Exporting a Nominatim database to SQlite.
"""
from typing import Set
+import logging
from pathlib import Path
import sqlalchemy as sa
+from nominatim.typing import SaSelect
+from nominatim.db.sqlalchemy_types import Geometry
import nominatim.api as napi
+LOG = logging.getLogger()
+
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.
outapi = napi.NominatimAPIAsync(project_dir,
{'NOMINATIM_DATABASE_DSN': f"sqlite:dbname={outfile}"})
- async with api.begin() as inconn, outapi.begin() as outconn:
- pass
+ async with api.begin() as src, outapi.begin() as dest:
+ writer = SqliteWriter(src, dest, options)
+ await writer.write()
finally:
await api.close()
+
+
+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.
+ """
+ await self.dest.execute(sa.select(sa.func.InitSpatialMetaData(True, 'WGS84')))
+
+ await self.create_tables()
+ await self.copy_data()
+ await self.create_indexes()
+
+
+ async def create_tables(self) -> None:
+ """ Set up the database tables.
+ """
+ if 'search' not in self.options:
+ self.dest.t.meta.remove(self.dest.t.search_name)
+
+ 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 copy_data(self) -> None:
+ """ Copy data for all registered tables.
+ """
+ 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): getattr(r, k) for k in r._fields}
+ for r in partition]
+ await self.dest.execute(table.insert(), data)
+
+
+ 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', 'rank_address')
+ await self.create_index('addressline', 'place_id')
+
+
+ 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)
+
+
+ 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
+
+ sql = sa.select(*(sa.func.ST_AsText(c).label(c.name)
+ if isinstance(c.type, Geometry) else c for c in columns))
+
+ return sql