Nominatim/nominatim/tools/convert_sqlite.py

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2023-10-11 23:35:18 +03:00
# SPDX-License-Identifier: GPL-3.0-or-later
#
# This file is part of Nominatim. (https://nominatim.org)
#
# Copyright (C) 2023 by the Nominatim developer community.
# For a full list of authors see the git log.
"""
Exporting a Nominatim database to SQlite.
"""
from typing import Set, Any
import datetime as dt
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import logging
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from pathlib import Path
import sqlalchemy as sa
from nominatim.typing import SaSelect, SaRow
from nominatim.db.sqlalchemy_types import Geometry, IntArray
from nominatim.api.search.query_analyzer_factory import make_query_analyzer
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import nominatim.api as napi
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LOG = logging.getLogger()
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async def convert(project_dir: Path, outfile: Path, options: Set[str]) -> None:
""" Export an existing database to sqlite. The resulting database
will be usable against the Python frontend of Nominatim.
"""
api = napi.NominatimAPIAsync(project_dir)
try:
outapi = napi.NominatimAPIAsync(project_dir,
{'NOMINATIM_DATABASE_DSN': f"sqlite:dbname={outfile}",
'NOMINATIM_DATABASE_RW': '1'})
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try:
async with api.begin() as src, outapi.begin() as dest:
writer = SqliteWriter(src, dest, options)
await writer.write()
finally:
await outapi.close()
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finally:
await api.close()
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class SqliteWriter:
""" Worker class which creates a new SQLite database.
"""
def __init__(self, src: napi.SearchConnection,
dest: napi.SearchConnection, options: Set[str]) -> None:
self.src = src
self.dest = dest
self.options = options
async def write(self) -> None:
""" Create the database structure and copy the data from
the source database to the destination.
"""
LOG.warning('Setting up spatialite')
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await self.dest.execute(sa.select(sa.func.InitSpatialMetaData(True, 'WGS84')))
await self.create_tables()
await self.copy_data()
if 'search' in self.options:
await self.create_word_table()
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await self.create_indexes()
async def create_tables(self) -> None:
""" Set up the database tables.
"""
LOG.warning('Setting up tables')
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if 'search' not in self.options:
self.dest.t.meta.remove(self.dest.t.search_name)
else:
await self.create_class_tables()
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await self.dest.connection.run_sync(self.dest.t.meta.create_all)
# Convert all Geometry columns to Spatialite geometries
for table in self.dest.t.meta.sorted_tables:
for col in table.c:
if isinstance(col.type, Geometry):
await self.dest.execute(sa.select(
sa.func.RecoverGeometryColumn(table.name, col.name, 4326,
col.type.subtype.upper(), 'XY')))
async def create_class_tables(self) -> None:
""" Set up the table that serve class/type-specific geometries.
"""
sql = sa.text("""SELECT tablename FROM pg_tables
WHERE tablename LIKE 'place_classtype_%'""")
for res in await self.src.execute(sql):
for db in (self.src, self.dest):
sa.Table(res[0], db.t.meta,
sa.Column('place_id', sa.BigInteger),
sa.Column('centroid', Geometry))
async def create_word_table(self) -> None:
""" Create the word table.
This table needs the property information to determine the
correct format. Therefore needs to be done after all other
data has been copied.
"""
await make_query_analyzer(self.src)
await make_query_analyzer(self.dest)
src = self.src.t.meta.tables['word']
dest = self.dest.t.meta.tables['word']
await self.dest.connection.run_sync(dest.create)
LOG.warning("Copying word table")
async_result = await self.src.connection.stream(sa.select(src))
async for partition in async_result.partitions(10000):
data = [{k: getattr(r, k) for k in r._fields} for r in partition]
await self.dest.execute(dest.insert(), data)
await self.dest.connection.run_sync(sa.Index('idx_word_woken', dest.c.word_token).create)
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async def copy_data(self) -> None:
""" Copy data for all registered tables.
"""
def _getfield(row: SaRow, key: str) -> Any:
value = getattr(row, key)
if isinstance(value, dt.datetime):
if value.tzinfo is not None:
value = value.astimezone(dt.timezone.utc)
return value
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for table in self.dest.t.meta.sorted_tables:
LOG.warning("Copying '%s'", table.name)
async_result = await self.src.connection.stream(self.select_from(table.name))
async for partition in async_result.partitions(10000):
data = [{('class_' if k == 'class' else k): _getfield(r, k)
for k in r._fields}
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for r in partition]
await self.dest.execute(table.insert(), data)
# Set up a minimal copy of pg_tables used to look up the class tables later.
pg_tables = sa.Table('pg_tables', self.dest.t.meta,
sa.Column('schemaname', sa.Text, default='public'),
sa.Column('tablename', sa.Text))
await self.dest.connection.run_sync(pg_tables.create)
data = [{'tablename': t} for t in self.dest.t.meta.tables]
await self.dest.execute(pg_tables.insert().values(data))
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async def create_indexes(self) -> None:
""" Add indexes necessary for the frontend.
"""
# reverse place node lookup needs an extra table to simulate a
# partial index with adaptive buffering.
await self.dest.execute(sa.text(
""" CREATE TABLE placex_place_node_areas AS
SELECT place_id, ST_Expand(geometry,
14.0 * exp(-0.2 * rank_search) - 0.03) as geometry
FROM placex
WHERE rank_address between 5 and 25
and osm_type = 'N'
and linked_place_id is NULL """))
await self.dest.execute(sa.select(
sa.func.RecoverGeometryColumn('placex_place_node_areas', 'geometry',
4326, 'GEOMETRY', 'XY')))
await self.dest.execute(sa.select(sa.func.CreateSpatialIndex(
'placex_place_node_areas', 'geometry')))
# Remaining indexes.
await self.create_spatial_index('country_grid', 'geometry')
await self.create_spatial_index('placex', 'geometry')
await self.create_spatial_index('osmline', 'linegeo')
await self.create_spatial_index('tiger', 'linegeo')
await self.create_index('placex', 'place_id')
await self.create_index('placex', 'parent_place_id')
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await self.create_index('placex', 'rank_address')
await self.create_index('addressline', 'place_id')
await self.create_index('postcode', 'place_id')
await self.create_index('osmline', 'place_id')
await self.create_index('tiger', 'place_id')
if 'search' in self.options:
await self.create_spatial_index('postcode', 'geometry')
await self.create_spatial_index('search_name', 'centroid')
await self.create_index('search_name', 'place_id')
await self.create_index('osmline', 'parent_place_id')
await self.create_index('tiger', 'parent_place_id')
await self.create_search_index()
for t in self.dest.t.meta.tables:
if t.startswith('place_classtype_'):
await self.dest.execute(sa.select(
sa.func.CreateSpatialIndex(t, 'centroid')))
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async def create_spatial_index(self, table: str, column: str) -> None:
""" Create a spatial index on the given table and column.
"""
await self.dest.execute(sa.select(
sa.func.CreateSpatialIndex(getattr(self.dest.t, table).name, column)))
async def create_index(self, table_name: str, column: str) -> None:
""" Create a simple index on the given table and column.
"""
table = getattr(self.dest.t, table_name)
await self.dest.connection.run_sync(
sa.Index(f"idx_{table}_{column}", getattr(table.c, column)).create)
async def create_search_index(self) -> None:
""" Create the tables and indexes needed for word lookup.
"""
LOG.warning("Creating reverse search table")
rsn = sa.Table('reverse_search_name', self.dest.t.meta,
sa.Column('word', sa.Integer()),
sa.Column('column', sa.Text()),
sa.Column('places', IntArray))
await self.dest.connection.run_sync(rsn.create)
tsrc = self.src.t.search_name
for column in ('name_vector', 'nameaddress_vector'):
sql = sa.select(sa.func.unnest(getattr(tsrc.c, column)).label('word'),
sa.func.ArrayAgg(tsrc.c.place_id).label('places'))\
.group_by('word')
async_result = await self.src.connection.stream(sql)
async for partition in async_result.partitions(100):
data = []
for row in partition:
row.places.sort()
data.append({'word': row.word,
'column': column,
'places': row.places})
await self.dest.execute(rsn.insert(), data)
await self.dest.connection.run_sync(
sa.Index('idx_reverse_search_name_word', rsn.c.word).create)
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def select_from(self, table: str) -> SaSelect:
""" Create the SQL statement to select the source columns and rows.
"""
columns = self.src.t.meta.tables[table].c
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if table == 'placex':
# SQLite struggles with Geometries that are larger than 5MB,
# so simplify those.
return sa.select(*(c for c in columns if not isinstance(c.type, Geometry)),
sa.func.ST_AsText(columns.centroid).label('centroid'),
sa.func.ST_AsText(
sa.case((sa.func.ST_MemSize(columns.geometry) < 5000000,
columns.geometry),
else_=sa.func.ST_SimplifyPreserveTopology(
columns.geometry, 0.0001)
)).label('geometry'))
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sql = sa.select(*(sa.func.ST_AsText(c).label(c.name)
if isinstance(c.type, Geometry) else c for c in columns))
return sql