From: Sarah Hoffmann Date: Tue, 2 Apr 2024 14:17:21 +0000 (+0200) Subject: split search SQL in windowed search_name lookup and constraint search X-Git-Tag: deploy~10^2^2~4 X-Git-Url: https://git.openstreetmap.org./nominatim.git/commitdiff_plain/424ebd7fe9c63f85e8d94449715d52062a27d43d split search SQL in windowed search_name lookup and constraint search --- diff --git a/.pylintrc b/.pylintrc index c1384c00..27214bae 100644 --- a/.pylintrc +++ b/.pylintrc @@ -13,6 +13,6 @@ ignored-classes=NominatimArgs,closing # 'too-many-ancestors' is triggered already by deriving from UserDict # 'not-context-manager' disabled because it causes false positives once # typed Python is enabled. See also https://github.com/PyCQA/pylint/issues/5273 -disable=too-few-public-methods,duplicate-code,too-many-ancestors,bad-option-value,no-self-use,not-context-manager,use-dict-literal,chained-comparison,attribute-defined-outside-init +disable=too-few-public-methods,duplicate-code,too-many-ancestors,bad-option-value,no-self-use,not-context-manager,use-dict-literal,chained-comparison,attribute-defined-outside-init,too-many-boolean-expressions good-names=i,j,x,y,m,t,fd,db,cc,x1,x2,y1,y2,pt,k,v,nr diff --git a/nominatim/api/search/db_searches.py b/nominatim/api/search/db_searches.py index 3f294de7..c2ac4e16 100644 --- a/nominatim/api/search/db_searches.py +++ b/nominatim/api/search/db_searches.py @@ -645,97 +645,145 @@ class PlaceSearch(AbstractSearch): self.expected_count = expected_count - async def lookup(self, conn: SearchConnection, - details: SearchDetails) -> nres.SearchResults: - """ Find results for the search in the database. + def _inner_search_name_cte(self, conn: SearchConnection, + details: SearchDetails) -> 'sa.CTE': + """ Create a subquery that preselects the rows in the search_name + table. """ - t = conn.t.placex - tsearch = conn.t.search_name - - sql: SaLambdaSelect = sa.lambda_stmt(lambda: - _select_placex(t).where(t.c.place_id == tsearch.c.place_id)) - - - if details.geometry_output: - sql = _add_geometry_columns(sql, t.c.geometry, details) + t = conn.t.search_name penalty: SaExpression = sa.literal(self.penalty) for ranking in self.rankings: - penalty += ranking.sql_penalty(tsearch) + penalty += ranking.sql_penalty(t) + + sql = sa.select(t.c.place_id, t.c.search_rank, t.c.address_rank, + t.c.country_code, t.c.centroid, + t.c.name_vector, t.c.nameaddress_vector, + sa.case((t.c.importance > 0, t.c.importance), + else_=0.40001-(sa.cast(t.c.search_rank, sa.Float())/75)) + .label('importance'), + penalty.label('penalty')) for lookup in self.lookups: - sql = sql.where(lookup.sql_condition(tsearch)) + sql = sql.where(lookup.sql_condition(t)) if self.countries: - sql = sql.where(tsearch.c.country_code.in_(self.countries.values)) + sql = sql.where(t.c.country_code.in_(self.countries.values)) if self.postcodes: # if a postcode is given, don't search for state or country level objects - sql = sql.where(tsearch.c.address_rank > 9) - tpc = conn.t.postcode - pcs = self.postcodes.values - if self.expected_count > 5000: + sql = sql.where(t.c.address_rank > 9) + if self.expected_count > 10000: # Many results expected. Restrict by postcode. + tpc = conn.t.postcode sql = sql.where(sa.select(tpc.c.postcode) - .where(tpc.c.postcode.in_(pcs)) - .where(tsearch.c.centroid.within_distance(tpc.c.geometry, 0.12)) + .where(tpc.c.postcode.in_(self.postcodes.values)) + .where(t.c.centroid.within_distance(tpc.c.geometry, 0.12)) .exists()) - # Less results, only have a preference for close postcodes - pc_near = sa.select(sa.func.min(tpc.c.geometry.ST_Distance(tsearch.c.centroid)))\ + if details.viewbox is not None: + if details.bounded_viewbox: + sql = sql.where(t.c.centroid + .intersects(VIEWBOX_PARAM, + use_index=details.viewbox.area < 0.2)) + elif not self.postcodes and not self.housenumbers and self.expected_count >= 10000: + sql = sql.where(t.c.centroid + .intersects(VIEWBOX2_PARAM, + use_index=details.viewbox.area < 0.5)) + + if details.near is not None and details.near_radius is not None: + if details.near_radius < 0.1: + sql = sql.where(t.c.centroid.within_distance(NEAR_PARAM, + NEAR_RADIUS_PARAM)) + else: + sql = sql.where(t.c.centroid + .ST_Distance(NEAR_PARAM) < NEAR_RADIUS_PARAM) + + if self.housenumbers: + sql = sql.where(t.c.address_rank.between(16, 30)) + else: + if details.excluded: + sql = sql.where(_exclude_places(t)) + if details.min_rank > 0: + sql = sql.where(sa.or_(t.c.address_rank >= MIN_RANK_PARAM, + t.c.search_rank >= MIN_RANK_PARAM)) + if details.max_rank < 30: + sql = sql.where(sa.or_(t.c.address_rank <= MAX_RANK_PARAM, + t.c.search_rank <= MAX_RANK_PARAM)) + + inner = sql.limit(10000).order_by(sa.desc(sa.text('importance'))).subquery() + + sql = sa.select(inner.c.place_id, inner.c.search_rank, inner.c.address_rank, + inner.c.country_code, inner.c.centroid, inner.c.importance, + inner.c.penalty) + + # If the query is not an address search or has a geographic preference, + # preselect most important items to restrict the number of places + # that need to be looked up in placex. + if not self.housenumbers\ + and (details.viewbox is None or details.bounded_viewbox)\ + and (details.near is None or details.near_radius is not None)\ + and not self.qualifiers: + sql = sql.add_columns(sa.func.first_value(inner.c.penalty - inner.c.importance) + .over(order_by=inner.c.penalty - inner.c.importance) + .label('min_penalty')) + + inner = sql.subquery() + + sql = sa.select(inner.c.place_id, inner.c.search_rank, inner.c.address_rank, + inner.c.country_code, inner.c.centroid, inner.c.importance, + inner.c.penalty)\ + .where(inner.c.penalty - inner.c.importance < inner.c.min_penalty + 0.5) + + return sql.cte('searches') + + + async def lookup(self, conn: SearchConnection, + details: SearchDetails) -> nres.SearchResults: + """ Find results for the search in the database. + """ + t = conn.t.placex + tsearch = self._inner_search_name_cte(conn, details) + + sql = _select_placex(t).join(tsearch, t.c.place_id == tsearch.c.place_id) + + if details.geometry_output: + sql = _add_geometry_columns(sql, t.c.geometry, details) + + penalty: SaExpression = tsearch.c.penalty + + if self.postcodes: + tpc = conn.t.postcode + pcs = self.postcodes.values + + pc_near = sa.select(sa.func.min(tpc.c.geometry.ST_Distance(t.c.centroid)))\ .where(tpc.c.postcode.in_(pcs))\ .scalar_subquery() penalty += sa.case((t.c.postcode.in_(pcs), 0.0), 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 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)) - else: - penalty += sa.case((t.c.geometry.intersects(VIEWBOX_PARAM, use_index=False), 0.0), - (t.c.geometry.intersects(VIEWBOX2_PARAM, use_index=False), 0.5), - else_=1.0) + if details.viewbox is not None and not details.bounded_viewbox: + penalty += sa.case((t.c.geometry.intersects(VIEWBOX_PARAM, use_index=False), 0.0), + (t.c.geometry.intersects(VIEWBOX2_PARAM, use_index=False), 0.5), + else_=1.0) if details.near is not None: - if details.near_radius is not None: - if details.near_radius < 0.1: - sql = sql.where(tsearch.c.centroid.within_distance(NEAR_PARAM, - NEAR_RADIUS_PARAM)) - else: - sql = sql.where(tsearch.c.centroid - .ST_Distance(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: - 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_=0.40001-(sa.cast(tsearch.c.search_rank, sa.Float())/75))) - sql = sql.add_columns(t.c.importance) - + sql = sql.order_by(penalty - tsearch.c.importance) + sql = sql.add_columns(tsearch.c.importance) - sql = sql.add_columns(penalty.label('accuracy')) - if self.expected_count < 10000: - sql = sql.order_by(sa.text('accuracy')) + sql = sql.add_columns(penalty.label('accuracy'))\ + .order_by(sa.text('accuracy')) if self.housenumbers: hnr_list = '|'.join(self.housenumbers.values) - sql = sql.where(tsearch.c.address_rank.between(16, 30))\ - .where(sa.or_(tsearch.c.address_rank < 30, - 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. - inner = sql.limit(10000).subquery() + inner = sql.where(sa.or_(tsearch.c.address_rank < 30, + sa.func.RegexpWord(hnr_list, t.c.housenumber)))\ + .subquery() # Housenumbers from placex thnr = conn.t.placex.alias('hnr') @@ -783,14 +831,6 @@ class PlaceSearch(AbstractSearch): .where(t.c.indexed_status == 0) if self.qualifiers: sql = sql.where(self.qualifiers.sql_restrict(t)) - if details.excluded: - sql = sql.where(_exclude_places(tsearch)) - if details.min_rank > 0: - sql = sql.where(sa.or_(tsearch.c.address_rank >= MIN_RANK_PARAM, - tsearch.c.search_rank >= MIN_RANK_PARAM)) - if details.max_rank < 30: - sql = sql.where(sa.or_(tsearch.c.address_rank <= MAX_RANK_PARAM, - tsearch.c.search_rank <= MAX_RANK_PARAM)) if details.layers is not None: sql = sql.where(_filter_by_layer(t, details.layers))