Tokenizer implementing normalisation as used before Nominatim 4 but using
libICU instead of the PostgreSQL module.
"""
-from typing import Optional, Sequence, List, Tuple, Mapping, Any, cast, Dict, Set, Iterable
+from typing import Optional, Sequence, List, Tuple, Mapping, Any, cast, \
+ Dict, Set, Iterable
import itertools
import json
import logging
from nominatim.data.place_info import PlaceInfo
from nominatim.tokenizer.icu_rule_loader import ICURuleLoader
from nominatim.tokenizer.place_sanitizer import PlaceSanitizer
-from nominatim.tokenizer.sanitizers.base import PlaceName
+from nominatim.data.place_name import PlaceName
from nominatim.tokenizer.icu_token_analysis import ICUTokenAnalysis
from nominatim.tokenizer.base import AbstractAnalyzer, AbstractTokenizer
LOG = logging.getLogger()
+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.
"""
class ICUTokenizer(AbstractTokenizer):
- """ This tokenizer uses libICU to covert names and queries to ASCII.
+ """ 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.
"""
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, 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')
+ self._create_lookup_indices(config, 'word')
def update_sql_functions(self, config: Configuration) -> None:
self.init_from_project(config)
- def update_statistics(self) -> None:
+ def update_statistics(self, config: Configuration) -> None:
""" Recompute frequencies for all name 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 info = info || jsonb_build_object('count', count)
- FROM word_frequencies WHERE word_id = id""")
- cur.drop_table("word_frequencies")
+ if not conn.table_exists('search_name'):
+ return
+
+ with conn.cursor() as cur:
+ LOG.info('Computing word frequencies')
+ cur.drop_table('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.drop_table('tmp_word')
+ cur.execute("""CREATE TABLE tmp_word AS
+ SELECT word_id, word_token, type, word,
+ (CASE WHEN wf.count is null THEN info
+ ELSE info || jsonb_build_object('count', wf.count)
+ END) as info
+ FROM word LEFT JOIN word_frequencies wf
+ ON word.word_id = wf.id""")
+ cur.drop_table('word_frequencies')
+
+ 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:
self.loader.make_token_analysis())
- def _install_php(self, phpdir: Path, overwrite: bool = True) -> None:
+ 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: Optional[Path], overwrite: bool = True) -> None:
""" Install the php script for the tokenizer.
"""
- assert self.loader is not None
- php_file = self.data_dir / "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')
+ 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) -> None:
self.loader.save_config_to_db(conn)
- def _init_db_tables(self, config: Configuration) -> None:
+ 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_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()
+
+
+ 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_sql_file(conn, 'tokenizer/icu_tokenizer_tables.sql')
+ 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()
+
+
+ def _create_lookup_indices(self, config: Configuration, table_name: str) -> None:
+ """ Create addtional 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 _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()
+
+
+
+
class ICUNameAnalyzer(AbstractAnalyzer):
""" The ICU analyzer uses the ICU library for splitting names.
postcode_name = place.name.strip().upper()
variant_base = None
else:
- postcode_name = analyzer.normalize(place.name)
+ postcode_name = analyzer.get_canonical_id(place)
variant_base = place.get_attr("variant")
if variant_base:
if analyzer is None:
variants = [term]
else:
- variants = analyzer.get_variants_ascii(variant)
+ variants = analyzer.compute_variants(variant)
if term not in variants:
variants.append(term)
else:
- def update_special_phrases(self, phrases: Sequence[Tuple[str, str, str, str]],
+ 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
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 databse that are no longer in the
+ """ Remove all phrases from the database that are no longer in the
new phrase list.
"""
to_delete = existing_phrases - new_phrases
result = self._cache.housenumbers.get(norm_name, result)
if result[0] is None:
with self.conn.cursor() as cur:
- cur.execute("SELECT getorcreate_hnr_id(%s)", (norm_name, ))
- result = cur.fetchone()[0], norm_name # type: ignore[no-untyped-call]
+ 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.
- norm_name = analyzer.normalize(hnr.name)
- if norm_name:
- result = self._cache.housenumbers.get(norm_name, result)
+ 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.get_variants_ascii(norm_name)
+ variants = analyzer.compute_variants(word_id)
if variants:
with self.conn.cursor() as cur:
- cur.execute("SELECT create_analyzed_hnr_id(%s, %s)",
- (norm_name, list(variants)))
- result = cur.fetchone()[0], variants[0] # type: ignore[no-untyped-call]
- self._cache.housenumbers[norm_name] = result
+ 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 retrived for the standard analyser.
+ The name is only retrieved for the standard analyser.
"""
assert self.conn is not None
norm_name = self._search_normalized(name)
for name in names:
analyzer_id = name.get_attr('analyzer')
analyzer = self.token_analysis.get_analyzer(analyzer_id)
- norm_name = analyzer.normalize(name.name)
+ word_id = analyzer.get_canonical_id(name)
if analyzer_id is None:
- token_id = norm_name
+ token_id = word_id
else:
- token_id = f'{norm_name}@{analyzer_id}'
+ token_id = f'{word_id}@{analyzer_id}'
full, part = self._cache.names.get(token_id, (None, None))
if full is None:
- variants = analyzer.get_variants_ascii(norm_name)
+ variants = analyzer.compute_variants(word_id)
if not variants:
continue
with self.conn.cursor() as cur:
cur.execute("SELECT * FROM getorcreate_full_word(%s, %s)",
(token_id, variants))
- full, part = cast(Tuple[int, List[int]],
- cur.fetchone()) # type: ignore[no-untyped-call]
+ full, part = cast(Tuple[int, List[int]], cur.fetchone())
self._cache.names[token_id] = (full, part)
postcode_name = item.name.strip().upper()
variant_base = None
else:
- postcode_name = analyzer.normalize(item.name)
+ postcode_name = analyzer.get_canonical_id(item)
variant_base = item.get_attr("variant")
if variant_base:
variants = {term}
if analyzer is not None and variant_base:
- variants.update(analyzer.get_variants_ascii(variant_base))
+ variants.update(analyzer.compute_variants(variant_base))
with self.conn.cursor() as cur:
cur.execute("SELECT create_postcode_word(%s, %s)",
self.names: Optional[str] = None
self.housenumbers: Set[str] = set()
self.housenumber_tokens: Set[int] = set()
- self.street_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
out['hnr'] = ';'.join(self.housenumbers)
out['hnr_tokens'] = self._mk_array(self.housenumber_tokens)
- if self.street_tokens:
+ if self.street_tokens is not None:
out['street'] = self._mk_array(self.street_tokens)
if self.place_tokens:
def add_street(self, tokens: Iterable[int]) -> None:
""" Add addr:street match terms.
"""
+ if self.street_tokens is None:
+ self.street_tokens = set()
self.street_tokens.update(tokens)
projects / nominatim.git / blobdiff