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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.`)
}
}