"""
Functions for importing tiger data and handling tarbar and directory files
"""
-from typing import Any, TextIO, List, Union, cast
+from typing import Any, TextIO, List, Union, cast, Iterator, Dict
import csv
import io
import logging
import os
import tarfile
-from psycopg2.extras import Json
+from psycopg.types.json import Json
-from nominatim_core.config import Configuration
-from nominatim_core.db.connection import connect
-from nominatim_core.db.async_connection import WorkerPool
-from nominatim_core.db.sql_preprocessor import SQLPreprocessor
-from nominatim_core.errors import UsageError
+from ..config import Configuration
+from ..db.connection import connect
+from ..db.sql_preprocessor import SQLPreprocessor
+from ..errors import UsageError
+from ..db.query_pool import QueryPool
from ..data.place_info import PlaceInfo
-from ..tokenizer.base import AbstractAnalyzer, AbstractTokenizer
+from ..tokenizer.base import AbstractTokenizer
from . import freeze
LOG = logging.getLogger()
self.tar_handle.close()
self.tar_handle = None
+ def __bool__(self) -> bool:
+ return bool(self.files)
- def next_file(self) -> TextIO:
+ def get_file(self, fname: Union[str, tarfile.TarInfo]) -> TextIO:
""" Return a file handle to the next file to be processed.
Raises an IndexError if there is no file left.
"""
- fname = self.files.pop(0)
-
if self.tar_handle is not None:
extracted = self.tar_handle.extractfile(fname)
assert extracted is not None
return open(cast(str, fname), encoding='utf-8')
- def __len__(self) -> int:
- return len(self.files)
-
-
-def handle_threaded_sql_statements(pool: WorkerPool, fd: TextIO,
- analyzer: AbstractAnalyzer) -> None:
- """ Handles sql statement with multiplexing
- """
- lines = 0
- # Using pool of database connections to execute sql statements
-
- sql = "SELECT tiger_line_import(%s, %s, %s, %s, %s, %s)"
-
- for row in csv.DictReader(fd, delimiter=';'):
- try:
- address = dict(street=row['street'], postcode=row['postcode'])
- args = ('SRID=4326;' + row['geometry'],
- int(row['from']), int(row['to']), row['interpolation'],
- Json(analyzer.process_place(PlaceInfo({'address': address}))),
- analyzer.normalize_postcode(row['postcode']))
- except ValueError:
- continue
- pool.next_free_worker().perform(sql, args=args)
-
- lines += 1
- if lines == 1000:
- print('.', end='', flush=True)
- lines = 0
+ def __iter__(self) -> Iterator[Dict[str, Any]]:
+ """ Iterate over the lines in each file.
+ """
+ for fname in self.files:
+ fd = self.get_file(fname)
+ yield from csv.DictReader(fd, delimiter=';')
-def add_tiger_data(data_dir: str, config: Configuration, threads: int,
+async def add_tiger_data(data_dir: str, config: Configuration, threads: int,
tokenizer: AbstractTokenizer) -> int:
""" Import tiger data from directory or tar file `data dir`.
"""
dsn = config.get_libpq_dsn()
with connect(dsn) as conn:
- is_frozen = freeze.is_frozen(conn)
- conn.close()
-
- if is_frozen:
+ if freeze.is_frozen(conn):
raise UsageError("Tiger cannot be imported when database frozen (Github issue #3048)")
with TigerInput(data_dir) as tar:
# sql_query in <threads - 1> chunks.
place_threads = max(1, threads - 1)
- with WorkerPool(dsn, place_threads, ignore_sql_errors=True) as pool:
+ async with QueryPool(dsn, place_threads, autocommit=True) as pool:
with tokenizer.name_analyzer() as analyzer:
- while tar:
- with tar.next_file() as fd:
- handle_threaded_sql_statements(pool, fd, analyzer)
-
- print('\n')
+ lines = 0
+ for row in tar:
+ try:
+ address = dict(street=row['street'], postcode=row['postcode'])
+ args = ('SRID=4326;' + row['geometry'],
+ int(row['from']), int(row['to']), row['interpolation'],
+ Json(analyzer.process_place(PlaceInfo({'address': address}))),
+ analyzer.normalize_postcode(row['postcode']))
+ except ValueError:
+ continue
+
+ await pool.put_query(
+ """SELECT tiger_line_import(%s::GEOMETRY, %s::INT,
+ %s::INT, %s::TEXT, %s::JSONB, %s::TEXT)""",
+ args)
+
+ lines += 1
+ if lines == 1000:
+ print('.', end='', flush=True)
+ lines = 0
+
+ print('', flush=True)
LOG.warning("Creating indexes on Tiger data")
with connect(dsn) as conn: