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