mirror of
https://github.com/osm-search/Nominatim.git
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150 lines
5.0 KiB
Python
150 lines
5.0 KiB
Python
# SPDX-License-Identifier: GPL-2.0-only
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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) 2022 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 importing tiger data and handling tarbar and directory files
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"""
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from typing import Any, TextIO, List, Union, cast
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import csv
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import io
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import logging
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import os
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import tarfile
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from psycopg2.extras import Json
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from nominatim.config import Configuration
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from nominatim.db.connection import connect
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from nominatim.db.async_connection import WorkerPool
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from nominatim.db.sql_preprocessor import SQLPreprocessor
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from nominatim.errors import UsageError
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from nominatim.data.place_info import PlaceInfo
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from nominatim.tokenizer.base import AbstractAnalyzer, AbstractTokenizer
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from nominatim.tools import freeze
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LOG = logging.getLogger()
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class TigerInput:
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""" Context manager that goes through Tiger input files which may
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either be in a directory or gzipped together in a tar file.
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"""
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def __init__(self, data_dir: str) -> None:
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self.tar_handle = None
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self.files: List[Union[str, tarfile.TarInfo]] = []
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if data_dir.endswith('.tar.gz'):
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try:
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self.tar_handle = tarfile.open(data_dir) # pylint: disable=consider-using-with
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except tarfile.ReadError as err:
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LOG.fatal("Cannot open '%s'. Is this a tar file?", data_dir)
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raise UsageError("Cannot open Tiger data file.") from err
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self.files = [i for i in self.tar_handle.getmembers() if i.name.endswith('.csv')]
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LOG.warning("Found %d CSV files in tarfile with path %s", len(self.files), data_dir)
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else:
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files = os.listdir(data_dir)
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self.files = [os.path.join(data_dir, i) for i in files if i.endswith('.csv')]
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LOG.warning("Found %d CSV files in path %s", len(self.files), data_dir)
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if not self.files:
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LOG.warning("Tiger data import selected but no files found at %s", data_dir)
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def __enter__(self) -> 'TigerInput':
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return self
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def __exit__(self, exc_type: Any, exc_val: Any, exc_tb: Any) -> None:
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if self.tar_handle:
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self.tar_handle.close()
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self.tar_handle = None
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def next_file(self) -> TextIO:
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""" Return a file handle to the next file to be processed.
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Raises an IndexError if there is no file left.
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"""
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fname = self.files.pop(0)
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if self.tar_handle is not None:
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extracted = self.tar_handle.extractfile(fname)
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assert extracted is not None
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return io.TextIOWrapper(extracted)
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return open(cast(str, fname), encoding='utf-8')
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def __len__(self) -> int:
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return len(self.files)
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def handle_threaded_sql_statements(pool: WorkerPool, fd: TextIO,
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analyzer: AbstractAnalyzer) -> None:
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""" Handles sql statement with multiplexing
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"""
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lines = 0
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# Using pool of database connections to execute sql statements
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sql = "SELECT tiger_line_import(%s, %s, %s, %s, %s, %s)"
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for row in csv.DictReader(fd, delimiter=';'):
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try:
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address = dict(street=row['street'], postcode=row['postcode'])
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args = ('SRID=4326;' + row['geometry'],
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int(row['from']), int(row['to']), row['interpolation'],
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Json(analyzer.process_place(PlaceInfo({'address': address}))),
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analyzer.normalize_postcode(row['postcode']))
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except ValueError:
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continue
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pool.next_free_worker().perform(sql, args=args)
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lines += 1
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if lines == 1000:
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print('.', end='', flush=True)
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lines = 0
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def add_tiger_data(data_dir: str, config: Configuration, threads: int,
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tokenizer: AbstractTokenizer) -> int:
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""" Import tiger data from directory or tar file `data dir`.
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"""
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dsn = config.get_libpq_dsn()
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with connect(dsn) as conn:
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is_frozen = freeze.is_frozen(conn)
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conn.close()
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if is_frozen:
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raise UsageError("Tiger cannot be imported when database frozen (Github issue #3048)")
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with TigerInput(data_dir) as tar:
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if not tar:
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return 1
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with connect(dsn) as conn:
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sql = SQLPreprocessor(conn, config)
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sql.run_sql_file(conn, 'tiger_import_start.sql')
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# Reading files and then for each file line handling
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# sql_query in <threads - 1> chunks.
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place_threads = max(1, threads - 1)
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with WorkerPool(dsn, place_threads, ignore_sql_errors=True) as pool:
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with tokenizer.name_analyzer() as analyzer:
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while tar:
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with tar.next_file() as fd:
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handle_threaded_sql_statements(pool, fd, analyzer)
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print('\n')
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LOG.warning("Creating indexes on Tiger data")
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with connect(dsn) as conn:
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sql = SQLPreprocessor(conn, config)
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sql.run_sql_file(conn, 'tiger_import_finish.sql')
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return 0
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