orexpr.append(table.c.rank_address.between(1, 29))
orexpr.append(sa.and_(table.c.rank_address == 30,
sa.or_(table.c.housenumber != None,
- table.c.address.has_key('housename'))))
+ table.c.address.has_key('addr:housename'))))
elif layers & DataLayer.POI:
orexpr.append(sa.and_(table.c.rank_address == 30,
table.c.class_.not_in(('place', 'building'))))
"""
table = await conn.get_class_table(*category)
- t = conn.t.placex.alias('p')
+ t = conn.t.placex
tgeom = conn.t.placex.alias('pgeom')
sql = _select_placex(t).where(tgeom.c.place_id.in_(ids))\
# radius for the lookup.
sql = sql.join(table, t.c.place_id == table.c.place_id)\
.join(tgeom,
- sa.case((sa.and_(tgeom.c.rank_address < 9,
- tgeom.c.geometry.is_area()),
- tgeom.c.geometry.ST_Contains(table.c.centroid)),
- else_ = tgeom.c.centroid.ST_DWithin(table.c.centroid, 0.05)))\
+ table.c.centroid.ST_CoveredBy(
+ sa.case((sa.and_(tgeom.c.rank_address < 9,
+ tgeom.c.geometry.is_area()),
+ tgeom.c.geometry),
+ else_ = tgeom.c.centroid.ST_Expand(0.05))))\
.order_by(tgeom.c.centroid.ST_Distance(table.c.centroid))
sql = sql.where(t.c.rank_address.between(MIN_RANK_PARAM, MAX_RANK_PARAM))
"""
def __init__(self, sdata: SearchData) -> None:
super().__init__(sdata.penalty)
- self.categories = sdata.qualifiers
+ self.qualifiers = sdata.qualifiers
self.countries = sdata.countries
.order_by(t.c.centroid.ST_Distance(NEAR_PARAM)) \
.limit(LIMIT_PARAM)
- classtype = self.categories.values
+ classtype = self.qualifiers.values
if len(classtype) == 1:
cclass, ctype = classtype[0]
sql: SaLambdaSelect = sa.lambda_stmt(lambda: _base_query()
rows.extend(await conn.execute(sql, bind_params))
else:
# use the class type tables
- for category in self.categories.values:
+ for category in self.qualifiers.values:
table = await conn.get_class_table(*category)
if table is not None:
sql = _select_placex(t)\
for row in rows:
result = nres.create_from_placex_row(row, nres.SearchResult)
assert result
- result.accuracy = self.penalty + self.categories.get_penalty((row.class_, row.type))
+ result.accuracy = self.penalty + self.qualifiers.get_penalty((row.class_, row.type))
result.bbox = Bbox.from_wkb(row.bbox)
results.append(result)
t = conn.t.placex
ccodes = self.countries.values
- sql: SaLambdaSelect = sa.lambda_stmt(lambda: _select_placex(t)\
+ sql = _select_placex(t)\
.where(t.c.country_code.in_(ccodes))\
- .where(t.c.rank_address == 4))
+ .where(t.c.rank_address == 4)
if details.geometry_output:
sql = _add_geometry_columns(sql, t.c.geometry, details)
result = nres.create_from_placex_row(row, nres.SearchResult)
assert result
result.accuracy = self.penalty + self.countries.get_penalty(row.country_code, 5.0)
+ result.bbox = Bbox.from_wkb(row.bbox)
results.append(result)
return results or await self.lookup_in_country_table(conn, details)
t = conn.t.postcode
pcs = self.postcodes.values
- sql: SaLambdaSelect = sa.lambda_stmt(lambda:
- sa.select(t.c.place_id, t.c.parent_place_id,
+ sql = sa.select(t.c.place_id, t.c.parent_place_id,
t.c.rank_search, t.c.rank_address,
t.c.postcode, t.c.country_code,
- t.c.geometry.label('centroid'))
- .where(t.c.postcode.in_(pcs)))
+ t.c.geometry.label('centroid'))\
+ .where(t.c.postcode.in_(pcs))
if details.geometry_output:
sql = _add_geometry_columns(sql, t.c.geometry, details)
pcs = self.postcodes.values
if self.expected_count > 1000:
# Many results expected. Restrict by postcode.
- sql = sql.where(lambda: sa.select(tpc.c.postcode)
+ sql = sql.where(sa.select(tpc.c.postcode)
.where(tpc.c.postcode.in_(pcs))
.where(tsearch.c.centroid.ST_DWithin(tpc.c.geometry, 0.12))
.exists())
if details.viewbox is not None:
if details.bounded_viewbox:
- sql = sql.where(tsearch.c.centroid.intersects(VIEWBOX_PARAM))
+ if details.viewbox.area < 0.2:
+ sql = sql.where(tsearch.c.centroid.intersects(VIEWBOX_PARAM))
+ else:
+ sql = sql.where(tsearch.c.centroid.ST_Intersects_no_index(VIEWBOX_PARAM))
+ elif self.expected_count >= 10000:
+ if details.viewbox.area < 0.5:
+ sql = sql.where(tsearch.c.centroid.intersects(VIEWBOX2_PARAM))
+ else:
+ sql = sql.where(tsearch.c.centroid.ST_Intersects_no_index(VIEWBOX2_PARAM))
else:
penalty += sa.case((t.c.geometry.intersects(VIEWBOX_PARAM), 0.0),
(t.c.geometry.intersects(VIEWBOX2_PARAM), 1.0),
if details.near is not None:
if details.near_radius is not None:
- sql = sql.where(tsearch.c.centroid.ST_DWithin(NEAR_PARAM, NEAR_RADIUS_PARAM))
- sql = sql.add_columns(-tsearch.c.centroid.ST_Distance(NEAR_PARAM)
+ if details.near_radius < 0.1:
+ sql = sql.where(tsearch.c.centroid.ST_DWithin(NEAR_PARAM, NEAR_RADIUS_PARAM))
+ else:
+ sql = sql.where(tsearch.c.centroid.ST_DWithin_no_index(NEAR_PARAM,
+ NEAR_RADIUS_PARAM))
+ sql = sql.add_columns((-tsearch.c.centroid.ST_Distance(NEAR_PARAM))
.label('importance'))
sql = sql.order_by(sa.desc(sa.text('importance')))
else:
- sql = sql.order_by(penalty - sa.case((tsearch.c.importance > 0, tsearch.c.importance),
- else_=0.75001-(sa.cast(tsearch.c.search_rank, sa.Float())/40)))
+ if self.expected_count < 10000\
+ or (details.viewbox is not None and details.viewbox.area < 0.5):
+ sql = sql.order_by(
+ penalty - sa.case((tsearch.c.importance > 0, tsearch.c.importance),
+ else_=0.75001-(sa.cast(tsearch.c.search_rank, sa.Float())/40)))
sql = sql.add_columns(t.c.importance)
- sql = sql.add_columns(penalty.label('accuracy'))\
- .order_by(sa.text('accuracy'))
+ sql = sql.add_columns(penalty.label('accuracy'))
+
+ if self.expected_count < 10000:
+ sql = sql.order_by(sa.text('accuracy'))
if self.housenumbers:
hnr_regexp = f"\\m({'|'.join(self.housenumbers.values)})\\M"
.where(thnr.c.indexed_status == 0)
if details.excluded:
- place_sql = place_sql.where(_exclude_places(thnr))
+ place_sql = place_sql.where(thnr.c.place_id.not_in(sa.bindparam('excluded')))
if self.qualifiers:
place_sql = place_sql.where(self.qualifiers.sql_restrict(thnr))
- numerals = [int(n) for n in self.housenumbers.values if n.isdigit()]
+ numerals = [int(n) for n in self.housenumbers.values
+ if n.isdigit() and len(n) < 8]
interpol_sql: SaColumn
tiger_sql: SaColumn
if numerals and \
projects / nominatim.git / blobdiff