further restrict stop search criterion

[nominatim.git] / 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 66e7efaf7f729dec8fdc8f0f889295b6ed8a6f67..39c25f6b3118f4c0bb6c00b14482b0d453d57621 100644 (file)
--- 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.
 """
 """
 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
 import heapq
 
 from nominatim.api.types import SearchDetails, DataLayer


@@ -89,12 +89,14 @@ class SearchBuilder:
         if sdata is None:
             return
 
         if sdata is None:
             return
 

-        categories = self.get_search_categories(assignment)
+        near_items = self.get_near_items(assignment)
+        if near_items is not None and not near_items:
+            return # impossible compbination of near items and category parameter

 
         if assignment.name is None:
 
         if assignment.name is None:

-            if categories and not sdata.postcodes:
-                sdata.qualifiers = categories
-                categories = None
+            if near_items and not sdata.postcodes:
+                sdata.qualifiers = near_items
+                near_items = None

                 builder = self.build_poi_search(sdata)
             elif assignment.housenumber:
                 hnr_tokens = self.query.get_tokens(assignment.housenumber,
                 builder = self.build_poi_search(sdata)
             elif assignment.housenumber:
                 hnr_tokens = self.query.get_tokens(assignment.housenumber,


@@ -102,16 +104,19 @@ class SearchBuilder:
                 builder = self.build_housenumber_search(sdata, hnr_tokens, assignment.address)
             else:
                 builder = self.build_special_search(sdata, assignment.address,
                 builder = self.build_housenumber_search(sdata, hnr_tokens, assignment.address)
             else:
                 builder = self.build_special_search(sdata, assignment.address,

-                                                    bool(categories))
+                                                    bool(near_items))

         else:
             builder = self.build_name_search(sdata, assignment.name, assignment.address,
         else:
             builder = self.build_name_search(sdata, assignment.name, assignment.address,

-                                             bool(categories))
+                                             bool(near_items))

 
 

-        if categories:
-            penalty = min(categories.penalties)
-            categories.penalties = [p - penalty for p in categories.penalties]
+        if near_items:
+            penalty = min(near_items.penalties)
+            near_items.penalties = [p - penalty for p in near_items.penalties]

             for search in builder:
             for search in builder:

-                yield dbs.NearSearch(penalty + assignment.penalty, categories, search)
+                search_penalty = search.penalty
+                search.penalty = 0.0
+                yield dbs.NearSearch(penalty + assignment.penalty + search_penalty,
+                                     near_items, search)

         else:
             for search in builder:
                 search.penalty += assignment.penalty
         else:
             for search in builder:
                 search.penalty += assignment.penalty


@@ -158,11 +163,15 @@ class SearchBuilder:
             housenumber is the main name token.
         """
         sdata.lookups = [dbf.FieldLookup('name_vector', [t.token for t in hnrs], 'lookup_any')]
             housenumber is the main name token.
         """
         sdata.lookups = [dbf.FieldLookup('name_vector', [t.token for t in hnrs], 'lookup_any')]

+        expected_count = sum(t.count for t in hnrs)

 
         partials = [t for trange in address
                        for t in self.query.get_partials_list(trange)]
 
 
         partials = [t for trange in address
                        for t in self.query.get_partials_list(trange)]
 

-        if len(partials) != 1 or partials[0].count < 10000:
+        if expected_count < 8000:
+            sdata.lookups.append(dbf.FieldLookup('nameaddress_vector',
+                                                 [t.token for t in partials], 'restrict'))
+        elif 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 partials], 'lookup_all'))
         else:


@@ -173,7 +182,7 @@ class SearchBuilder:
                                 'lookup_any'))
 
         sdata.housenumbers = dbf.WeightedStrings([], [])
                                 'lookup_any'))
 
         sdata.housenumbers = dbf.WeightedStrings([], [])

-        yield dbs.PlaceSearch(0.05, sdata, sum(t.count for t in hnrs))
+        yield dbs.PlaceSearch(0.05, sdata, expected_count)

 
 
     def build_name_search(self, sdata: dbf.SearchData,
 
 
     def build_name_search(self, sdata: dbf.SearchData,


@@ -208,7 +217,7 @@ class SearchBuilder:
                            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))
 
                            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_count < 3000) and partials_indexed:
+        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
 
             yield penalty, exp_count, dbf.lookup_by_names(name_tokens, addr_tokens)
             return
 


@@ -321,8 +330,15 @@ class SearchBuilder:
                               self.query.get_tokens(assignment.postcode,
                                                     TokenType.POSTCODE))
         if assignment.qualifier:
                               self.query.get_tokens(assignment.postcode,
                                                     TokenType.POSTCODE))
         if assignment.qualifier:

-            sdata.set_qualifiers(self.query.get_tokens(assignment.qualifier,
-                                                       TokenType.QUALIFIER))
+            tokens = self.query.get_tokens(assignment.qualifier, TokenType.QUALIFIER)
+            if self.details.categories:
+                tokens = [t for t in tokens if t.get_category() in self.details.categories]
+                if not tokens:
+                    return None
+            sdata.set_qualifiers(tokens)
+        elif self.details.categories:
+            sdata.qualifiers = dbf.WeightedCategories(self.details.categories,
+                                                      [0.0] * len(self.details.categories))

 
         if assignment.address:
             sdata.set_ranking([self.get_addr_ranking(r) for r in assignment.address])
 
         if assignment.address:
             sdata.set_ranking([self.get_addr_ranking(r) for r in assignment.address])


@@ -332,23 +348,22 @@ class SearchBuilder:
         return sdata
 
 
         return sdata
 
 

-    def get_search_categories(self,
-                              assignment: TokenAssignment) -> Optional[dbf.WeightedCategories]:
-        """ Collect tokens for category search or use the categories
+    def get_near_items(self, assignment: TokenAssignment) -> Optional[dbf.WeightedCategories]:
+        """ Collect tokens for near items search or use the categories

             requested per parameter.
             Returns None if no category search is requested.
         """
             requested per parameter.
             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])
-
-        if self.details.categories:
-            return dbf.WeightedCategories(self.details.categories,
-                                          [0.0] * len(self.details.categories))
+        if assignment.near_item:
+            tokens: Dict[Tuple[str, str], float] = {}
+            for t in self.query.get_tokens(assignment.near_item, TokenType.NEAR_ITEM):
+                cat = t.get_category()
+                # The category of a near search will be that of near_item.
+                # Thus, if search is restricted to a category parameter,
+                # the two sets must intersect.
+                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()))

 
         return None
 
 
         return None