X-Git-Url: https://git.openstreetmap.org./nominatim.git/blobdiff_plain/cc45930ef90c82bb332e9ce9bf418bd763f618b2..d8ed565bce27c638074fbc6f1961dfc0d160e312:/nominatim/api/search/db_search_builder.py diff --git a/nominatim/api/search/db_search_builder.py b/nominatim/api/search/db_search_builder.py index 2a3153be..7826925a 100644 --- a/nominatim/api/search/db_search_builder.py +++ b/nominatim/api/search/db_search_builder.py @@ -7,7 +7,7 @@ """ Convertion from token assignment to an abstract DB search. """ -from typing import Optional, List, Tuple, Iterator +from typing import Optional, List, Tuple, Iterator, Dict import heapq from nominatim.api.types import SearchDetails, DataLayer @@ -15,7 +15,6 @@ from nominatim.api.search.query import QueryStruct, Token, TokenType, TokenRange from nominatim.api.search.token_assignment import TokenAssignment import nominatim.api.search.db_search_fields as dbf import nominatim.api.search.db_searches as dbs -from nominatim.api.logging import log def wrap_near_search(categories: List[Tuple[str, str]], @@ -112,9 +111,11 @@ class SearchBuilder: penalty = min(categories.penalties) categories.penalties = [p - penalty for p in categories.penalties] for search in builder: - yield dbs.NearSearch(penalty, categories, search) + yield dbs.NearSearch(penalty + assignment.penalty, categories, search) else: - yield from builder + for search in builder: + search.penalty += assignment.penalty + yield search def build_poi_search(self, sdata: dbf.SearchData) -> Iterator[dbs.AbstractSearch]: @@ -156,13 +157,22 @@ class SearchBuilder: """ Build a simple address search for special entries where the housenumber is the main name token. """ - partial_tokens: List[int] = [] - for trange in address: - partial_tokens.extend(t.token for t in self.query.get_partials_list(trange)) + sdata.lookups = [dbf.FieldLookup('name_vector', [t.token for t in hnrs], 'lookup_any')] + + partials = [t for trange in address + for t in self.query.get_partials_list(trange)] + + if len(partials) != 1 or partials[0].count < 10000: + sdata.lookups.append(dbf.FieldLookup('nameaddress_vector', + [t.token for t in partials], 'lookup_all')) + else: + sdata.lookups.append( + dbf.FieldLookup('nameaddress_vector', + [t.token for t + in self.query.get_tokens(address[0], TokenType.WORD)], + 'lookup_any')) - sdata.lookups = [dbf.FieldLookup('name_vector', [t.token for t in hnrs], 'lookup_any'), - dbf.FieldLookup('nameaddress_vector', partial_tokens, 'lookup_all') - ] + sdata.housenumbers = dbf.WeightedStrings([], []) yield dbs.PlaceSearch(0.05, sdata, sum(t.count for t in hnrs)) @@ -187,69 +197,43 @@ class SearchBuilder: be searched for. This takes into account how frequent the terms are and tries to find a lookup that optimizes index use. """ - penalty = 0.0 # extra penalty currently unused - + penalty = 0.0 # extra penalty name_partials = self.query.get_partials_list(name) - exp_name_count = min(t.count for t in name_partials) - addr_partials = [] - for trange in address: - addr_partials.extend(self.query.get_partials_list(trange)) + name_tokens = [t.token for t in name_partials] + + addr_partials = [t for r in address for t in self.query.get_partials_list(r)] addr_tokens = [t.token for t in addr_partials] + partials_indexed = all(t.is_indexed for t in name_partials) \ and all(t.is_indexed for t in addr_partials) + exp_count = min(t.count for t in name_partials) / (2**(len(name_partials) - 1)) - if (len(name_partials) > 3 or exp_name_count < 1000) and partials_indexed: - # Lookup by name partials, use address partials to restrict results. - lookup = [dbf.FieldLookup('name_vector', - [t.token for t in name_partials], 'lookup_all')] - if addr_tokens: - lookup.append(dbf.FieldLookup('nameaddress_vector', addr_tokens, 'restrict')) - yield penalty, exp_name_count, lookup - return - - exp_addr_count = min(t.count for t in addr_partials) if addr_partials else exp_name_count - if exp_addr_count < 1000 and partials_indexed: - # Lookup by address partials and restrict results through name terms. - # Give this a small penalty because lookups in the address index are - # more expensive - yield penalty + exp_addr_count/5000, exp_addr_count,\ - [dbf.FieldLookup('name_vector', [t.token for t in name_partials], 'restrict'), - dbf.FieldLookup('nameaddress_vector', addr_tokens, 'lookup_all')] + if (len(name_partials) > 3 or exp_count < 8000) and partials_indexed: + yield penalty, exp_count, dbf.lookup_by_names(name_tokens, addr_tokens) return # Partial term to frequent. Try looking up by rare full names first. name_fulls = self.query.get_tokens(name, TokenType.WORD) - rare_names = list(filter(lambda t: t.count < 1000, name_fulls)) + fulls_count = sum(t.count for t in name_fulls) # At this point drop unindexed partials from the address. # This might yield wrong results, nothing we can do about that. if not partials_indexed: addr_tokens = [t.token for t in addr_partials if t.is_indexed] - log().var_dump('before', penalty) penalty += 1.2 * sum(t.penalty for t in addr_partials if not t.is_indexed) - log().var_dump('after', penalty) - if rare_names: - # Any of the full names applies with all of the partials from the address - lookup = [dbf.FieldLookup('name_vector', [t.token for t in rare_names], 'lookup_any')] - if addr_tokens: - lookup.append(dbf.FieldLookup('nameaddress_vector', addr_tokens, 'restrict')) - yield penalty, sum(t.count for t in rare_names), lookup + # Any of the full names applies with all of the partials from the address + yield penalty, fulls_count / (2**len(addr_partials)),\ + dbf.lookup_by_any_name([t.token for t in name_fulls], addr_tokens, + 'restrict' if fulls_count < 10000 else 'lookup_all') # To catch remaining results, lookup by name and address # We only do this if there is a reasonable number of results expected. - if min(exp_name_count, exp_addr_count) < 10000: - if all(t.is_indexed for t in name_partials): - lookup = [dbf.FieldLookup('name_vector', - [t.token for t in name_partials], 'lookup_all')] - else: - # we don't have the partials, try with the non-rare names - non_rare_names = [t.token for t in name_fulls if t.count >= 1000] - if not non_rare_names: - return - lookup = [dbf.FieldLookup('name_vector', non_rare_names, 'lookup_any')] + exp_count = exp_count / (2**len(addr_partials)) if addr_partials else exp_count + if exp_count < 10000 and all(t.is_indexed for t in name_partials): + lookup = [dbf.FieldLookup('name_vector', name_tokens, 'lookup_all')] if addr_tokens: lookup.append(dbf.FieldLookup('nameaddress_vector', addr_tokens, 'lookup_all')) - yield penalty + 0.1 * max(0, 5 - len(name_partials) - len(addr_tokens)),\ - min(exp_name_count, exp_addr_count), lookup + penalty += 0.35 * max(0, 5 - len(name_partials) - len(addr_tokens)) + yield penalty, exp_count, lookup def get_name_ranking(self, trange: TokenRange) -> dbf.FieldRanking: @@ -355,12 +339,13 @@ class SearchBuilder: Returns None if no category search is requested. """ if assignment.category: - tokens = [t for t in self.query.get_tokens(assignment.category, - TokenType.CATEGORY) - if not self.details.categories - or t.get_category() in self.details.categories] - return dbf.WeightedCategories([t.get_category() for t in tokens], - [t.penalty for t in tokens]) + tokens: Dict[Tuple[str, str], float] = {} + for t in self.query.get_tokens(assignment.category, TokenType.CATEGORY): + cat = t.get_category() + if (not self.details.categories or cat in self.details.categories)\ + and t.penalty < tokens.get(cat, 1000.0): + tokens[cat] = t.penalty + return dbf.WeightedCategories(list(tokens.keys()), list(tokens.values())) if self.details.categories: return dbf.WeightedCategories(self.details.categories,