+# 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 but using
libICU instead of the PostgreSQL module.
"""
-from collections import Counter
+from typing import Optional, Sequence, List, Tuple, Mapping, Any, cast, \
+ Dict, Set, Iterable
import itertools
import json
import logging
-import re
+from pathlib import Path
from textwrap import dedent
-from nominatim.db.connection import connect
-from nominatim.db.properties import set_property, get_property
+from nominatim.db.connection import connect, Connection, Cursor
+from nominatim.config import Configuration
from nominatim.db.utils import CopyBuffer
from nominatim.db.sql_preprocessor import SQLPreprocessor
+from nominatim.data.place_info import PlaceInfo
from nominatim.tokenizer.icu_rule_loader import ICURuleLoader
-from nominatim.tokenizer.icu_name_processor import ICUNameProcessor, ICUNameProcessorRules
+from nominatim.tokenizer.place_sanitizer import PlaceSanitizer
+from nominatim.data.place_name import PlaceName
+from nominatim.tokenizer.icu_token_analysis import ICUTokenAnalysis
from nominatim.tokenizer.base import AbstractAnalyzer, AbstractTokenizer
-DBCFG_MAXWORDFREQ = "tokenizer_maxwordfreq"
DBCFG_TERM_NORMALIZATION = "tokenizer_term_normalization"
LOG = logging.getLogger()
-def create(dsn, data_dir):
+WORD_TYPES =(('country_names', 'C'),
+ ('postcodes', 'P'),
+ ('full_word', 'W'),
+ ('housenumbers', 'H'))
+
+def create(dsn: str, data_dir: Path) -> 'ICUTokenizer':
""" Create a new instance of the tokenizer provided by this module.
"""
- return LegacyICUTokenizer(dsn, data_dir)
+ return ICUTokenizer(dsn, data_dir)
-class LegacyICUTokenizer(AbstractTokenizer):
- """ This tokenizer uses libICU to covert names and queries to ASCII.
+class ICUTokenizer(AbstractTokenizer):
+ """ This tokenizer uses libICU to convert names and queries to ASCII.
Otherwise it uses the same algorithms and data structures as the
normalization routines in Nominatim 3.
"""
- def __init__(self, dsn, data_dir):
+ def __init__(self, dsn: str, data_dir: Path) -> None:
self.dsn = dsn
self.data_dir = data_dir
- self.naming_rules = None
- self.term_normalization = None
- self.max_word_frequency = None
+ self.loader: Optional[ICURuleLoader] = None
- def init_new_db(self, config, init_db=True):
+ 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.
"""
- loader = ICURuleLoader(config.load_sub_configuration('icu_tokenizer.yaml',
- config='TOKENIZER_CONFIG'))
- self.naming_rules = ICUNameProcessorRules(loader=loader)
- self.term_normalization = config.TERM_NORMALIZATION
- self.max_word_frequency = config.MAX_WORD_FREQUENCY
+ self.loader = ICURuleLoader(config)
- self._install_php(config.lib_dir.php)
- self._save_config(config)
+ self._install_php(config.lib_dir.php, overwrite=True)
+ self._save_config()
if init_db:
self.update_sql_functions(config)
- self._init_db_tables(config)
+ self._setup_db_tables(config)
+ self._create_base_indices(config, 'word')
- def init_from_project(self):
+ def init_from_project(self, config: Configuration) -> None:
""" Initialise the tokenizer from the project directory.
"""
+ self.loader = ICURuleLoader(config)
+
with connect(self.dsn) as conn:
- self.naming_rules = ICUNameProcessorRules(conn=conn)
- self.term_normalization = get_property(conn, DBCFG_TERM_NORMALIZATION)
- self.max_word_frequency = get_property(conn, DBCFG_MAXWORDFREQ)
+ self.loader.load_config_from_db(conn)
+ self._install_php(config.lib_dir.php, overwrite=False)
- def finalize_import(self, _):
+
+ def finalize_import(self, config: Configuration) -> None:
""" Do any required postprocessing to make the tokenizer data ready
for use.
"""
+ self._create_lookup_indices(config, 'word')
- def update_sql_functions(self, config):
+ def update_sql_functions(self, config: Configuration) -> None:
""" Reimport the SQL functions for this tokenizer.
"""
with connect(self.dsn) as conn:
- max_word_freq = get_property(conn, DBCFG_MAXWORDFREQ)
sqlp = SQLPreprocessor(conn, config)
- sqlp.run_sql_file(conn, 'tokenizer/icu_tokenizer.sql',
- max_word_freq=max_word_freq)
+ sqlp.run_sql_file(conn, 'tokenizer/icu_tokenizer.sql')
- def check_database(self):
+ def check_database(self, config: Configuration) -> None:
""" Check that the tokenizer is set up correctly.
"""
- self.init_from_project()
+ # Will throw an error if there is an issue.
+ self.init_from_project(config)
+
+
+ def update_statistics(self, config: Configuration, threads: int = 2) -> None:
+ """ Recompute frequencies for all name words.
+ """
+ with connect(self.dsn) as conn:
+ if not conn.table_exists('search_name'):
+ return
+
+ with conn.cursor() as cur:
+ cur.execute('ANALYSE search_name')
+ if threads > 1:
+ cur.execute('SET max_parallel_workers_per_gather TO %s',
+ (min(threads, 6),))
+
+ if conn.server_version_tuple() < (12, 0):
+ LOG.info('Computing word frequencies')
+ cur.drop_table('word_frequencies')
+ cur.drop_table('addressword_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)')
+ cur.execute("""CREATE TEMP TABLE addressword_frequencies AS
+ SELECT unnest(nameaddress_vector) as id, count(*)
+ FROM search_name GROUP BY id""")
+ cur.execute('CREATE INDEX ON addressword_frequencies(id)')
+ cur.execute("""CREATE OR REPLACE FUNCTION word_freq_update(wid INTEGER,
+ INOUT info JSONB)
+ AS $$
+ DECLARE rec RECORD;
+ BEGIN
+ IF info is null THEN
+ info = '{}'::jsonb;
+ END IF;
+ FOR rec IN SELECT count FROM word_frequencies WHERE id = wid
+ LOOP
+ info = info || jsonb_build_object('count', rec.count);
+ END LOOP;
+ FOR rec IN SELECT count FROM addressword_frequencies WHERE id = wid
+ LOOP
+ info = info || jsonb_build_object('addr_count', rec.count);
+ END LOOP;
+ IF info = '{}'::jsonb THEN
+ info = null;
+ END IF;
+ END;
+ $$ LANGUAGE plpgsql IMMUTABLE;
+ """)
+ LOG.info('Update word table with recomputed frequencies')
+ cur.drop_table('tmp_word')
+ cur.execute("""CREATE TABLE tmp_word AS
+ SELECT word_id, word_token, type, word,
+ word_freq_update(word_id, info) as info
+ FROM word
+ """)
+ cur.drop_table('word_frequencies')
+ cur.drop_table('addressword_frequencies')
+ else:
+ LOG.info('Computing word frequencies')
+ cur.drop_table('word_frequencies')
+ cur.execute("""
+ CREATE TEMP TABLE word_frequencies AS
+ WITH word_freq AS MATERIALIZED (
+ SELECT unnest(name_vector) as id, count(*)
+ FROM search_name GROUP BY id),
+ addr_freq AS MATERIALIZED (
+ SELECT unnest(nameaddress_vector) as id, count(*)
+ FROM search_name GROUP BY id)
+ SELECT coalesce(a.id, w.id) as id,
+ (CASE WHEN w.count is null THEN '{}'::JSONB
+ ELSE jsonb_build_object('count', w.count) END
+ ||
+ CASE WHEN a.count is null THEN '{}'::JSONB
+ ELSE jsonb_build_object('addr_count', a.count) END) as info
+ FROM word_freq w FULL JOIN addr_freq a ON a.id = w.id;
+ """)
+ cur.execute('CREATE UNIQUE INDEX ON word_frequencies(id) INCLUDE(info)')
+ cur.execute('ANALYSE word_frequencies')
+ LOG.info('Update word table with recomputed frequencies')
+ cur.drop_table('tmp_word')
+ cur.execute("""CREATE TABLE tmp_word AS
+ SELECT word_id, word_token, type, word,
+ (CASE WHEN wf.info is null THEN word.info
+ ELSE coalesce(word.info, '{}'::jsonb) || wf.info
+ END) as info
+ FROM word LEFT JOIN word_frequencies wf
+ ON word.word_id = wf.id
+ """)
+ cur.drop_table('word_frequencies')
+
+ with conn.cursor() as cur:
+ cur.execute('SET max_parallel_workers_per_gather TO 0')
+
+ sqlp = SQLPreprocessor(conn, config)
+ sqlp.run_string(conn,
+ 'GRANT SELECT ON tmp_word TO "{{config.DATABASE_WEBUSER}}"')
+ conn.commit()
+ self._create_base_indices(config, 'tmp_word')
+ self._create_lookup_indices(config, 'tmp_word')
+ self._move_temporary_word_table('tmp_word')
+
+
+
+ def _cleanup_housenumbers(self) -> None:
+ """ Remove unused house numbers.
+ """
+ with connect(self.dsn) as conn:
+ if not conn.table_exists('search_name'):
+ return
+ with conn.cursor(name="hnr_counter") as cur:
+ cur.execute("""SELECT DISTINCT word_id, coalesce(info->>'lookup', word_token)
+ FROM word
+ WHERE type = 'H'
+ AND NOT EXISTS(SELECT * FROM search_name
+ WHERE ARRAY[word.word_id] && name_vector)
+ AND (char_length(coalesce(word, word_token)) > 6
+ OR coalesce(word, word_token) not similar to '\\d+')
+ """)
+ candidates = {token: wid for wid, token in cur}
+ with conn.cursor(name="hnr_counter") as cur:
+ cur.execute("""SELECT housenumber FROM placex
+ WHERE housenumber is not null
+ AND (char_length(housenumber) > 6
+ OR housenumber not similar to '\\d+')
+ """)
+ for row in cur:
+ for hnr in row[0].split(';'):
+ candidates.pop(hnr, None)
+ LOG.info("There are %s outdated housenumbers.", len(candidates))
+ LOG.debug("Outdated housenumbers: %s", candidates.keys())
+ if candidates:
+ with conn.cursor() as cur:
+ cur.execute("""DELETE FROM word WHERE word_id = any(%s)""",
+ (list(candidates.values()), ))
+ conn.commit()
- if self.naming_rules is None:
- return "Configuration for tokenizer 'icu' are missing."
- return None
+
+ def update_word_tokens(self) -> None:
+ """ Remove unused tokens.
+ """
+ LOG.warning("Cleaning up housenumber tokens.")
+ self._cleanup_housenumbers()
+ LOG.warning("Tokenizer house-keeping done.")
- def name_analyzer(self):
+ def name_analyzer(self) -> 'ICUNameAnalyzer':
""" Create a new analyzer for tokenizing names and queries
using this tokinzer. Analyzers are context managers and should
be used accordingly:
Analyzers are not thread-safe. You need to instantiate one per thread.
"""
- return LegacyICUNameAnalyzer(self.dsn, ICUNameProcessor(self.naming_rules))
+ assert self.loader is not None
+ return ICUNameAnalyzer(self.dsn, self.loader.make_sanitizer(),
+ self.loader.make_token_analysis())
+
+
+ def most_frequent_words(self, conn: Connection, num: int) -> List[str]:
+ """ Return a list of the `num` most frequent full words
+ in the database.
+ """
+ with conn.cursor() as cur:
+ cur.execute("""SELECT word, sum((info->>'count')::int) as count
+ FROM word WHERE type = 'W'
+ GROUP BY word
+ ORDER BY count DESC LIMIT %s""", (num,))
+ return list(s[0].split('@')[0] for s in cur)
- def _install_php(self, phpdir):
+ def _install_php(self, phpdir: Optional[Path], overwrite: bool = True) -> None:
""" Install the php script for the tokenizer.
"""
- php_file = self.data_dir / "tokenizer.php"
- php_file.write_text(dedent(f"""\
- <?php
- @define('CONST_Max_Word_Frequency', {self.max_word_frequency});
- @define('CONST_Term_Normalization_Rules', "{self.term_normalization}");
- @define('CONST_Transliteration', "{self.naming_rules.search_rules}");
- require_once('{phpdir}/tokenizer/icu_tokenizer.php');"""))
+ if phpdir is not None:
+ assert self.loader is not None
+ php_file = self.data_dir / "tokenizer.php"
+
+ if not php_file.exists() or overwrite:
+ php_file.write_text(dedent(f"""\
+ <?php
+ @define('CONST_Max_Word_Frequency', 10000000);
+ @define('CONST_Term_Normalization_Rules', "{self.loader.normalization_rules}");
+ @define('CONST_Transliteration', "{self.loader.get_search_rules()}");
+ require_once('{phpdir}/tokenizer/icu_tokenizer.php');"""), encoding='utf-8')
- def _save_config(self, config):
+ def _save_config(self) -> None:
""" Save the configuration that needs to remain stable for the given
database as database properties.
"""
+ assert self.loader is not None
with connect(self.dsn) as conn:
- self.naming_rules.save_rules(conn)
+ self.loader.save_config_to_db(conn)
- set_property(conn, DBCFG_MAXWORDFREQ, config.MAX_WORD_FREQUENCY)
- set_property(conn, DBCFG_TERM_NORMALIZATION, self.term_normalization)
-
- def _init_db_tables(self, config):
+ def _setup_db_tables(self, config: Configuration) -> None:
""" Set up the word table and fill it with pre-computed word
frequencies.
"""
with connect(self.dsn) as conn:
+ with conn.cursor() as cur:
+ cur.drop_table('word')
sqlp = SQLPreprocessor(conn, config)
- sqlp.run_sql_file(conn, 'tokenizer/icu_tokenizer_tables.sql')
+ sqlp.run_string(conn, """
+ CREATE TABLE word (
+ word_id INTEGER,
+ word_token text NOT NULL,
+ type text NOT NULL,
+ word text,
+ info jsonb
+ ) {{db.tablespace.search_data}};
+ GRANT SELECT ON word TO "{{config.DATABASE_WEBUSER}}";
+
+ DROP SEQUENCE IF EXISTS seq_word;
+ CREATE SEQUENCE seq_word start 1;
+ GRANT SELECT ON seq_word to "{{config.DATABASE_WEBUSER}}";
+ """)
conn.commit()
- LOG.warning("Precomputing word tokens")
- # get partial words and their frequencies
- words = self._count_partial_terms(conn)
-
- # copy them back into the word table
- with CopyBuffer() as copystr:
- for term, cnt in words.items():
- copystr.add('w', term, json.dumps({'count': cnt}))
+ def _create_base_indices(self, config: Configuration, table_name: str) -> 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_string(conn,
+ """CREATE INDEX idx_{{table_name}}_word_token ON {{table_name}}
+ USING BTREE (word_token) {{db.tablespace.search_index}}""",
+ table_name=table_name)
+ for name, ctype in WORD_TYPES:
+ sqlp.run_string(conn,
+ """CREATE INDEX idx_{{table_name}}_{{idx_name}} ON {{table_name}}
+ USING BTREE (word) {{db.tablespace.address_index}}
+ WHERE type = '{{column_type}}'
+ """,
+ table_name=table_name, idx_name=name,
+ column_type=ctype)
+ conn.commit()
- with conn.cursor() as cur:
- copystr.copy_out(cur, 'word',
- columns=['type', 'word_token', 'info'])
- cur.execute("""UPDATE word SET word_id = nextval('seq_word')
- WHERE word_id is null and type = 'w'""")
+ def _create_lookup_indices(self, config: Configuration, table_name: str) -> None:
+ """ Create additional indexes used when running the API.
+ """
+ with connect(self.dsn) as conn:
+ sqlp = SQLPreprocessor(conn, config)
+ # Index required for details lookup.
+ sqlp.run_string(conn, """
+ CREATE INDEX IF NOT EXISTS idx_{{table_name}}_word_id
+ ON {{table_name}} USING BTREE (word_id) {{db.tablespace.search_index}}
+ """,
+ table_name=table_name)
conn.commit()
- def _count_partial_terms(self, conn):
- """ Count the partial terms from the names in the place table.
- """
- words = Counter()
- name_proc = ICUNameProcessor(self.naming_rules)
- with conn.cursor(name="words") as cur:
- cur.execute(""" SELECT v, count(*) FROM
- (SELECT svals(name) as v FROM place)x
- WHERE length(v) < 75 GROUP BY v""")
+ def _move_temporary_word_table(self, old: str) -> None:
+ """ Rename all tables and indexes used by the tokenizer.
+ """
+ with connect(self.dsn) as conn:
+ with conn.cursor() as cur:
+ cur.drop_table('word')
+ cur.execute(f"ALTER TABLE {old} RENAME TO word")
+ for idx in ('word_token', 'word_id'):
+ cur.execute(f"""ALTER INDEX idx_{old}_{idx}
+ RENAME TO idx_word_{idx}""")
+ for name, _ in WORD_TYPES:
+ cur.execute(f"""ALTER INDEX idx_{old}_{name}
+ RENAME TO idx_word_{name}""")
+ conn.commit()
- for name, cnt in cur:
- terms = set()
- for word in name_proc.get_variants_ascii(name_proc.get_normalized(name)):
- if ' ' in word:
- terms.update(word.split())
- for term in terms:
- words[term] += cnt
- return words
-class LegacyICUNameAnalyzer(AbstractAnalyzer):
- """ The legacy analyzer uses the ICU library for splitting names.
+class ICUNameAnalyzer(AbstractAnalyzer):
+ """ The ICU analyzer uses the ICU library for splitting names.
Each instance opens a connection to the database to request the
normalization.
"""
- def __init__(self, dsn, name_proc):
- self.conn = connect(dsn).connection
+ def __init__(self, dsn: str, sanitizer: PlaceSanitizer,
+ token_analysis: ICUTokenAnalysis) -> None:
+ self.conn: Optional[Connection] = connect(dsn).connection
self.conn.autocommit = True
- self.name_processor = name_proc
+ self.sanitizer = sanitizer
+ self.token_analysis = token_analysis
self._cache = _TokenCache()
- def close(self):
+ def close(self) -> None:
""" Free all resources used by the analyzer.
"""
if self.conn:
self.conn = None
- def get_word_token_info(self, words):
+ def _search_normalized(self, name: str) -> str:
+ """ Return the search token transliteration of the given name.
+ """
+ return cast(str, self.token_analysis.search.transliterate(name)).strip()
+
+
+ def _normalized(self, name: str) -> str:
+ """ Return the normalized version of the given name with all
+ non-relevant information removed.
+ """
+ return cast(str, self.token_analysis.normalizer.transliterate(name)).strip()
+
+
+ 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 is used for testing and debugging only
and not necessarily efficient.
"""
+ assert self.conn is not None
full_tokens = {}
partial_tokens = {}
for word in words:
if word.startswith('#'):
- full_tokens[word] = self.name_processor.get_search_normalized(word[1:])
+ full_tokens[word] = self._search_normalized(word[1:])
else:
- partial_tokens[word] = self.name_processor.get_search_normalized(word)
+ partial_tokens[word] = self._search_normalized(word)
with self.conn.cursor() as cur:
cur.execute("""SELECT word_token, word_id
+ [(k, v, part_ids.get(v, None)) for k, v in partial_tokens.items()]
- @staticmethod
- def normalize_postcode(postcode):
+ 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
return postcode.strip().upper()
- def _make_standard_hnr(self, hnr):
- """ Create a normalised version of a housenumber.
-
- This function takes minor shortcuts on transliteration.
- """
- return self.name_processor.get_search_normalized(hnr)
-
- def update_postcodes_from_db(self):
+ def update_postcodes_from_db(self) -> None:
""" Update postcode tokens in the word table from the location_postcode
table.
"""
- to_delete = []
+ assert self.conn is not None
+ analyzer = self.token_analysis.analysis.get('@postcode')
+
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 type = 'P') w
- ON pc = word) x
- WHERE pc is null or word is null""")
-
- with CopyBuffer() as copystr:
- for postcode, word in cur:
- if postcode is None:
- to_delete.append(word)
- else:
- copystr.add(self.name_processor.get_search_normalized(postcode),
- 'P', postcode)
-
- if to_delete:
- cur.execute("""DELETE FROM WORD
- WHERE type ='P' and word = any(%s)
- """, (to_delete, ))
-
- copystr.copy_out(cur, 'word',
- columns=['word_token', 'type', 'word'])
-
-
- def update_special_phrases(self, phrases, should_replace):
+ # First get all postcode names currently in the word table.
+ cur.execute("SELECT DISTINCT word FROM word WHERE type = 'P'")
+ word_entries = set((entry[0] for entry in cur))
+
+ # Then compute the required postcode names from the postcode table.
+ needed_entries = set()
+ cur.execute("SELECT country_code, postcode FROM location_postcode")
+ for cc, postcode in cur:
+ info = PlaceInfo({'country_code': cc,
+ 'class': 'place', 'type': 'postcode',
+ 'address': {'postcode': postcode}})
+ address = self.sanitizer.process_names(info)[1]
+ for place in address:
+ if place.kind == 'postcode':
+ if analyzer is None:
+ postcode_name = place.name.strip().upper()
+ variant_base = None
+ else:
+ postcode_name = analyzer.get_canonical_id(place)
+ variant_base = place.get_attr("variant")
+
+ if variant_base:
+ needed_entries.add(f'{postcode_name}@{variant_base}')
+ else:
+ needed_entries.add(postcode_name)
+ break
+
+ # Now update the word table.
+ self._delete_unused_postcode_words(word_entries - needed_entries)
+ self._add_missing_postcode_words(needed_entries - word_entries)
+
+ def _delete_unused_postcode_words(self, tokens: Iterable[str]) -> None:
+ assert self.conn is not None
+ if tokens:
+ with self.conn.cursor() as cur:
+ cur.execute("DELETE FROM word WHERE type = 'P' and word = any(%s)",
+ (list(tokens), ))
+
+ def _add_missing_postcode_words(self, tokens: Iterable[str]) -> None:
+ assert self.conn is not None
+ if not tokens:
+ return
+
+ analyzer = self.token_analysis.analysis.get('@postcode')
+ terms = []
+
+ for postcode_name in tokens:
+ if '@' in postcode_name:
+ term, variant = postcode_name.split('@', 2)
+ term = self._search_normalized(term)
+ if analyzer is None:
+ variants = [term]
+ else:
+ variants = analyzer.compute_variants(variant)
+ if term not in variants:
+ variants.append(term)
+ else:
+ variants = [self._search_normalized(postcode_name)]
+ terms.append((postcode_name, variants))
+
+ if terms:
+ with self.conn.cursor() as cur:
+ cur.execute_values("""SELECT create_postcode_word(pc, var)
+ FROM (VALUES %s) AS v(pc, var)""",
+ terms)
+
+
+
+
+ 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.
If `should_replace` is True, then the previous set of will be
completely replaced. Otherwise the phrases are added to the
already existing ones.
"""
- norm_phrases = set(((self.name_processor.get_normalized(p[0]), p[1], p[2], p[3])
+ assert self.conn is not None
+ norm_phrases = set(((self._normalized(p[0]), p[1], p[2], p[3])
for p in phrases))
with self.conn.cursor() as cur:
len(norm_phrases), added, deleted)
- def _add_special_phrases(self, cursor, new_phrases, existing_phrases):
+ def _add_special_phrases(self, cursor: Cursor,
+ new_phrases: Set[Tuple[str, str, str, str]],
+ existing_phrases: Set[Tuple[str, str, str, str]]) -> int:
""" Add all phrases to the database that are not yet there.
"""
to_add = new_phrases - existing_phrases
added = 0
with CopyBuffer() as copystr:
for word, cls, typ, oper in to_add:
- term = self.name_processor.get_search_normalized(word)
+ term = self._search_normalized(word)
if term:
copystr.add(term, 'S', word,
json.dumps({'class': cls, 'type': typ,
return added
- @staticmethod
- def _remove_special_phrases(cursor, new_phrases, existing_phrases):
- """ Remove all phrases from the databse that are no longer in the
+ def _remove_special_phrases(self, cursor: Cursor,
+ new_phrases: Set[Tuple[str, str, str, str]],
+ existing_phrases: Set[Tuple[str, str, str, str]]) -> int:
+ """ Remove all phrases from the database that are no longer in the
new phrase list.
"""
to_delete = existing_phrases - new_phrases
return len(to_delete)
- def add_country_names(self, country_code, names):
- """ Add names for the given country to the search index.
+ def add_country_names(self, country_code: str, names: Mapping[str, str]) -> None:
+ """ Add default names for the given country to the search index.
+ """
+ # Make sure any name preprocessing for country names applies.
+ info = PlaceInfo({'name': names, 'country_code': country_code,
+ 'rank_address': 4, 'class': 'boundary',
+ 'type': 'administrative'})
+ self._add_country_full_names(country_code,
+ self.sanitizer.process_names(info)[0],
+ internal=True)
+
+
+ def _add_country_full_names(self, country_code: str, names: Sequence[PlaceName],
+ internal: bool = False) -> None:
+ """ Add names for the given country from an already sanitized
+ name list.
"""
+ assert self.conn is not None
word_tokens = set()
- for name in self._compute_full_names(names):
- norm_name = self.name_processor.get_search_normalized(name)
+ for name in names:
+ norm_name = self._search_normalized(name.name)
if norm_name:
word_tokens.add(norm_name)
with self.conn.cursor() as cur:
# Get existing names
- cur.execute("""SELECT word_token FROM word
- WHERE type = 'C' and word = %s""",
+ cur.execute("""SELECT word_token, coalesce(info ? 'internal', false) as is_internal
+ FROM word
+ WHERE type = 'C' and word = %s""",
(country_code, ))
- word_tokens.difference_update((t[0] for t in cur))
+ # internal/external names
+ existing_tokens: Dict[bool, Set[str]] = {True: set(), False: set()}
+ for word in cur:
+ existing_tokens[word[1]].add(word[0])
+
+ # Delete names that no longer exist.
+ gone_tokens = existing_tokens[internal] - word_tokens
+ if internal:
+ gone_tokens.update(existing_tokens[False] & word_tokens)
+ if gone_tokens:
+ cur.execute("""DELETE FROM word
+ USING unnest(%s) as token
+ WHERE type = 'C' and word = %s
+ and word_token = token""",
+ (list(gone_tokens), country_code))
# Only add those names that are not yet in the list.
- if word_tokens:
- cur.execute("""INSERT INTO word (word_token, type, word)
- (SELECT token, 'C', %s
- FROM unnest(%s) as token)
- """, (country_code, list(word_tokens)))
-
- # No names are deleted at the moment.
- # If deletion is made possible, then the static names from the
- # initial 'country_name' table should be kept.
-
-
- def process_place(self, place):
+ new_tokens = word_tokens - existing_tokens[True]
+ if not internal:
+ new_tokens -= existing_tokens[False]
+ if new_tokens:
+ if internal:
+ sql = """INSERT INTO word (word_token, type, word, info)
+ (SELECT token, 'C', %s, '{"internal": "yes"}'
+ FROM unnest(%s) as token)
+ """
+ else:
+ sql = """INSERT INTO word (word_token, type, word)
+ (SELECT token, 'C', %s
+ FROM unnest(%s) as token)
+ """
+ cur.execute(sql, (country_code, list(new_tokens)))
+
+
+ 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
+ Returns a JSON-serializable structure that will be handed into
the database via the token_info field.
"""
- token_info = _TokenInfo(self._cache)
+ token_info = _TokenInfo()
- names = place.get('name')
+ names, address = self.sanitizer.process_names(place)
if names:
- fulls, partials = self._compute_name_tokens(names)
+ token_info.set_names(*self._compute_name_tokens(names))
- token_info.add_names(fulls, partials)
+ if place.is_country():
+ assert place.country_code is not None
+ self._add_country_full_names(place.country_code, names)
- country_feature = place.get('country_feature')
- if country_feature and re.fullmatch(r'[A-Za-z][A-Za-z]', country_feature):
- self.add_country_names(country_feature.lower(), names)
-
- address = place.get('address')
if address:
self._process_place_address(token_info, address)
- return token_info.data
+ return token_info.to_dict()
+
+
+ def _process_place_address(self, token_info: '_TokenInfo',
+ address: Sequence[PlaceName]) -> None:
+ for item in address:
+ if item.kind == 'postcode':
+ token_info.set_postcode(self._add_postcode(item))
+ elif item.kind == 'housenumber':
+ token_info.add_housenumber(*self._compute_housenumber_token(item))
+ elif item.kind == 'street':
+ token_info.add_street(self._retrieve_full_tokens(item.name))
+ elif item.kind == 'place':
+ if not item.suffix:
+ token_info.add_place(itertools.chain(*self._compute_name_tokens([item])))
+ elif not item.kind.startswith('_') and not item.suffix and \
+ item.kind not in ('country', 'full', 'inclusion'):
+ token_info.add_address_term(item.kind,
+ itertools.chain(*self._compute_name_tokens([item])))
+
+
+ def _compute_housenumber_token(self, hnr: PlaceName) -> Tuple[Optional[int], Optional[str]]:
+ """ Normalize the housenumber and return the word token and the
+ canonical form.
+ """
+ assert self.conn is not None
+ analyzer = self.token_analysis.analysis.get('@housenumber')
+ result: Tuple[Optional[int], Optional[str]] = (None, None)
+ if analyzer is None:
+ # When no custom analyzer is set, simply normalize and transliterate
+ norm_name = self._search_normalized(hnr.name)
+ if norm_name:
+ result = self._cache.housenumbers.get(norm_name, result)
+ if result[0] is None:
+ with self.conn.cursor() as cur:
+ hid = cur.scalar("SELECT getorcreate_hnr_id(%s)", (norm_name, ))
+
+ result = hid, norm_name
+ self._cache.housenumbers[norm_name] = result
+ else:
+ # Otherwise use the analyzer to determine the canonical name.
+ # Per convention we use the first variant as the 'lookup name', the
+ # name that gets saved in the housenumber field of the place.
+ word_id = analyzer.get_canonical_id(hnr)
+ if word_id:
+ result = self._cache.housenumbers.get(word_id, result)
+ if result[0] is None:
+ variants = analyzer.compute_variants(word_id)
+ if variants:
+ with self.conn.cursor() as cur:
+ hid = cur.scalar("SELECT create_analyzed_hnr_id(%s, %s)",
+ (word_id, list(variants)))
+ result = hid, variants[0]
+ self._cache.housenumbers[word_id] = result
+
+ return result
+
+
+ def _retrieve_full_tokens(self, name: str) -> List[int]:
+ """ Get the full name token for the given name, if it exists.
+ The name is only retrieved for the standard analyser.
+ """
+ assert self.conn is not None
+ norm_name = self._search_normalized(name)
- def _process_place_address(self, token_info, address):
- hnrs = []
- addr_terms = []
- for key, value in address.items():
- if key == 'postcode':
- self._add_postcode(value)
- elif key in ('housenumber', 'streetnumber', 'conscriptionnumber'):
- hnrs.append(value)
- elif key == 'street':
- token_info.add_street(*self._compute_name_tokens({'name': value}))
- elif key == 'place':
- token_info.add_place(*self._compute_name_tokens({'name': value}))
- elif not key.startswith('_') and \
- key not in ('country', 'full'):
- addr_terms.append((key, *self._compute_name_tokens({'name': value})))
+ # return cached if possible
+ if norm_name in self._cache.fulls:
+ return self._cache.fulls[norm_name]
- if hnrs:
- hnrs = self._split_housenumbers(hnrs)
- token_info.add_housenumbers(self.conn, [self._make_standard_hnr(n) for n in hnrs])
+ with self.conn.cursor() as cur:
+ cur.execute("SELECT word_id FROM word WHERE word_token = %s and type = 'W'",
+ (norm_name, ))
+ full = [row[0] for row in cur]
+
+ self._cache.fulls[norm_name] = full
- if addr_terms:
- token_info.add_address_terms(addr_terms)
+ return full
- def _compute_name_tokens(self, names):
+ def _compute_name_tokens(self, names: Sequence[PlaceName]) -> Tuple[Set[int], Set[int]]:
""" Computes the full name and partial name tokens for the given
dictionary of names.
"""
- full_names = self._compute_full_names(names)
- full_tokens = set()
- partial_tokens = set()
+ assert self.conn is not None
+ full_tokens: Set[int] = set()
+ partial_tokens: Set[int] = set()
+
+ for name in names:
+ analyzer_id = name.get_attr('analyzer')
+ analyzer = self.token_analysis.get_analyzer(analyzer_id)
+ word_id = analyzer.get_canonical_id(name)
+ if analyzer_id is None:
+ token_id = word_id
+ else:
+ token_id = f'{word_id}@{analyzer_id}'
- for name in full_names:
- norm_name = self.name_processor.get_normalized(name)
- full, part = self._cache.names.get(norm_name, (None, None))
+ full, part = self._cache.names.get(token_id, (None, None))
if full is None:
- variants = self.name_processor.get_variants_ascii(norm_name)
+ variants = analyzer.compute_variants(word_id)
if not variants:
continue
with self.conn.cursor() as cur:
- cur.execute("SELECT (getorcreate_full_word(%s, %s)).*",
- (norm_name, variants))
- full, part = cur.fetchone()
+ cur.execute("SELECT * FROM getorcreate_full_word(%s, %s)",
+ (token_id, variants))
+ full, part = cast(Tuple[int, List[int]], cur.fetchone())
- self._cache.names[norm_name] = (full, part)
+ self._cache.names[token_id] = (full, part)
+
+ assert part is not None
full_tokens.add(full)
partial_tokens.update(part)
return full_tokens, partial_tokens
- @staticmethod
- def _compute_full_names(names):
- """ Return the set of all full name word ids to be used with the
- given dictionary of names.
- """
- full_names = set()
- for name in (n.strip() for ns in names.values() for n in re.split('[;,]', ns)):
- if name:
- full_names.add(name)
-
- brace_idx = name.find('(')
- if brace_idx >= 0:
- full_names.add(name[:brace_idx].strip())
-
- return full_names
-
-
- def _add_postcode(self, postcode):
+ def _add_postcode(self, item: PlaceName) -> Optional[str]:
""" Make sure the normalized postcode is present in the word table.
"""
- if re.search(r'[:,;]', postcode) is None:
- postcode = self.normalize_postcode(postcode)
+ assert self.conn is not None
+ analyzer = self.token_analysis.analysis.get('@postcode')
- if postcode not in self._cache.postcodes:
- term = self.name_processor.get_search_normalized(postcode)
- if not term:
- return
+ if analyzer is None:
+ postcode_name = item.name.strip().upper()
+ variant_base = None
+ else:
+ postcode_name = analyzer.get_canonical_id(item)
+ variant_base = item.get_attr("variant")
- with self.conn.cursor() as cur:
- # no word_id needed for postcodes
- cur.execute("""INSERT INTO word (word_token, type, word)
- (SELECT %s, 'P', pc FROM (VALUES (%s)) as v(pc)
- WHERE NOT EXISTS
- (SELECT * FROM word
- WHERE type = 'P' and word = pc))
- """, (term, postcode))
- self._cache.postcodes.add(postcode)
-
-
- @staticmethod
- def _split_housenumbers(hnrs):
- if len(hnrs) > 1 or ',' in hnrs[0] or ';' in hnrs[0]:
- # split numbers if necessary
- simple_list = []
- for hnr in hnrs:
- simple_list.extend((x.strip() for x in re.split(r'[;,]', hnr)))
-
- if len(simple_list) > 1:
- hnrs = list(set(simple_list))
- else:
- hnrs = simple_list
+ if variant_base:
+ postcode = f'{postcode_name}@{variant_base}'
+ else:
+ postcode = postcode_name
- return hnrs
+ if postcode not in self._cache.postcodes:
+ term = self._search_normalized(postcode_name)
+ if not term:
+ return None
+ variants = {term}
+ if analyzer is not None and variant_base:
+ variants.update(analyzer.compute_variants(variant_base))
+ with self.conn.cursor() as cur:
+ cur.execute("SELECT create_postcode_word(%s, %s)",
+ (postcode, list(variants)))
+ self._cache.postcodes.add(postcode)
+
+ return postcode_name
class _TokenInfo:
""" Collect token information to be sent back to the database.
"""
- def __init__(self, cache):
- self._cache = cache
- self.data = {}
+ def __init__(self) -> None:
+ self.names: Optional[str] = None
+ self.housenumbers: Set[str] = set()
+ self.housenumber_tokens: Set[int] = set()
+ self.street_tokens: Optional[Set[int]] = None
+ self.place_tokens: Set[int] = set()
+ self.address_tokens: Dict[str, str] = {}
+ self.postcode: Optional[str] = None
+
+
+ def _mk_array(self, tokens: Iterable[Any]) -> str:
+ return f"{{{','.join((str(s) for s in tokens))}}}"
+
+
+ def to_dict(self) -> Dict[str, Any]:
+ """ Return the token information in database importable format.
+ """
+ out: Dict[str, Any] = {}
+
+ if self.names:
+ out['names'] = self.names
+
+ if self.housenumbers:
+ out['hnr'] = ';'.join(self.housenumbers)
+ out['hnr_tokens'] = self._mk_array(self.housenumber_tokens)
+
+ if self.street_tokens is not None:
+ out['street'] = self._mk_array(self.street_tokens)
+
+ if self.place_tokens:
+ out['place'] = self._mk_array(self.place_tokens)
+
+ if self.address_tokens:
+ out['addr'] = self.address_tokens
- @staticmethod
- def _mk_array(tokens):
- return '{%s}' % ','.join((str(s) for s in tokens))
+ if self.postcode:
+ out['postcode'] = self.postcode
+ return out
- def add_names(self, fulls, partials):
+
+ def set_names(self, fulls: Iterable[int], partials: Iterable[int]) -> None:
""" Adds token information for the normalised names.
"""
- self.data['names'] = self._mk_array(itertools.chain(fulls, partials))
+ self.names = self._mk_array(itertools.chain(fulls, partials))
- def add_housenumbers(self, conn, hnrs):
+ def add_housenumber(self, token: Optional[int], hnr: Optional[str]) -> None:
""" Extract housenumber information from a list of normalised
housenumbers.
"""
- self.data['hnr_tokens'] = self._mk_array(self._cache.get_hnr_tokens(conn, hnrs))
- self.data['hnr'] = ';'.join(hnrs)
+ if token:
+ assert hnr is not None
+ self.housenumbers.add(hnr)
+ self.housenumber_tokens.add(token)
- def add_street(self, fulls, _):
+ def add_street(self, tokens: Iterable[int]) -> None:
""" Add addr:street match terms.
"""
- if fulls:
- self.data['street'] = self._mk_array(fulls)
+ if self.street_tokens is None:
+ self.street_tokens = set()
+ self.street_tokens.update(tokens)
- def add_place(self, fulls, partials):
+ def add_place(self, tokens: Iterable[int]) -> None:
""" Add addr:place search and match terms.
"""
- if fulls:
- self.data['place_search'] = self._mk_array(itertools.chain(fulls, partials))
- self.data['place_match'] = self._mk_array(fulls)
+ self.place_tokens.update(tokens)
- def add_address_terms(self, terms):
+ def add_address_term(self, key: str, partials: Iterable[int]) -> None:
""" Add additional address terms.
"""
- tokens = {}
-
- for key, fulls, partials in terms:
- if fulls:
- tokens[key] = [self._mk_array(itertools.chain(fulls, partials)),
- self._mk_array(fulls)]
+ array = self._mk_array(partials)
+ if len(array) > 2:
+ self.address_tokens[key] = array
- if tokens:
- self.data['addr'] = tokens
+ def set_postcode(self, postcode: Optional[str]) -> None:
+ """ Set the postcode to the given one.
+ """
+ self.postcode = postcode
class _TokenCache:
This cache is not thread-safe and needs to be instantiated per
analyzer.
"""
- def __init__(self):
- self.names = {}
- self.postcodes = set()
- self.housenumbers = {}
-
-
- def get_hnr_tokens(self, conn, terms):
- """ Get token ids for a list of housenumbers, looking them up in the
- database if necessary. `terms` is an iterable of normalized
- housenumbers.
- """
- tokens = []
- askdb = []
-
- for term in terms:
- token = self.housenumbers.get(term)
- if token is None:
- askdb.append(term)
- else:
- tokens.append(token)
-
- if askdb:
- with conn.cursor() as cur:
- cur.execute("SELECT nr, getorcreate_hnr_id(nr) FROM unnest(%s) as nr",
- (askdb, ))
- for term, tid in cur:
- self.housenumbers[term] = tid
- tokens.append(tid)
-
- return tokens
+ def __init__(self) -> None:
+ self.names: Dict[str, Tuple[int, List[int]]] = {}
+ self.partials: Dict[str, int] = {}
+ self.fulls: Dict[str, List[int]] = {}
+ self.postcodes: Set[str] = set()
+ self.housenumbers: Dict[str, Tuple[Optional[int], Optional[str]]] = {}
projects / nominatim.git / blobdiff