1 # SPDX-License-Identifier: GPL-3.0-or-later
3 # This file is part of Nominatim. (https://nominatim.org)
5 # Copyright (C) 2023 by the Nominatim developer community.
6 # For a full list of authors see the git log.
8 Implementation of the acutal database accesses for forward search.
10 from typing import List, Tuple, AsyncIterator, Dict, Any, Callable
13 import sqlalchemy as sa
14 from sqlalchemy.dialects.postgresql import array_agg
16 from nominatim.typing import SaFromClause, SaScalarSelect, SaColumn, \
17 SaExpression, SaSelect, SaLambdaSelect, SaRow, SaBind
18 from nominatim.api.connection import SearchConnection
19 from nominatim.api.types import SearchDetails, DataLayer, GeometryFormat, Bbox
20 import nominatim.api.results as nres
21 from nominatim.api.search.db_search_fields import SearchData, WeightedCategories
22 from nominatim.db.sqlalchemy_types import Geometry
24 #pylint: disable=singleton-comparison,not-callable
25 #pylint: disable=too-many-branches,too-many-arguments,too-many-locals,too-many-statements
27 def no_index(expr: SaColumn) -> SaColumn:
28 """ Wrap the given expression, so that the query planner will
29 refrain from using the expression for index lookup.
31 return sa.func.coalesce(sa.null(), expr) # pylint: disable=not-callable
34 def _details_to_bind_params(details: SearchDetails) -> Dict[str, Any]:
35 """ Create a dictionary from search parameters that can be used
36 as bind parameter for SQL execute.
38 return {'limit': details.max_results,
39 'min_rank': details.min_rank,
40 'max_rank': details.max_rank,
41 'viewbox': details.viewbox,
42 'viewbox2': details.viewbox_x2,
44 'near_radius': details.near_radius,
45 'excluded': details.excluded,
46 'countries': details.countries}
49 LIMIT_PARAM: SaBind = sa.bindparam('limit')
50 MIN_RANK_PARAM: SaBind = sa.bindparam('min_rank')
51 MAX_RANK_PARAM: SaBind = sa.bindparam('max_rank')
52 VIEWBOX_PARAM: SaBind = sa.bindparam('viewbox', type_=Geometry)
53 VIEWBOX2_PARAM: SaBind = sa.bindparam('viewbox2', type_=Geometry)
54 NEAR_PARAM: SaBind = sa.bindparam('near', type_=Geometry)
55 NEAR_RADIUS_PARAM: SaBind = sa.bindparam('near_radius')
56 COUNTRIES_PARAM: SaBind = sa.bindparam('countries')
58 def _within_near(t: SaFromClause) -> Callable[[], SaExpression]:
59 return lambda: t.c.geometry.ST_DWithin(NEAR_PARAM, NEAR_RADIUS_PARAM)
61 def _exclude_places(t: SaFromClause) -> Callable[[], SaExpression]:
62 return lambda: t.c.place_id.not_in(sa.bindparam('excluded'))
64 def _select_placex(t: SaFromClause) -> SaSelect:
65 return sa.select(t.c.place_id, t.c.osm_type, t.c.osm_id, t.c.name,
67 t.c.address, t.c.extratags,
68 t.c.housenumber, t.c.postcode, t.c.country_code,
70 t.c.parent_place_id, t.c.rank_address, t.c.rank_search,
71 t.c.linked_place_id, t.c.admin_level,
73 t.c.geometry.ST_Expand(0).label('bbox'))
76 def _add_geometry_columns(sql: SaLambdaSelect, col: SaColumn, details: SearchDetails) -> SaSelect:
79 if details.geometry_simplification > 0.0:
80 col = sa.func.ST_SimplifyPreserveTopology(col, details.geometry_simplification)
82 if details.geometry_output & GeometryFormat.GEOJSON:
83 out.append(sa.func.ST_AsGeoJSON(col, 7).label('geometry_geojson'))
84 if details.geometry_output & GeometryFormat.TEXT:
85 out.append(sa.func.ST_AsText(col).label('geometry_text'))
86 if details.geometry_output & GeometryFormat.KML:
87 out.append(sa.func.ST_AsKML(col, 7).label('geometry_kml'))
88 if details.geometry_output & GeometryFormat.SVG:
89 out.append(sa.func.ST_AsSVG(col, 0, 7).label('geometry_svg'))
91 return sql.add_columns(*out)
94 def _make_interpolation_subquery(table: SaFromClause, inner: SaFromClause,
95 numerals: List[int], details: SearchDetails) -> SaScalarSelect:
96 all_ids = array_agg(table.c.place_id) # type: ignore[no-untyped-call]
97 sql = sa.select(all_ids).where(table.c.parent_place_id == inner.c.place_id)
99 if len(numerals) == 1:
100 sql = sql.where(sa.between(numerals[0], table.c.startnumber, table.c.endnumber))\
101 .where((numerals[0] - table.c.startnumber) % table.c.step == 0)
103 sql = sql.where(sa.or_(
104 *(sa.and_(sa.between(n, table.c.startnumber, table.c.endnumber),
105 (n - table.c.startnumber) % table.c.step == 0)
109 sql = sql.where(_exclude_places(table))
111 return sql.scalar_subquery()
114 def _filter_by_layer(table: SaFromClause, layers: DataLayer) -> SaColumn:
115 orexpr: List[SaExpression] = []
116 if layers & DataLayer.ADDRESS and layers & DataLayer.POI:
117 orexpr.append(no_index(table.c.rank_address).between(1, 30))
118 elif layers & DataLayer.ADDRESS:
119 orexpr.append(no_index(table.c.rank_address).between(1, 29))
120 orexpr.append(sa.and_(no_index(table.c.rank_address) == 30,
121 sa.or_(table.c.housenumber != None,
122 table.c.address.has_key('addr:housename'))))
123 elif layers & DataLayer.POI:
124 orexpr.append(sa.and_(no_index(table.c.rank_address) == 30,
125 table.c.class_.not_in(('place', 'building'))))
127 if layers & DataLayer.MANMADE:
129 if not layers & DataLayer.RAILWAY:
130 exclude.append('railway')
131 if not layers & DataLayer.NATURAL:
132 exclude.extend(('natural', 'water', 'waterway'))
133 orexpr.append(sa.and_(table.c.class_.not_in(tuple(exclude)),
134 no_index(table.c.rank_address) == 0))
137 if layers & DataLayer.RAILWAY:
138 include.append('railway')
139 if layers & DataLayer.NATURAL:
140 include.extend(('natural', 'water', 'waterway'))
141 orexpr.append(sa.and_(table.c.class_.in_(tuple(include)),
142 no_index(table.c.rank_address) == 0))
147 return sa.or_(*orexpr)
150 def _interpolated_position(table: SaFromClause, nr: SaColumn) -> SaColumn:
151 pos = sa.cast(nr - table.c.startnumber, sa.Float) / (table.c.endnumber - table.c.startnumber)
153 (table.c.endnumber == table.c.startnumber, table.c.linegeo.ST_Centroid()),
154 else_=table.c.linegeo.ST_LineInterpolatePoint(pos)).label('centroid')
157 async def _get_placex_housenumbers(conn: SearchConnection,
158 place_ids: List[int],
159 details: SearchDetails) -> AsyncIterator[nres.SearchResult]:
161 sql = _select_placex(t).add_columns(t.c.importance)\
162 .where(t.c.place_id.in_(place_ids))
164 if details.geometry_output:
165 sql = _add_geometry_columns(sql, t.c.geometry, details)
167 for row in await conn.execute(sql):
168 result = nres.create_from_placex_row(row, nres.SearchResult)
170 result.bbox = Bbox.from_wkb(row.bbox)
174 async def _get_osmline(conn: SearchConnection, place_ids: List[int],
176 details: SearchDetails) -> AsyncIterator[nres.SearchResult]:
178 values = sa.values(sa.Column('nr', sa.Integer()), name='housenumber')\
179 .data([(n,) for n in numerals])
180 sql = sa.select(t.c.place_id, t.c.osm_id,
181 t.c.parent_place_id, t.c.address,
182 values.c.nr.label('housenumber'),
183 _interpolated_position(t, values.c.nr),
184 t.c.postcode, t.c.country_code)\
185 .where(t.c.place_id.in_(place_ids))\
186 .join(values, values.c.nr.between(t.c.startnumber, t.c.endnumber))
188 if details.geometry_output:
190 sql = _add_geometry_columns(sa.select(sub), sub.c.centroid, details)
192 for row in await conn.execute(sql):
193 result = nres.create_from_osmline_row(row, nres.SearchResult)
198 async def _get_tiger(conn: SearchConnection, place_ids: List[int],
199 numerals: List[int], osm_id: int,
200 details: SearchDetails) -> AsyncIterator[nres.SearchResult]:
202 values = sa.values(sa.Column('nr', sa.Integer()), name='housenumber')\
203 .data([(n,) for n in numerals])
204 sql = sa.select(t.c.place_id, t.c.parent_place_id,
205 sa.literal('W').label('osm_type'),
206 sa.literal(osm_id).label('osm_id'),
207 values.c.nr.label('housenumber'),
208 _interpolated_position(t, values.c.nr),
210 .where(t.c.place_id.in_(place_ids))\
211 .join(values, values.c.nr.between(t.c.startnumber, t.c.endnumber))
213 if details.geometry_output:
215 sql = _add_geometry_columns(sa.select(sub), sub.c.centroid, details)
217 for row in await conn.execute(sql):
218 result = nres.create_from_tiger_row(row, nres.SearchResult)
223 class AbstractSearch(abc.ABC):
224 """ Encapuslation of a single lookup in the database.
227 def __init__(self, penalty: float) -> None:
228 self.penalty = penalty
231 async def lookup(self, conn: SearchConnection,
232 details: SearchDetails) -> nres.SearchResults:
233 """ Find results for the search in the database.
237 class NearSearch(AbstractSearch):
238 """ Category search of a place type near the result of another search.
240 def __init__(self, penalty: float, categories: WeightedCategories,
241 search: AbstractSearch) -> None:
242 super().__init__(penalty)
244 self.categories = categories
247 async def lookup(self, conn: SearchConnection,
248 details: SearchDetails) -> nres.SearchResults:
249 """ Find results for the search in the database.
251 results = nres.SearchResults()
252 base = await self.search.lookup(conn, details)
257 base.sort(key=lambda r: (r.accuracy, r.rank_search))
258 max_accuracy = base[0].accuracy + 0.5
259 if base[0].rank_address == 0:
262 elif base[0].rank_address < 26:
264 max_rank = min(25, base[0].rank_address + 4)
268 base = nres.SearchResults(r for r in base if r.source_table == nres.SourceTable.PLACEX
269 and r.accuracy <= max_accuracy
270 and r.bbox and r.bbox.area < 20
271 and r.rank_address >= min_rank
272 and r.rank_address <= max_rank)
275 baseids = [b.place_id for b in base[:5] if b.place_id]
277 for category, penalty in self.categories:
278 await self.lookup_category(results, conn, baseids, category, penalty, details)
279 if len(results) >= details.max_results:
285 async def lookup_category(self, results: nres.SearchResults,
286 conn: SearchConnection, ids: List[int],
287 category: Tuple[str, str], penalty: float,
288 details: SearchDetails) -> None:
289 """ Find places of the given category near the list of
290 place ids and add the results to 'results'.
292 table = await conn.get_class_table(*category)
294 tgeom = conn.t.placex.alias('pgeom')
297 # No classtype table available, do a simplified lookup in placex.
298 table = conn.t.placex.alias('inner')
299 sql = sa.select(table.c.place_id,
300 sa.func.min(tgeom.c.centroid.ST_Distance(table.c.centroid))
302 .join(tgeom, table.c.geometry.intersects(tgeom.c.centroid.ST_Expand(0.01)))\
303 .where(table.c.class_ == category[0])\
304 .where(table.c.type == category[1])
306 # Use classtype table. We can afford to use a larger
307 # radius for the lookup.
308 sql = sa.select(table.c.place_id,
309 sa.func.min(tgeom.c.centroid.ST_Distance(table.c.centroid))
312 table.c.centroid.ST_CoveredBy(
313 sa.case((sa.and_(tgeom.c.rank_address > 9,
314 tgeom.c.geometry.is_area()),
316 else_ = tgeom.c.centroid.ST_Expand(0.05))))
318 inner = sql.where(tgeom.c.place_id.in_(ids))\
319 .group_by(table.c.place_id).subquery()
322 sql = _select_placex(t).add_columns((-inner.c.dist).label('importance'))\
323 .join(inner, inner.c.place_id == t.c.place_id)\
324 .order_by(inner.c.dist)
326 sql = sql.where(no_index(t.c.rank_address).between(MIN_RANK_PARAM, MAX_RANK_PARAM))
327 if details.countries:
328 sql = sql.where(t.c.country_code.in_(COUNTRIES_PARAM))
330 sql = sql.where(_exclude_places(t))
331 if details.layers is not None:
332 sql = sql.where(_filter_by_layer(t, details.layers))
334 sql = sql.limit(LIMIT_PARAM)
335 for row in await conn.execute(sql, _details_to_bind_params(details)):
336 result = nres.create_from_placex_row(row, nres.SearchResult)
338 result.accuracy = self.penalty + penalty
339 result.bbox = Bbox.from_wkb(row.bbox)
340 results.append(result)
344 class PoiSearch(AbstractSearch):
345 """ Category search in a geographic area.
347 def __init__(self, sdata: SearchData) -> None:
348 super().__init__(sdata.penalty)
349 self.qualifiers = sdata.qualifiers
350 self.countries = sdata.countries
353 async def lookup(self, conn: SearchConnection,
354 details: SearchDetails) -> nres.SearchResults:
355 """ Find results for the search in the database.
357 bind_params = _details_to_bind_params(details)
360 rows: List[SaRow] = []
362 if details.near and details.near_radius is not None and details.near_radius < 0.2:
363 # simply search in placex table
364 def _base_query() -> SaSelect:
365 return _select_placex(t) \
366 .add_columns((-t.c.centroid.ST_Distance(NEAR_PARAM))
367 .label('importance'))\
368 .where(t.c.linked_place_id == None) \
369 .where(t.c.geometry.ST_DWithin(NEAR_PARAM, NEAR_RADIUS_PARAM)) \
370 .order_by(t.c.centroid.ST_Distance(NEAR_PARAM)) \
373 classtype = self.qualifiers.values
374 if len(classtype) == 1:
375 cclass, ctype = classtype[0]
376 sql: SaLambdaSelect = sa.lambda_stmt(lambda: _base_query()
377 .where(t.c.class_ == cclass)
378 .where(t.c.type == ctype))
380 sql = _base_query().where(sa.or_(*(sa.and_(t.c.class_ == cls, t.c.type == typ)
381 for cls, typ in classtype)))
384 sql = sql.where(t.c.country_code.in_(self.countries.values))
386 if details.viewbox is not None and details.bounded_viewbox:
387 sql = sql.where(t.c.geometry.intersects(VIEWBOX_PARAM))
389 rows.extend(await conn.execute(sql, bind_params))
391 # use the class type tables
392 for category in self.qualifiers.values:
393 table = await conn.get_class_table(*category)
394 if table is not None:
395 sql = _select_placex(t)\
396 .add_columns(t.c.importance)\
397 .join(table, t.c.place_id == table.c.place_id)\
398 .where(t.c.class_ == category[0])\
399 .where(t.c.type == category[1])
401 if details.viewbox is not None and details.bounded_viewbox:
402 sql = sql.where(table.c.centroid.intersects(VIEWBOX_PARAM))
404 if details.near and details.near_radius is not None:
405 sql = sql.order_by(table.c.centroid.ST_Distance(NEAR_PARAM))\
406 .where(table.c.centroid.ST_DWithin(NEAR_PARAM,
410 sql = sql.where(t.c.country_code.in_(self.countries.values))
412 sql = sql.limit(LIMIT_PARAM)
413 rows.extend(await conn.execute(sql, bind_params))
415 results = nres.SearchResults()
417 result = nres.create_from_placex_row(row, nres.SearchResult)
419 result.accuracy = self.penalty + self.qualifiers.get_penalty((row.class_, row.type))
420 result.bbox = Bbox.from_wkb(row.bbox)
421 results.append(result)
426 class CountrySearch(AbstractSearch):
427 """ Search for a country name or country code.
429 def __init__(self, sdata: SearchData) -> None:
430 super().__init__(sdata.penalty)
431 self.countries = sdata.countries
434 async def lookup(self, conn: SearchConnection,
435 details: SearchDetails) -> nres.SearchResults:
436 """ Find results for the search in the database.
440 ccodes = self.countries.values
441 sql = _select_placex(t)\
442 .add_columns(t.c.importance)\
443 .where(t.c.country_code.in_(ccodes))\
444 .where(t.c.rank_address == 4)
446 if details.geometry_output:
447 sql = _add_geometry_columns(sql, t.c.geometry, details)
450 sql = sql.where(_exclude_places(t))
452 if details.viewbox is not None and details.bounded_viewbox:
453 sql = sql.where(lambda: t.c.geometry.intersects(VIEWBOX_PARAM))
455 if details.near is not None and details.near_radius is not None:
456 sql = sql.where(_within_near(t))
458 results = nres.SearchResults()
459 for row in await conn.execute(sql, _details_to_bind_params(details)):
460 result = nres.create_from_placex_row(row, nres.SearchResult)
462 result.accuracy = self.penalty + self.countries.get_penalty(row.country_code, 5.0)
463 result.bbox = Bbox.from_wkb(row.bbox)
464 results.append(result)
466 return results or await self.lookup_in_country_table(conn, details)
469 async def lookup_in_country_table(self, conn: SearchConnection,
470 details: SearchDetails) -> nres.SearchResults:
471 """ Look up the country in the fallback country tables.
473 # Avoid the fallback search when this is a more search. Country results
474 # usually are in the first batch of results and it is not possible
475 # to exclude these fallbacks.
477 return nres.SearchResults()
479 t = conn.t.country_name
480 tgrid = conn.t.country_grid
482 sql = sa.select(tgrid.c.country_code,
483 tgrid.c.geometry.ST_Centroid().ST_Collect().ST_Centroid()
485 tgrid.c.geometry.ST_Collect().ST_Expand(0).label('bbox'))\
486 .where(tgrid.c.country_code.in_(self.countries.values))\
487 .group_by(tgrid.c.country_code)
489 if details.viewbox is not None and details.bounded_viewbox:
490 sql = sql.where(tgrid.c.geometry.intersects(VIEWBOX_PARAM))
491 if details.near is not None and details.near_radius is not None:
492 sql = sql.where(_within_near(tgrid))
494 sub = sql.subquery('grid')
496 sql = sa.select(t.c.country_code,
497 t.c.name.merge(t.c.derived_name).label('name'),
498 sub.c.centroid, sub.c.bbox)\
499 .join(sub, t.c.country_code == sub.c.country_code)
501 if details.geometry_output:
502 sql = _add_geometry_columns(sql, sub.c.centroid, details)
504 results = nres.SearchResults()
505 for row in await conn.execute(sql, _details_to_bind_params(details)):
506 result = nres.create_from_country_row(row, nres.SearchResult)
508 result.bbox = Bbox.from_wkb(row.bbox)
509 result.accuracy = self.penalty + self.countries.get_penalty(row.country_code, 5.0)
510 results.append(result)
516 class PostcodeSearch(AbstractSearch):
517 """ Search for a postcode.
519 def __init__(self, extra_penalty: float, sdata: SearchData) -> None:
520 super().__init__(sdata.penalty + extra_penalty)
521 self.countries = sdata.countries
522 self.postcodes = sdata.postcodes
523 self.lookups = sdata.lookups
524 self.rankings = sdata.rankings
527 async def lookup(self, conn: SearchConnection,
528 details: SearchDetails) -> nres.SearchResults:
529 """ Find results for the search in the database.
532 pcs = self.postcodes.values
534 sql = sa.select(t.c.place_id, t.c.parent_place_id,
535 t.c.rank_search, t.c.rank_address,
536 t.c.postcode, t.c.country_code,
537 t.c.geometry.label('centroid'))\
538 .where(t.c.postcode.in_(pcs))
540 if details.geometry_output:
541 sql = _add_geometry_columns(sql, t.c.geometry, details)
543 penalty: SaExpression = sa.literal(self.penalty)
545 if details.viewbox is not None:
546 if details.bounded_viewbox:
547 sql = sql.where(t.c.geometry.intersects(VIEWBOX_PARAM))
549 penalty += sa.case((t.c.geometry.intersects(VIEWBOX_PARAM), 0.0),
550 (t.c.geometry.intersects(VIEWBOX2_PARAM), 0.5),
553 if details.near is not None:
554 if details.near_radius is not None:
555 sql = sql.where(_within_near(t))
556 sql = sql.order_by(t.c.geometry.ST_Distance(NEAR_PARAM))
559 sql = sql.where(t.c.country_code.in_(self.countries.values))
562 sql = sql.where(_exclude_places(t))
565 assert len(self.lookups) == 1
566 assert self.lookups[0].lookup_type == 'restrict'
567 tsearch = conn.t.search_name
568 sql = sql.where(tsearch.c.place_id == t.c.parent_place_id)\
569 .where((tsearch.c.name_vector + tsearch.c.nameaddress_vector)
570 .contains(self.lookups[0].tokens))
572 for ranking in self.rankings:
573 penalty += ranking.sql_penalty(conn.t.search_name)
574 penalty += sa.case(*((t.c.postcode == v, p) for v, p in self.postcodes),
578 sql = sql.add_columns(penalty.label('accuracy'))
579 sql = sql.order_by('accuracy').limit(LIMIT_PARAM)
581 results = nres.SearchResults()
582 for row in await conn.execute(sql, _details_to_bind_params(details)):
583 result = nres.create_from_postcode_row(row, nres.SearchResult)
585 result.accuracy = row.accuracy
586 results.append(result)
592 class PlaceSearch(AbstractSearch):
593 """ Generic search for an address or named place.
595 def __init__(self, extra_penalty: float, sdata: SearchData, expected_count: int) -> None:
596 super().__init__(sdata.penalty + extra_penalty)
597 self.countries = sdata.countries
598 self.postcodes = sdata.postcodes
599 self.housenumbers = sdata.housenumbers
600 self.qualifiers = sdata.qualifiers
601 self.lookups = sdata.lookups
602 self.rankings = sdata.rankings
603 self.expected_count = expected_count
606 async def lookup(self, conn: SearchConnection,
607 details: SearchDetails) -> nres.SearchResults:
608 """ Find results for the search in the database.
611 tsearch = conn.t.search_name
613 sql: SaLambdaSelect = sa.lambda_stmt(lambda:
614 _select_placex(t).where(t.c.place_id == tsearch.c.place_id))
617 if details.geometry_output:
618 sql = _add_geometry_columns(sql, t.c.geometry, details)
620 penalty: SaExpression = sa.literal(self.penalty)
621 for ranking in self.rankings:
622 penalty += ranking.sql_penalty(tsearch)
624 for lookup in self.lookups:
625 sql = sql.where(lookup.sql_condition(tsearch))
628 sql = sql.where(tsearch.c.country_code.in_(self.countries.values))
631 # if a postcode is given, don't search for state or country level objects
632 sql = sql.where(tsearch.c.address_rank > 9)
633 tpc = conn.t.postcode
634 pcs = self.postcodes.values
635 if self.expected_count > 1000:
636 # Many results expected. Restrict by postcode.
637 sql = sql.where(sa.select(tpc.c.postcode)
638 .where(tpc.c.postcode.in_(pcs))
639 .where(tsearch.c.centroid.ST_DWithin(tpc.c.geometry, 0.12))
642 # Less results, only have a preference for close postcodes
643 pc_near = sa.select(sa.func.min(tpc.c.geometry.ST_Distance(tsearch.c.centroid)))\
644 .where(tpc.c.postcode.in_(pcs))\
646 penalty += sa.case((t.c.postcode.in_(pcs), 0.0),
647 else_=sa.func.coalesce(pc_near, 2.0))
649 if details.viewbox is not None:
650 if details.bounded_viewbox:
651 if details.viewbox.area < 0.2:
652 sql = sql.where(tsearch.c.centroid.intersects(VIEWBOX_PARAM))
654 sql = sql.where(tsearch.c.centroid.ST_Intersects_no_index(VIEWBOX_PARAM))
655 elif self.expected_count >= 10000:
656 if details.viewbox.area < 0.5:
657 sql = sql.where(tsearch.c.centroid.intersects(VIEWBOX2_PARAM))
659 sql = sql.where(tsearch.c.centroid.ST_Intersects_no_index(VIEWBOX2_PARAM))
661 penalty += sa.case((t.c.geometry.intersects(VIEWBOX_PARAM), 0.0),
662 (t.c.geometry.intersects(VIEWBOX2_PARAM), 0.5),
665 if details.near is not None:
666 if details.near_radius is not None:
667 if details.near_radius < 0.1:
668 sql = sql.where(tsearch.c.centroid.ST_DWithin(NEAR_PARAM, NEAR_RADIUS_PARAM))
670 sql = sql.where(tsearch.c.centroid.ST_DWithin_no_index(NEAR_PARAM,
672 sql = sql.add_columns((-tsearch.c.centroid.ST_Distance(NEAR_PARAM))
673 .label('importance'))
674 sql = sql.order_by(sa.desc(sa.text('importance')))
676 if self.expected_count < 10000\
677 or (details.viewbox is not None and details.viewbox.area < 0.5):
679 penalty - sa.case((tsearch.c.importance > 0, tsearch.c.importance),
680 else_=0.75001-(sa.cast(tsearch.c.search_rank, sa.Float())/40)))
681 sql = sql.add_columns(t.c.importance)
684 sql = sql.add_columns(penalty.label('accuracy'))
686 if self.expected_count < 10000:
687 sql = sql.order_by(sa.text('accuracy'))
689 if self.housenumbers:
690 hnr_regexp = f"\\m({'|'.join(self.housenumbers.values)})\\M"
691 sql = sql.where(tsearch.c.address_rank.between(16, 30))\
692 .where(sa.or_(tsearch.c.address_rank < 30,
693 t.c.housenumber.op('~*')(hnr_regexp)))
695 # Cross check for housenumbers, need to do that on a rather large
696 # set. Worst case there are 40.000 main streets in OSM.
697 inner = sql.limit(10000).subquery()
699 # Housenumbers from placex
700 thnr = conn.t.placex.alias('hnr')
701 pid_list = array_agg(thnr.c.place_id) # type: ignore[no-untyped-call]
702 place_sql = sa.select(pid_list)\
703 .where(thnr.c.parent_place_id == inner.c.place_id)\
704 .where(thnr.c.housenumber.op('~*')(hnr_regexp))\
705 .where(thnr.c.linked_place_id == None)\
706 .where(thnr.c.indexed_status == 0)
709 place_sql = place_sql.where(thnr.c.place_id.not_in(sa.bindparam('excluded')))
711 place_sql = place_sql.where(self.qualifiers.sql_restrict(thnr))
713 numerals = [int(n) for n in self.housenumbers.values
714 if n.isdigit() and len(n) < 8]
715 interpol_sql: SaColumn
718 (not self.qualifiers or ('place', 'house') in self.qualifiers.values):
719 # Housenumbers from interpolations
720 interpol_sql = _make_interpolation_subquery(conn.t.osmline, inner,
722 # Housenumbers from Tiger
723 tiger_sql = sa.case((inner.c.country_code == 'us',
724 _make_interpolation_subquery(conn.t.tiger, inner,
728 interpol_sql = sa.null()
729 tiger_sql = sa.null()
731 unsort = sa.select(inner, place_sql.scalar_subquery().label('placex_hnr'),
732 interpol_sql.label('interpol_hnr'),
733 tiger_sql.label('tiger_hnr')).subquery('unsort')
734 sql = sa.select(unsort)\
735 .order_by(sa.case((unsort.c.placex_hnr != None, 1),
736 (unsort.c.interpol_hnr != None, 2),
737 (unsort.c.tiger_hnr != None, 3),
741 sql = sql.where(t.c.linked_place_id == None)\
742 .where(t.c.indexed_status == 0)
744 sql = sql.where(self.qualifiers.sql_restrict(t))
746 sql = sql.where(_exclude_places(tsearch))
747 if details.min_rank > 0:
748 sql = sql.where(sa.or_(tsearch.c.address_rank >= MIN_RANK_PARAM,
749 tsearch.c.search_rank >= MIN_RANK_PARAM))
750 if details.max_rank < 30:
751 sql = sql.where(sa.or_(tsearch.c.address_rank <= MAX_RANK_PARAM,
752 tsearch.c.search_rank <= MAX_RANK_PARAM))
753 if details.layers is not None:
754 sql = sql.where(_filter_by_layer(t, details.layers))
756 sql = sql.limit(LIMIT_PARAM)
758 results = nres.SearchResults()
759 for row in await conn.execute(sql, _details_to_bind_params(details)):
760 result = nres.create_from_placex_row(row, nres.SearchResult)
762 result.bbox = Bbox.from_wkb(row.bbox)
763 result.accuracy = row.accuracy
764 if self.housenumbers and row.rank_address < 30:
766 subs = _get_placex_housenumbers(conn, row.placex_hnr, details)
767 elif row.interpol_hnr:
768 subs = _get_osmline(conn, row.interpol_hnr, numerals, details)
770 subs = _get_tiger(conn, row.tiger_hnr, numerals, row.osm_id, details)
775 async for sub in subs:
776 assert sub.housenumber
777 sub.accuracy = result.accuracy
778 if not any(nr in self.housenumbers.values
779 for nr in sub.housenumber.split(';')):
783 # Only add the street as a result, if it meets all other
785 if (not details.excluded or result.place_id not in details.excluded)\
786 and (not self.qualifiers or result.category in self.qualifiers.values)\
787 and result.rank_address >= details.min_rank:
788 result.accuracy += 1.0 # penalty for missing housenumber
789 results.append(result)
791 results.append(result)