12.2. Tables and Indexes
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.
12.2.1. 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.
12.2.2. Creating Indexes #
We can create a GIN index ( Section 12.9 ) to speed up text searches:
CREATE INDEX pgweb_idx ON pgweb USING GIN (to_tsvector('english', body));
  
   Notice that the 2-argument version of
   
    to_tsvector
   
   is
    used.  Only text search functions that specify a configuration name can
    be used in expression indexes (
   
    Section 11.7
   
   ).
    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
   
    tsvector
   
   s 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 2-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
   
    Section 12.9
   
   .)  The expression-index approach is
    simpler to set up, however, and it requires less disk space since the
   
    tsvector
   
   representation is not stored explicitly.