI.models.knex.raw(`
SELECT id, path, locale, title, description FROM "pagesVector", to_tsquery(?) query WHERE query @@ "tokens" ORDER BY ts_rank(tokens, query) DESC `, [tsquery(q)])
if (results.rows.length < 5) { const suggestResults = await WIKI.models.knex.raw(`SELECT word, word <-> ? AS rank FROM "pagesWords" WHERE similarity(word, ?) > 0.2 ORDER BY rank LIMIT 5;`, [q, q]) suggestions = suggestResults.rows.map(r => r.word) } return { results: results.rows, suggestions, totalHits: results.rows.length } } catch (err) { WIKI.logger.warn('Search Engine Error:') WIKI.logger.warn(err) } }, /** * CREATE * * @param {Object} page Page to create */ async created(page) { await WIKI.models.knex.raw(`
INSERT INTO "pagesVector" (path, locale, title, description, "tokens") VALUES ( ?, ?, ?, ?, (setweight(to_tsvector('${this.config.dictLanguage}', ?), 'A') || setweight(to_tsvector('${this.config.dictLanguage}', ?), 'B') || setweight(to_tsvector('${this.config.dictLanguage}', ?), 'C')) ) `, [page.path, page.localeCode, page.title, page.description, page.title, page.description, page.safeContent])
}, /** * UPDATE * * @param {Object} page Page to update */ async updated(page) { await WIKI.models.knex.raw(`
UPDATE "pagesVector" SET title = ?, description = ?, tokens = (setweight(to_tsvector('${this.config.dictLanguage}', ?), 'A') || setweight(to_tsvector('${this.config.dictLanguage}', ?), 'B') || setweight(to_tsvector('${this.config.dictLanguage}', ?), 'C')) WHERE path = ? AND locale = ? `, [page.title, page.description, page.title, page.description, page.safeContent, page.path, page.localeCode])
}, /** * DELETE * * @param {Object} page Page to delete */ async deleted(page) { await WIKI.models.knex('pagesVector').where({ locale: page.localeCode, path: page.path }).del().limit(1) }, /** * RENAME * * @param {Object} page Page to rename */ async renamed(page) { await WIKI.models.knex('pagesVector').where({ locale: page.localeCode, path: page.sourcePath }).update({ locale: page.localeCode, path: page.destinationPath }) }, /** * REBUILD INDEX */ async rebuild() { WIKI.logger.info(`(SEARCH/POSTGRES) Rebuilding Index...`) await WIKI.models.knex('pagesVector').truncate() await WIKI.models.knex('pagesWords').truncate()
await pipeline( WIKI.models.knex.column('path', 'localeCode', 'title', 'description', 'render').select().from('pages').where({ isPublished: true, isPrivate: false }).stream(), new stream.Transform({ objectMode: true, transform: async (page, enc, cb) => { const content = WIKI.models.pages.cleanHTML(page.render) await WIKI.models.knex.raw(`
INSERT INTO "pagesVector" (path, locale, title, description, "tokens", content) VALUES ( ?, ?, ?, ?, (setweight(to_tsvector('${this.config.dictLanguage}', ?), 'A') || setweight(to_tsvector('${this.config.dictLanguage}', ?), 'B') || setweight(to_tsvector('${this.config.dictLanguage}', ?), 'C')), ? ) `, [page.path, page.localeCode, page.title, page.description, page.title, page.description, content, content])
cb() } }) )
await WIKI.models.knex.raw(`
INSERT INTO "pagesWords" (word) SELECT word FROM ts_stat( 'SELECT to_tsvector(''simple'', "title") || to_tsvector(''simple'', "description") || to_tsvector(''simple'', "content") FROM "pagesVector"' ) `)
WIKI.logger.info(`(SEARCH/POSTGRES) Index rebuilt successfully.`) } }
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