This topic shows how to use text search operators to search database tables and how to create indexes to speed up text searches.
The examples in the previous section illustrated full text matching using simple constant strings. This section shows how to search table data, optionally using indexes.
This section contains the following subtopics:
Searching a Table
It is possible to do a full text search without an index. A simple query to print the title of each row that contains the word friend in its body field is:
SELECT title
FROM pgweb
WHERE to_tsvector('english', body) @@ to_tsquery('english', 'friend');
This will also find related words such as friends and friendly, since all these are reduced to the same normalized lexeme.
The query above specifies that the english configuration is to be used to parse and normalize the strings. Alternatively we could omit the configuration parameters:
SELECT title
FROM pgweb
WHERE to_tsvector(body) @@ to_tsquery('friend');
This query will use the configuration set by default_text_search_config.
A more complex example is to select the ten most recent documents that contain create and table in the title or body:
SELECT title
FROM pgweb
WHERE to_tsvector(title || ' ' || body) @@ to_tsquery('create & table')
ORDER BY last_mod_date DESC
LIMIT 10;
For clarity we omitted the coalesce function calls which would be needed to find rows that contain NULL in one of the two fields.
Although these queries will work without an index, most applications will find this approach too slow, except perhaps for occasional ad-hoc searches. Practical use of text searching usually requires creating an index.
Creating Indexes
We can create a GIN index (GiST and GIN Indexes for Text Search) to speed up text searches:
CREATE INDEX pgweb_idx ON pgweb USING GIN (to_tsvector('english', body));
Notice that the two-argument version of to_tsvector is used. Only text search functions that specify a configuration name can be used in expression indexes. This is because the index contents must be unaffected by default_text_search_config. If they were affected, the index contents might be inconsistent because different entries could contain tsvectors that were created with different text search configurations, and there would be no way to guess which was which. It would be impossible to dump and restore such an index correctly.
Because the two-argument version of to_tsvector was used in the index above, only a query reference that uses the two-argument version of to_tsvector with the same configuration name will use that index. That is, WHERE to_tsvector('english', body) @@ 'a & b' can use the index, but WHERE to_tsvector(body) @@ 'a & b' cannot. This ensures that an index will be used only with the same configuration used to create the index entries.
It is possible to set up more complex expression indexes wherein the configuration name is specified by another column, e.g.:
CREATE INDEX pgweb_idx ON pgweb USING GIN (to_tsvector(config_name, body));
where config_name is a column in the pgweb table. This allows mixed configurations in the same index while recording which configuration was used for each index entry. This would be useful, for example, if the document collection contained documents in different languages. Again, queries that are meant to use the index must be phrased to match, e.g., WHERE to_tsvector(config_name, body) @@ 'a & b'.
Indexes can even concatenate columns:
CREATE INDEX pgweb_idx ON pgweb USING GIN (to_tsvector('english', title || ' ' || body));
Another approach is to create a separate tsvector column to hold the output of to_tsvector. To keep this column automatically up to date with its source data, use a stored generated column. This example is a concatenation of title and body, using coalesce to ensure that one field will still be indexed when the other is NULL:
ALTER TABLE pgweb
ADD COLUMN textsearchable_index_col tsvector
GENERATED ALWAYS AS (to_tsvector('english', coalesce(title, '') || ' ' || coalesce(body, ''))) STORED;
Then we create a GIN index to speed up the search:
CREATE INDEX textsearch_idx ON pgweb USING GIN (textsearchable_index_col);
Now we are ready to perform a fast full text search:
SELECT title FROM pgweb WHERE textsearchable_index_col @@ to_tsquery('create & table')
ORDER BY last_mod_date DESC LIMIT 10;
One advantage of the separate-column approach over an expression index is that it is not necessary to explicitly specify the text search configuration in queries in order to make use of the index. As shown in the example above, the query can depend on default_text_search_config. Another advantage is that searches will be faster, since it will not be necessary to redo the to_tsvector calls to verify index matches. (This is more important when using a GiST index than a GIN index; see GiST and GIN Indexes for Text Search.) The expression-index approach is simpler to set up, however, and it requires less disk space since the tsvector representation is not stored explicitly.
Parent topic: Using Full Text Search
