skip lookup with full names when there are none

[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 905b5c621cfe8cd99e28ec0bf13a2a5c9bff392a..c755f2a74f8a16e2d53ca30503549040685d0046 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,


@@ -214,16 +223,17 @@ class SearchBuilder:
 
         # Partial term to frequent. Try looking up by rare full names first.
         name_fulls = self.query.get_tokens(name, TokenType.WORD)
 
         # Partial term to frequent. Try looking up by rare full names first.
         name_fulls = self.query.get_tokens(name, TokenType.WORD)

-        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]
-            penalty += 1.2 * sum(t.penalty for t in addr_partials if not t.is_indexed)
-        # 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')
+        if 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]
+                penalty += 1.2 * sum(t.penalty for t in addr_partials if not t.is_indexed)
+            # 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.
 
         # To catch remaining results, lookup by name and address
         # We only do this if there is a reasonable number of results expected.


@@ -321,8 +331,15 @@ 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 +349,22 @@ 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