![]() ![]() Right comment:6 provides another example of that. In such cases, the characteristics of the output column would need to be defined by identifying its role in the query, pretty much as you say. For instance, any query involving an outer join could produce null values for a "not null" column. I'm still getting familiar with the ORM, but I imagine that there could easily be cases where column values are null even if the table columns are declared not null. Right the main issue here is that SearchVector (just like Concat for example) has been coalescing nulls to empty strings forever so we can't just change it now without breaking backward compatibility. This then becomes an issue of knowing when this might be guaranteed. I wouldn't expect to_tsvector to treat an empty string and null in the same way - this being SQL after all - but the aim would be to avoid coalesce where null could never occur. That would make filter(column_search=SearchQuery('simple', config='simple')) result in the desired to_tsvector('simple', column) plainto_tsquery('simple', 'keyword').įWIW that's already something we do for the SearchVectorExact lookup. Lhs, lhs_params = super().process_lhs(qn, connection) Self.lhs = SearchVector(self.lhs, config=config) If not isinstance(_field, SearchVectorField): SearchQuery, SearchVector, SearchVectorExact, SearchVectorFieldĬlass PostgresSimpleLookup(FieldGetDbPrepValueMixin, Lookup): search import SearchVector, SearchVectorExact, SearchVectorField django/contrib/postgres/lookups.py diff -git a/django/contrib/postgres/lookups.py b/django/contrib/postgres/lookups.pyįrom django.db.models import Lookup, Transformįrom django.db.models.lookups import Exact, FieldGetDbPrepValueMixinįrom.To_tsvector('simple', column) plainto_tsquery('simple', 'keyword')Ī patch is provided as a suggestion of how this issue might be fixed. This should produce the following more desirable SQL: What seems to be possible, however, is to modify the SQL generation to avoid using coalesce where it can be determined that the operand given to to_tsvector will not yield a null value. Unfortunately, the use of coalesce now blocks any application of an index on the column. To_tsvector('simple', coalesce(column, '')) plainto_tsquery('simple', 'keyword') The resulting SQL generated by Django is then as follows: ![]() (search=SearchVector("column", config="simple")).filter(search=SearchQuery("keyword", config="simple")) The Django documentation suggests using an annotation employing a SearchVector as follows: To_tsvector(column) plainto_tsquery('simple', 'keyword') (column_search=SearchQuery("keyword", config="simple")) Introducing a SearchQuery object employing the config parameter. "Only text search functions that specify a configuration name can be used in expression indexes Because the two-argument version of to_tsvector was used in the index above, only a query reference that uses the 2-argument version of to_tsvector with the same configuration name will use that index." However, the PostgreSQL documentation notes that such expressions will be unable to take advantage of indexes created on the column: To_tsvector(column) plainto_tsquery('keyword') If the length is greater than 120 minutes, the film is long.When following the PostgreSQL full-text search documentation for Django ( ), the search lookup.If the length is greater than 50 minutes and less than or equal to 120 minutes, the film is medium.If the lengh is less than 50 minutes, the film is short.Suppose you want to label the films by their length based on the following logic: Let’s take a look at the film table from the sample database. If you omit the ELSE clause, the CASE expression returns NULL. In case all conditions evaluate to false, the CASE expression returns the result ( else_result) that follows the ELSE keyword. Also, it immediately stops evaluating the next expression. For example, if the condition_2 evaluates to true, the CASE expression returns the result_2. If a condition evaluates to true, the CASE expression returns the corresponding result that follows the condition. When a condition evaluates to false, the CASE expression evaluates the next condition from the top to bottom until it finds a condition that evaluates to true. In this syntax, each condition ( condition_1, condition_2…) is a boolean expression that returns either true or false. END Code language: SQL (Structured Query Language) ( sql ) ![]()
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