"""
Implementation of the acutal database accesses for forward search.
"""
-from typing import List, Tuple, AsyncIterator, Dict, Any, Callable
+from typing import List, Tuple, AsyncIterator, Dict, Any, Callable, cast
import abc
import sqlalchemy as sa
-from sqlalchemy.dialects.postgresql import array_agg
from nominatim.typing import SaFromClause, SaScalarSelect, SaColumn, \
SaExpression, SaSelect, SaLambdaSelect, SaRow, SaBind
from nominatim.api.types import SearchDetails, DataLayer, GeometryFormat, Bbox
import nominatim.api.results as nres
from nominatim.api.search.db_search_fields import SearchData, WeightedCategories
-from nominatim.db.sqlalchemy_types import Geometry
+from nominatim.db.sqlalchemy_types import Geometry, IntArray
#pylint: disable=singleton-comparison,not-callable
#pylint: disable=too-many-branches,too-many-arguments,too-many-locals,too-many-statements
def _make_interpolation_subquery(table: SaFromClause, inner: SaFromClause,
numerals: List[int], details: SearchDetails) -> SaScalarSelect:
- all_ids = array_agg(table.c.place_id) # type: ignore[no-untyped-call]
+ all_ids = sa.func.ArrayAgg(table.c.place_id)
sql = sa.select(all_ids).where(table.c.parent_place_id == inner.c.place_id)
if len(numerals) == 1:
orexpr.append(no_index(table.c.rank_address).between(1, 30))
elif layers & DataLayer.ADDRESS:
orexpr.append(no_index(table.c.rank_address).between(1, 29))
- orexpr.append(sa.and_(no_index(table.c.rank_address) == 30,
- sa.or_(table.c.housenumber != None,
- table.c.address.has_key('addr:housename'))))
+ orexpr.append(sa.func.IsAddressPoint(table))
elif layers & DataLayer.POI:
orexpr.append(sa.and_(no_index(table.c.rank_address) == 30,
table.c.class_.not_in(('place', 'building'))))
yield result
+def _int_list_to_subquery(inp: List[int]) -> 'sa.Subquery':
+ """ Create a subselect that returns the given list of integers
+ as rows in the column 'nr'.
+ """
+ vtab = sa.func.JsonArrayEach(sa.type_coerce(inp, sa.JSON))\
+ .table_valued(sa.column('value', type_=sa.JSON))
+ return sa.select(sa.cast(sa.cast(vtab.c.value, sa.Text), sa.Integer).label('nr')).subquery()
+
+
async def _get_osmline(conn: SearchConnection, place_ids: List[int],
numerals: List[int],
details: SearchDetails) -> AsyncIterator[nres.SearchResult]:
t = conn.t.osmline
- values = sa.values(sa.Column('nr', sa.Integer()), name='housenumber')\
- .data([(n,) for n in numerals])
+
+ values = _int_list_to_subquery(numerals)
sql = sa.select(t.c.place_id, t.c.osm_id,
t.c.parent_place_id, t.c.address,
values.c.nr.label('housenumber'),
numerals: List[int], osm_id: int,
details: SearchDetails) -> AsyncIterator[nres.SearchResult]:
t = conn.t.tiger
- values = sa.values(sa.Column('nr', sa.Integer()), name='housenumber')\
- .data([(n,) for n in numerals])
+ values = _int_list_to_subquery(numerals)
sql = sa.select(t.c.place_id, t.c.parent_place_id,
sa.literal('W').label('osm_type'),
sa.literal(osm_id).label('osm_id'),
class AbstractSearch(abc.ABC):
""" Encapuslation of a single lookup in the database.
"""
+ SEARCH_PRIO: int = 2
def __init__(self, penalty: float) -> None:
self.penalty = penalty
if table is None:
# No classtype table available, do a simplified lookup in placex.
- table = conn.t.placex.alias('inner')
+ table = conn.t.placex
sql = sa.select(table.c.place_id,
sa.func.min(tgeom.c.centroid.ST_Distance(table.c.centroid))
.label('dist'))\
class CountrySearch(AbstractSearch):
""" Search for a country name or country code.
"""
+ SEARCH_PRIO = 0
+
def __init__(self, sdata: SearchData) -> None:
super().__init__(sdata.penalty)
self.countries = sdata.countries
result.bbox = Bbox.from_wkb(row.bbox)
results.append(result)
- return results or await self.lookup_in_country_table(conn, details)
+ if not results:
+ results = await self.lookup_in_country_table(conn, details)
+
+ if results:
+ details.min_rank = min(5, details.max_rank)
+ details.max_rank = min(25, details.max_rank)
+
+ return results
async def lookup_in_country_table(self, conn: SearchConnection,
tsearch = conn.t.search_name
sql = sql.where(tsearch.c.place_id == t.c.parent_place_id)\
.where((tsearch.c.name_vector + tsearch.c.nameaddress_vector)
- .contains(self.lookups[0].tokens))
+ .contains(sa.type_coerce(self.lookups[0].tokens,
+ IntArray)))
for ranking in self.rankings:
penalty += ranking.sql_penalty(conn.t.search_name)
class PlaceSearch(AbstractSearch):
""" Generic search for an address or named place.
"""
+ SEARCH_PRIO = 1
+
def __init__(self, extra_penalty: float, sdata: SearchData, expected_count: int) -> None:
super().__init__(sdata.penalty + extra_penalty)
self.countries = sdata.countries
.where(tpc.c.postcode.in_(pcs))\
.scalar_subquery()
penalty += sa.case((t.c.postcode.in_(pcs), 0.0),
- else_=sa.func.coalesce(pc_near, 2.0))
+ else_=sa.func.coalesce(pc_near, cast(SaColumn, 2.0)))
if details.viewbox is not None:
if details.bounded_viewbox:
sql = sql.where(tsearch.c.centroid
.intersects(VIEWBOX_PARAM,
use_index=details.viewbox.area < 0.2))
- elif self.expected_count >= 10000:
+ elif not self.postcodes and not self.housenumbers and self.expected_count >= 10000:
sql = sql.where(tsearch.c.centroid
.intersects(VIEWBOX2_PARAM,
use_index=details.viewbox.area < 0.5))
sql = sql.order_by(sa.text('accuracy'))
if self.housenumbers:
- hnr_regexp = f"\\m({'|'.join(self.housenumbers.values)})\\M"
+ hnr_list = '|'.join(self.housenumbers.values)
sql = sql.where(tsearch.c.address_rank.between(16, 30))\
.where(sa.or_(tsearch.c.address_rank < 30,
- t.c.housenumber.op('~*')(hnr_regexp)))
+ sa.func.RegexpWord(hnr_list, t.c.housenumber)))
# Cross check for housenumbers, need to do that on a rather large
# set. Worst case there are 40.000 main streets in OSM.
# Housenumbers from placex
thnr = conn.t.placex.alias('hnr')
- pid_list = array_agg(thnr.c.place_id) # type: ignore[no-untyped-call]
+ pid_list = sa.func.ArrayAgg(thnr.c.place_id)
place_sql = sa.select(pid_list)\
.where(thnr.c.parent_place_id == inner.c.place_id)\
- .where(thnr.c.housenumber.op('~*')(hnr_regexp))\
+ .where(sa.func.RegexpWord(hnr_list, thnr.c.housenumber))\
.where(thnr.c.linked_place_id == None)\
.where(thnr.c.indexed_status == 0)
projects / nominatim.git / blobdiff