X-Git-Url: https://git.openstreetmap.org./nominatim.git/blobdiff_plain/d711f5a81e6d02926cefe5c9c94bcf1d8f375b11..3d58254462289cad257cb96d60b7a24f8e7fc8da:/nominatim/tokenizer/legacy_tokenizer.py diff --git a/nominatim/tokenizer/legacy_tokenizer.py b/nominatim/tokenizer/legacy_tokenizer.py index 73a911b4..3b8f7569 100644 --- a/nominatim/tokenizer/legacy_tokenizer.py +++ b/nominatim/tokenizer/legacy_tokenizer.py @@ -1,10 +1,19 @@ +# SPDX-License-Identifier: GPL-2.0-only +# +# This file is part of Nominatim. (https://nominatim.org) +# +# Copyright (C) 2022 by the Nominatim developer community. +# For a full list of authors see the git log. """ Tokenizer implementing normalisation as used before Nominatim 4. """ +from collections import OrderedDict import logging import re import shutil +from textwrap import dedent +from icu import Transliterator import psycopg2 import psycopg2.extras @@ -13,6 +22,7 @@ from nominatim.db import properties from nominatim.db import utils as db_utils from nominatim.db.sql_preprocessor import SQLPreprocessor from nominatim.errors import UsageError +from nominatim.tokenizer.base import AbstractAnalyzer, AbstractTokenizer DBCFG_NORMALIZATION = "tokenizer_normalization" DBCFG_MAXWORDFREQ = "tokenizer_maxwordfreq" @@ -73,7 +83,7 @@ def _check_module(module_dir, conn): raise UsageError("Database module cannot be accessed.") from err -class LegacyTokenizer: +class LegacyTokenizer(AbstractTokenizer): """ The legacy tokenizer uses a special PostgreSQL module to normalize names and queries. The tokenizer thus implements normalization through calls to the database. @@ -85,7 +95,7 @@ class LegacyTokenizer: self.normalization = None - def init_new_db(self, config): + def init_new_db(self, config, init_db=True): """ Set up a new tokenizer for the database. This copies all necessary data in the project directory to make @@ -97,21 +107,39 @@ class LegacyTokenizer: self.normalization = config.TERM_NORMALIZATION + self._install_php(config, overwrite=True) + with connect(self.dsn) as conn: _check_module(module_dir, conn) self._save_config(conn, config) conn.commit() - self.update_sql_functions(config) - self._init_db_tables(config) + if init_db: + self.update_sql_functions(config) + self._init_db_tables(config) - def init_from_project(self): + def init_from_project(self, config): """ Initialise the tokenizer from the project directory. """ with connect(self.dsn) as conn: self.normalization = properties.get_property(conn, DBCFG_NORMALIZATION) + if not (config.project_dir / 'module' / 'nominatim.so').exists(): + _install_module(config.DATABASE_MODULE_PATH, + config.lib_dir.module, + config.project_dir / 'module') + + self._install_php(config, overwrite=False) + + def finalize_import(self, config): + """ Do any required postprocessing to make the tokenizer data ready + for use. + """ + with connect(self.dsn) as conn: + sqlp = SQLPreprocessor(conn, config) + sqlp.run_sql_file(conn, 'tokenizer/legacy_tokenizer_indices.sql') + def update_sql_functions(self, config): """ Reimport the SQL functions for this tokenizer. @@ -126,6 +154,33 @@ class LegacyTokenizer: modulepath=modulepath) + def check_database(self, _): + """ Check that the tokenizer is set up correctly. + """ + hint = """\ + The Postgresql extension nominatim.so was not correctly loaded. + + Error: {error} + + Hints: + * Check the output of the CMmake/make installation step + * Does nominatim.so exist? + * Does nominatim.so exist on the database server? + * Can nominatim.so be accessed by the database user? + """ + with connect(self.dsn) as conn: + with conn.cursor() as cur: + try: + out = cur.scalar("SELECT make_standard_name('a')") + except psycopg2.Error as err: + return hint.format(error=str(err)) + + if out != 'a': + return hint.format(error='Unexpected result for make_standard_name()') + + return None + + def migrate_database(self, config): """ Initialise the project directory of an existing database for use with this tokenizer. @@ -133,6 +188,7 @@ class LegacyTokenizer: This is a special migration function for updating existing databases to new software versions. """ + self.normalization = config.TERM_NORMALIZATION module_dir = _install_module(config.DATABASE_MODULE_PATH, config.lib_dir.module, config.project_dir / 'module') @@ -142,6 +198,32 @@ class LegacyTokenizer: self._save_config(conn, config) + def update_statistics(self): + """ Recompute the frequency of full words. + """ + with connect(self.dsn) as conn: + if conn.table_exists('search_name'): + with conn.cursor() as cur: + cur.drop_table("word_frequencies") + LOG.info("Computing word frequencies") + cur.execute("""CREATE TEMP TABLE word_frequencies AS + SELECT unnest(name_vector) as id, count(*) + FROM search_name GROUP BY id""") + cur.execute("CREATE INDEX ON word_frequencies(id)") + LOG.info("Update word table with recomputed frequencies") + cur.execute("""UPDATE word SET search_name_count = count + FROM word_frequencies + WHERE word_token like ' %' and word_id = id""") + cur.drop_table("word_frequencies") + conn.commit() + + + def update_word_tokens(self): + """ No house-keeping implemented for the legacy tokenizer. + """ + LOG.info("No tokenizer clean-up available.") + + def name_analyzer(self): """ Create a new analyzer for tokenizing names and queries using this tokinzer. Analyzers are context managers and should @@ -157,7 +239,23 @@ class LegacyTokenizer: Analyzers are not thread-safe. You need to instantiate one per thread. """ - return LegacyNameAnalyzer(self.dsn) + normalizer = Transliterator.createFromRules("phrase normalizer", + self.normalization) + return LegacyNameAnalyzer(self.dsn, normalizer) + + + def _install_php(self, config, overwrite=True): + """ Install the php script for the tokenizer. + """ + php_file = self.data_dir / "tokenizer.php" + + if not php_file.exists() or overwrite: + php_file.write_text(dedent("""\ + 1: + simple_list = list(set(simple_list)) + + with conn.cursor() as cur: + cur.execute("SELECT * FROM create_housenumbers(%s)", (simple_list, )) + self.data['hnr_tokens'], self.data['hnr'] = cur.fetchone() + + + def add_street(self, conn, street): + """ Add addr:street match terms. + """ + def _get_street(name): + with conn.cursor() as cur: + return cur.scalar("SELECT word_ids_from_name(%s)::text", (name, )) + + tokens = self.cache.streets.get(street, _get_street) + if tokens: + self.data['street'] = tokens + + + def add_place(self, conn, place): + """ Add addr:place search and match terms. + """ + def _get_place(name): + with conn.cursor() as cur: + cur.execute("""SELECT make_keywords(hstore('name' , %s))::text, + word_ids_from_name(%s)::text""", + (name, name)) + return cur.fetchone() + + self.data['place_search'], self.data['place_match'] = \ + self.cache.places.get(place, _get_place) + + + def add_address_terms(self, conn, terms): + """ Add additional address terms. + """ + def _get_address_term(name): + with conn.cursor() as cur: + cur.execute("""SELECT addr_ids_from_name(%s)::text, + word_ids_from_name(%s)::text""", + (name, name)) + return cur.fetchone() + + tokens = {} + for key, value in terms: + items = self.cache.address_terms.get(value, _get_address_term) + if items[0] or items[1]: + tokens[key] = items + + if tokens: + self.data['addr'] = tokens + + +class _LRU: + """ Least recently used cache that accepts a generator function to + produce the item when there is a cache miss. + """ + + def __init__(self, maxsize=128, init_data=None): + self.data = init_data or OrderedDict() + self.maxsize = maxsize + if init_data is not None and len(init_data) > maxsize: + self.maxsize = len(init_data) + + def get(self, key, generator): + """ Get the item with the given key from the cache. If nothing + is found in the cache, generate the value through the + generator function and store it in the cache. + """ + value = self.data.get(key) + if value is not None: + self.data.move_to_end(key) + else: + value = generator(key) + if len(self.data) >= self.maxsize: + self.data.popitem(last=False) + self.data[key] = value + + return value + + +class _TokenCache: + """ Cache for token information to avoid repeated database queries. + + This cache is not thread-safe and needs to be instantiated per + analyzer. + """ + def __init__(self, conn): + # various LRU caches + self.streets = _LRU(maxsize=256) + self.places = _LRU(maxsize=128) + self.address_terms = _LRU(maxsize=1024) + + # Lookup houseunumbers up to 100 and cache them + with conn.cursor() as cur: + cur.execute("""SELECT i, ARRAY[getorcreate_housenumber_id(i::text)]::text + FROM generate_series(1, 100) as i""") + self._cached_housenumbers = {str(r[0]): r[1] for r in cur} + + # For postcodes remember the ones that have already been added + self.postcodes = set() + + def get_housenumber(self, number): + """ Get a housenumber token from the cache. + """ + return self._cached_housenumbers.get(number) + + + def add_postcode(self, conn, postcode): + """ Make sure the given postcode is in the database. + """ + if postcode not in self.postcodes: + with conn.cursor() as cur: + cur.execute('SELECT create_postcode_id(%s)', (postcode, )) + self.postcodes.add(postcode)