forked from hans/Nominatim
249 lines
9.4 KiB
Python
249 lines
9.4 KiB
Python
# SPDX-License-Identifier: GPL-3.0-or-later
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#
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# This file is part of Nominatim. (https://nominatim.org)
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#
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# Copyright (C) 2025 by the Nominatim developer community.
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# For a full list of authors see the git log.
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"""
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Functions for bringing auxiliary data in the database up-to-date.
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"""
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from typing import MutableSequence, Tuple, Any, Mapping, Sequence, List
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import csv
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import gzip
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import logging
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from pathlib import Path
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from psycopg import sql as pysql
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from ..config import Configuration
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from ..db.connection import Connection, connect, drop_tables
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from ..db.utils import execute_file
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from ..db.sql_preprocessor import SQLPreprocessor
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LOG = logging.getLogger()
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OSM_TYPE = {'N': 'node', 'W': 'way', 'R': 'relation'}
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def _add_address_level_rows_from_entry(rows: MutableSequence[Tuple[Any, ...]],
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entry: Mapping[str, Any]) -> None:
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""" Converts a single entry from the JSON format for address rank
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descriptions into a flat format suitable for inserting into a
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PostgreSQL table and adds these lines to `rows`.
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"""
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countries = entry.get('countries') or (None, )
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for key, values in entry['tags'].items():
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for value, ranks in values.items():
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if isinstance(ranks, list):
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rank_search, rank_address = ranks
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else:
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rank_search = rank_address = ranks
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if not value:
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value = None
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for country in countries:
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rows.append((country, key, value, rank_search, rank_address))
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def load_address_levels(conn: Connection, table: str, levels: Sequence[Mapping[str, Any]]) -> None:
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""" Replace the `address_levels` table with the contents of `levels'.
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A new table is created any previously existing table is dropped.
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The table has the following columns:
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country, class, type, rank_search, rank_address
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"""
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rows: List[Tuple[Any, ...]] = []
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for entry in levels:
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_add_address_level_rows_from_entry(rows, entry)
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drop_tables(conn, table)
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with conn.cursor() as cur:
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cur.execute(pysql.SQL("""CREATE TABLE {} (
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country_code varchar(2),
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class TEXT,
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type TEXT,
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rank_search SMALLINT,
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rank_address SMALLINT)
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""").format(pysql.Identifier(table)))
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cur.executemany(pysql.SQL("INSERT INTO {} VALUES (%s, %s, %s, %s, %s)")
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.format(pysql.Identifier(table)), rows)
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cur.execute(pysql.SQL('CREATE UNIQUE INDEX ON {} (country_code, class, type)')
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.format(pysql.Identifier(table)))
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conn.commit()
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def load_address_levels_from_config(conn: Connection, config: Configuration) -> None:
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""" Replace the `address_levels` table with the content as
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defined in the given configuration. Uses the parameter
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NOMINATIM_ADDRESS_LEVEL_CONFIG to determine the location of the
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configuration file.
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"""
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cfg = config.load_sub_configuration('', config='ADDRESS_LEVEL_CONFIG')
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load_address_levels(conn, 'address_levels', cfg)
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def create_functions(conn: Connection, config: Configuration,
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enable_diff_updates: bool = True,
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enable_debug: bool = False) -> None:
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""" (Re)create the PL/pgSQL functions.
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"""
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sql = SQLPreprocessor(conn, config)
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sql.run_sql_file(conn, 'functions.sql',
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disable_diff_updates=not enable_diff_updates,
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debug=enable_debug)
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def import_wikipedia_articles(dsn: str, data_path: Path, ignore_errors: bool = False) -> int:
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""" Replaces the wikipedia importance tables with new data.
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The import is run in a single transaction so that the new data
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is replace seamlessly.
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Returns 0 if all was well and 1 if the importance file could not
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be found. Throws an exception if there was an error reading the file.
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"""
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if import_importance_csv(dsn, data_path / 'wikimedia-importance.csv.gz') == 0 \
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or import_importance_sql(dsn, data_path / 'wikimedia-importance.sql.gz',
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ignore_errors) == 0:
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return 0
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return 1
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def import_importance_csv(dsn: str, data_file: Path) -> int:
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""" Replace wikipedia importance table with data from a
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single CSV file.
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The file must be a gzipped CSV and have the following columns:
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language, title, importance, wikidata_id
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Other columns may be present but will be ignored.
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"""
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if not data_file.exists():
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return 1
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# Only import the first occurrence of a wikidata ID.
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# This keeps indexes and table small.
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wd_done = set()
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with connect(dsn) as conn:
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drop_tables(conn, 'wikipedia_article', 'wikipedia_redirect', 'wikimedia_importance')
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with conn.cursor() as cur:
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cur.execute("""CREATE TABLE wikimedia_importance (
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language TEXT NOT NULL,
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title TEXT NOT NULL,
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importance double precision NOT NULL,
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wikidata TEXT
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) """)
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copy_cmd = """COPY wikimedia_importance(language, title, importance, wikidata)
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FROM STDIN"""
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with gzip.open(str(data_file), 'rt') as fd, cur.copy(copy_cmd) as copy:
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for row in csv.DictReader(fd, delimiter='\t', quotechar='|'):
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wd_id = int(row['wikidata_id'][1:])
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copy.write_row((row['language'],
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row['title'],
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row['importance'],
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None if wd_id in wd_done else row['wikidata_id']))
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wd_done.add(wd_id)
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cur.execute("""CREATE INDEX IF NOT EXISTS idx_wikimedia_importance_title
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ON wikimedia_importance (title)""")
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cur.execute("""CREATE INDEX IF NOT EXISTS idx_wikimedia_importance_wikidata
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ON wikimedia_importance (wikidata)
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WHERE wikidata is not null""")
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conn.commit()
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return 0
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def import_importance_sql(dsn: str, data_file: Path, ignore_errors: bool) -> int:
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""" Replace wikipedia importance table with data from an SQL file.
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"""
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if not data_file.exists():
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return 1
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pre_code = """BEGIN;
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DROP TABLE IF EXISTS "wikipedia_article";
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DROP TABLE IF EXISTS "wikipedia_redirect";
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DROP TABLE IF EXISTS "wikipedia_importance";
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"""
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post_code = "COMMIT"
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execute_file(dsn, data_file, ignore_errors=ignore_errors,
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pre_code=pre_code, post_code=post_code)
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return 0
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def import_secondary_importance(dsn: str, data_path: Path, ignore_errors: bool = False) -> int:
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""" Replaces the secondary importance raster data table with new data.
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Returns 0 if all was well and 1 if the raster SQL file could not
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be found. Throws an exception if there was an error reading the file.
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"""
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datafile = data_path / 'secondary_importance.sql.gz'
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if not datafile.exists():
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return 1
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execute_file(dsn, datafile, ignore_errors=ignore_errors)
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return 0
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def recompute_importance(conn: Connection) -> None:
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""" Recompute wikipedia links and importance for all entries in placex.
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This is a long-running operations that must not be executed in
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parallel with updates.
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"""
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with conn.cursor() as cur:
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cur.execute('ALTER TABLE placex DISABLE TRIGGER ALL')
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cur.execute("""
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UPDATE placex SET (wikipedia, importance) =
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(SELECT wikipedia, importance
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FROM compute_importance(extratags, country_code, rank_search, centroid))
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""")
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cur.execute("""
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UPDATE placex s SET wikipedia = d.wikipedia, importance = d.importance
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FROM placex d
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WHERE s.place_id = d.linked_place_id and d.wikipedia is not null
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and (s.wikipedia is null or s.importance < d.importance);
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""")
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cur.execute("""
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UPDATE search_name s SET importance = p.importance
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FROM placex p
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WHERE s.place_id = p.place_id AND s.importance != p.importance
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""")
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cur.execute('ALTER TABLE placex ENABLE TRIGGER ALL')
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conn.commit()
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def invalidate_osm_object(osm_type: str, osm_id: int, conn: Connection,
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recursive: bool = True) -> None:
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""" Mark the given OSM object for reindexing. When 'recursive' is set
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to True (the default), then all dependent objects are marked for
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reindexing as well.
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'osm_type' must be on of 'N' (node), 'W' (way) or 'R' (relation).
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If the given object does not exist, then nothing happens.
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"""
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assert osm_type in ('N', 'R', 'W')
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LOG.warning("Invalidating OSM %s %s%s.",
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OSM_TYPE[osm_type], osm_id,
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' and its dependent places' if recursive else '')
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with conn.cursor() as cur:
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if recursive:
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sql = """SELECT place_force_update(place_id)
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FROM placex WHERE osm_type = %s and osm_id = %s"""
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else:
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sql = """UPDATE placex SET indexed_status = 2
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WHERE osm_type = %s and osm_id = %s"""
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cur.execute(sql, (osm_type, osm_id))
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