# 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 typing import Optional, Sequence, List, Tuple, Mapping, Any, Callable, \ cast, Dict, Set, Iterable from collections import OrderedDict import logging from pathlib import Path import re import shutil from textwrap import dedent from icu import Transliterator import psycopg2 import psycopg2.extras from nominatim.db.connection import connect, Connection from nominatim.config import Configuration from nominatim.db import properties from nominatim.db import utils as db_utils from nominatim.db.sql_preprocessor import SQLPreprocessor from nominatim.data.place_info import PlaceInfo from nominatim.errors import UsageError from nominatim.tokenizer.base import AbstractAnalyzer, AbstractTokenizer DBCFG_NORMALIZATION = "tokenizer_normalization" DBCFG_MAXWORDFREQ = "tokenizer_maxwordfreq" LOG = logging.getLogger() def create(dsn: str, data_dir: Path) -> 'LegacyTokenizer': """ Create a new instance of the tokenizer provided by this module. """ return LegacyTokenizer(dsn, data_dir) def _install_module(config_module_path: str, src_dir: Path, module_dir: Path) -> str: """ Copies the PostgreSQL normalisation module into the project directory if necessary. For historical reasons the module is saved in the '/module' subdirectory and not with the other tokenizer data. The function detects when the installation is run from the build directory. It doesn't touch the module in that case. """ # Custom module locations are simply used as is. if config_module_path: LOG.info("Using custom path for database module at '%s'", config_module_path) return config_module_path # Compatibility mode for builddir installations. if module_dir.exists() and src_dir.samefile(module_dir): LOG.info('Running from build directory. Leaving database module as is.') return str(module_dir) # In any other case install the module in the project directory. if not module_dir.exists(): module_dir.mkdir() destfile = module_dir / 'nominatim.so' shutil.copy(str(src_dir / 'nominatim.so'), str(destfile)) destfile.chmod(0o755) LOG.info('Database module installed at %s', str(destfile)) return str(module_dir) def _check_module(module_dir: str, conn: Connection) -> None: """ Try to use the PostgreSQL module to confirm that it is correctly installed and accessible from PostgreSQL. """ with conn.cursor() as cur: try: cur.execute("""CREATE FUNCTION nominatim_test_import_func(text) RETURNS text AS %s, 'transliteration' LANGUAGE c IMMUTABLE STRICT; DROP FUNCTION nominatim_test_import_func(text) """, (f'{module_dir}/nominatim.so', )) except psycopg2.DatabaseError as err: LOG.fatal("Error accessing database module: %s", err) raise UsageError("Database module cannot be accessed.") from err 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. """ def __init__(self, dsn: str, data_dir: Path) -> None: self.dsn = dsn self.data_dir = data_dir self.normalization: Optional[str] = None def init_new_db(self, config: Configuration, init_db: bool = True) -> None: """ Set up a new tokenizer for the database. This copies all necessary data in the project directory to make sure the tokenizer remains stable even over updates. """ assert config.project_dir is not None module_dir = _install_module(config.DATABASE_MODULE_PATH, config.lib_dir.module, config.project_dir / 'module') 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() if init_db: self.update_sql_functions(config) self._init_db_tables(config) def init_from_project(self, config: Configuration) -> None: """ Initialise the tokenizer from the project directory. """ assert config.project_dir is not None 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: Configuration) -> None: """ 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: Configuration) -> None: """ Reimport the SQL functions for this tokenizer. """ assert config.project_dir is not None with connect(self.dsn) as conn: max_word_freq = properties.get_property(conn, DBCFG_MAXWORDFREQ) modulepath = config.DATABASE_MODULE_PATH or \ str((config.project_dir / 'module').resolve()) sqlp = SQLPreprocessor(conn, config) sqlp.run_sql_file(conn, 'tokenizer/legacy_tokenizer.sql', max_word_freq=max_word_freq, modulepath=modulepath) def check_database(self, _: Configuration) -> Optional[str]: """ 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: Configuration) -> None: """ Initialise the project directory of an existing database for use with this tokenizer. This is a special migration function for updating existing databases to new software versions. """ assert config.project_dir is not None self.normalization = config.TERM_NORMALIZATION module_dir = _install_module(config.DATABASE_MODULE_PATH, config.lib_dir.module, config.project_dir / 'module') with connect(self.dsn) as conn: _check_module(module_dir, conn) self._save_config(conn, config) def update_statistics(self) -> None: """ 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) -> None: """ No house-keeping implemented for the legacy tokenizer. """ LOG.info("No tokenizer clean-up available.") def name_analyzer(self) -> 'LegacyNameAnalyzer': """ Create a new analyzer for tokenizing names and queries using this tokinzer. Analyzers are context managers and should be used accordingly: ``` with tokenizer.name_analyzer() as analyzer: analyser.tokenize() ``` When used outside the with construct, the caller must ensure to call the close() function before destructing the analyzer. Analyzers are not thread-safe. You need to instantiate one per thread. """ normalizer = Transliterator.createFromRules("phrase normalizer", self.normalization) return LegacyNameAnalyzer(self.dsn, normalizer) def _install_php(self, config: Configuration, overwrite: bool = True) -> None: """ 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(f"""\ None: """ Set up the word table and fill it with pre-computed word frequencies. """ with connect(self.dsn) as conn: sqlp = SQLPreprocessor(conn, config) sqlp.run_sql_file(conn, 'tokenizer/legacy_tokenizer_tables.sql') conn.commit() LOG.warning("Precomputing word tokens") db_utils.execute_file(self.dsn, config.lib_dir.data / 'words.sql') def _save_config(self, conn: Connection, config: Configuration) -> None: """ Save the configuration that needs to remain stable for the given database as database properties. """ assert self.normalization is not None properties.set_property(conn, DBCFG_NORMALIZATION, self.normalization) properties.set_property(conn, DBCFG_MAXWORDFREQ, config.MAX_WORD_FREQUENCY) class LegacyNameAnalyzer(AbstractAnalyzer): """ The legacy analyzer uses the special Postgresql module for splitting names. Each instance opens a connection to the database to request the normalization. """ def __init__(self, dsn: str, normalizer: Any): self.conn: Optional[Connection] = connect(dsn).connection self.conn.autocommit = True self.normalizer = normalizer psycopg2.extras.register_hstore(self.conn) self._cache = _TokenCache(self.conn) def close(self) -> None: """ Free all resources used by the analyzer. """ if self.conn: self.conn.close() self.conn = None def get_word_token_info(self, words: Sequence[str]) -> List[Tuple[str, str, int]]: """ Return token information for the given list of words. If a word starts with # it is assumed to be a full name otherwise is a partial name. The function returns a list of tuples with (original word, word token, word id). The function is used for testing and debugging only and not necessarily efficient. """ assert self.conn is not None with self.conn.cursor() as cur: cur.execute("""SELECT t.term, word_token, word_id FROM word, (SELECT unnest(%s::TEXT[]) as term) t WHERE word_token = (CASE WHEN left(t.term, 1) = '#' THEN ' ' || make_standard_name(substring(t.term from 2)) ELSE make_standard_name(t.term) END) and class is null and country_code is null""", (words, )) return [(r[0], r[1], r[2]) for r in cur] def normalize(self, phrase: str) -> str: """ Normalize the given phrase, i.e. remove all properties that are irrelevant for search. """ return cast(str, self.normalizer.transliterate(phrase)) def normalize_postcode(self, postcode: str) -> str: """ Convert the postcode to a standardized form. This function must yield exactly the same result as the SQL function 'token_normalized_postcode()'. """ return postcode.strip().upper() def update_postcodes_from_db(self) -> None: """ Update postcode tokens in the word table from the location_postcode table. """ assert self.conn is not None with self.conn.cursor() as cur: # This finds us the rows in location_postcode and word that are # missing in the other table. cur.execute("""SELECT * FROM (SELECT pc, word FROM (SELECT distinct(postcode) as pc FROM location_postcode) p FULL JOIN (SELECT word FROM word WHERE class ='place' and type = 'postcode') w ON pc = word) x WHERE pc is null or word is null""") to_delete = [] to_add = [] for postcode, word in cur: if postcode is None: to_delete.append(word) else: to_add.append(postcode) if to_delete: cur.execute("""DELETE FROM WORD WHERE class ='place' and type = 'postcode' and word = any(%s) """, (to_delete, )) if to_add: cur.execute("""SELECT count(create_postcode_id(pc)) FROM unnest(%s) as pc """, (to_add, )) def update_special_phrases(self, phrases: Iterable[Tuple[str, str, str, str]], should_replace: bool) -> None: """ Replace the search index for special phrases with the new phrases. """ assert self.conn is not None norm_phrases = set(((self.normalize(p[0]), p[1], p[2], p[3]) for p in phrases)) with self.conn.cursor() as cur: # Get the old phrases. existing_phrases = set() cur.execute("""SELECT word, class, type, operator FROM word WHERE class != 'place' OR (type != 'house' AND type != 'postcode')""") for label, cls, typ, oper in cur: existing_phrases.add((label, cls, typ, oper or '-')) to_add = norm_phrases - existing_phrases to_delete = existing_phrases - norm_phrases if to_add: cur.execute_values( """ INSERT INTO word (word_id, word_token, word, class, type, search_name_count, operator) (SELECT nextval('seq_word'), ' ' || make_standard_name(name), name, class, type, 0, CASE WHEN op in ('in', 'near') THEN op ELSE null END FROM (VALUES %s) as v(name, class, type, op))""", to_add) if to_delete and should_replace: cur.execute_values( """ DELETE FROM word USING (VALUES %s) as v(name, in_class, in_type, op) WHERE word = name and class = in_class and type = in_type and ((op = '-' and operator is null) or op = operator)""", to_delete) LOG.info("Total phrases: %s. Added: %s. Deleted: %s", len(norm_phrases), len(to_add), len(to_delete)) def add_country_names(self, country_code: str, names: Mapping[str, str]) -> None: """ Add names for the given country to the search index. """ assert self.conn is not None with self.conn.cursor() as cur: cur.execute( """INSERT INTO word (word_id, word_token, country_code) (SELECT nextval('seq_word'), lookup_token, %s FROM (SELECT DISTINCT ' ' || make_standard_name(n) as lookup_token FROM unnest(%s)n) y WHERE NOT EXISTS(SELECT * FROM word WHERE word_token = lookup_token and country_code = %s)) """, (country_code, list(names.values()), country_code)) def process_place(self, place: PlaceInfo) -> Mapping[str, Any]: """ Determine tokenizer information about the given place. Returns a JSON-serialisable structure that will be handed into the database via the token_info field. """ assert self.conn is not None token_info = _TokenInfo(self._cache) names = place.name if names: token_info.add_names(self.conn, names) if place.is_country(): assert place.country_code is not None self.add_country_names(place.country_code, names) address = place.address if address: self._process_place_address(token_info, address) return token_info.data def _process_place_address(self, token_info: '_TokenInfo', address: Mapping[str, str]) -> None: assert self.conn is not None hnrs = [] addr_terms = [] for key, value in address.items(): if key == 'postcode': # Make sure the normalized postcode is present in the word table. if re.search(r'[:,;]', value) is None: norm_pc = self.normalize_postcode(value) token_info.set_postcode(norm_pc) self._cache.add_postcode(self.conn, norm_pc) elif key in ('housenumber', 'streetnumber', 'conscriptionnumber'): hnrs.append(value) elif key == 'street': token_info.add_street(self.conn, value) elif key == 'place': token_info.add_place(self.conn, value) elif not key.startswith('_') \ and key not in ('country', 'full', 'inclusion'): addr_terms.append((key, value)) if hnrs: token_info.add_housenumbers(self.conn, hnrs) if addr_terms: token_info.add_address_terms(self.conn, addr_terms) class _TokenInfo: """ Collect token information to be sent back to the database. """ def __init__(self, cache: '_TokenCache') -> None: self.cache = cache self.data: Dict[str, Any] = {} def add_names(self, conn: Connection, names: Mapping[str, str]) -> None: """ Add token information for the names of the place. """ with conn.cursor() as cur: # Create the token IDs for all names. self.data['names'] = cur.scalar("SELECT make_keywords(%s)::text", (names, )) def add_housenumbers(self, conn: Connection, hnrs: Sequence[str]) -> None: """ Extract housenumber information from the address. """ if len(hnrs) == 1: token = self.cache.get_housenumber(hnrs[0]) if token is not None: self.data['hnr_tokens'] = token self.data['hnr'] = hnrs[0] return # split numbers if necessary simple_list: List[str] = [] for hnr in hnrs: simple_list.extend((x.strip() for x in re.split(r'[;,]', hnr))) if len(simple_list) > 1: simple_list = list(set(simple_list)) with conn.cursor() as cur: cur.execute("SELECT * FROM create_housenumbers(%s)", (simple_list, )) result = cur.fetchone() assert result is not None self.data['hnr_tokens'], self.data['hnr'] = result def set_postcode(self, postcode: str) -> None: """ Set or replace the postcode token with the given value. """ self.data['postcode'] = postcode def add_street(self, conn: Connection, street: str) -> None: """ Add addr:street match terms. """ def _get_street(name: str) -> List[int]: with conn.cursor() as cur: return cast(List[int], 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: Connection, place: str) -> None: """ Add addr:place search and match terms. """ def _get_place(name: str) -> Tuple[List[int], List[int]]: with conn.cursor() as cur: cur.execute("""SELECT make_keywords(hstore('name' , %s))::text, word_ids_from_name(%s)::text""", (name, name)) return cast(Tuple[List[int], List[int]], cur.fetchone()) self.data['place_search'], self.data['place_match'] = \ self.cache.places.get(place, _get_place) def add_address_terms(self, conn: Connection, terms: Sequence[Tuple[str, str]]) -> None: """ Add additional address terms. """ def _get_address_term(name: str) -> Tuple[List[int], List[int]]: with conn.cursor() as cur: cur.execute("""SELECT addr_ids_from_name(%s)::text, word_ids_from_name(%s)::text""", (name, name)) return cast(Tuple[List[int], List[int]], 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: int = 128): self.data: 'OrderedDict[str, Any]' = OrderedDict() self.maxsize = maxsize def get(self, key: str, generator: Callable[[str], Any]) -> Any: """ 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: Connection): # 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: Dict[str, str] = {str(r[0]): r[1] for r in cur} # For postcodes remember the ones that have already been added self.postcodes: Set[str] = set() def get_housenumber(self, number: str) -> Optional[str]: """ Get a housenumber token from the cache. """ return self._cached_housenumbers.get(number) def add_postcode(self, conn: Connection, postcode: str) -> None: """ 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)