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.
It is possible to do a full text search without an index. A simple query to print thetitleof each row that contains the wordfriendin itsbodyfield is:
This will also find related words such asfriendsandfriendly, since all these are reduced to the same normalized lexeme.
The query above specifies that theenglishconfiguration is to be used to parse and normalize the strings. Alternatively we could omit the configuration parameters:
This query will use the configuration set bydefault_text_search_config.
A more complex example is to select the ten most recent documents that containcreateandtablein thetitleorbody:
For clarity we omitted thecoalescefunction calls which would be needed to find rows that containNULLin 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.
We can create aGINindex (Section 12.9) to speed up text searches:
Notice that the 2-argument version ofto_tsvectoris 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 bydefault_text_search_config. If they were affected, the index contents might be inconsistent because different entries could containtsvectors 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 ofto_tsvectorwas used in the index above, only a query reference that uses the 2-argument version ofto_tsvectorwith the same configuration name will use that index. That is,WHERE to_tsvector('english', body) @@ 'a & b'can use the index, butWHERE 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.:
whereconfig_nameis a column in thepgwebtable. 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:
Another approach is to create a separatetsvectorcolumn to hold the output ofto_tsvector. This example is a concatenation oftitleandbody, usingcoalesceto ensure that one field will still be indexed when the other isNULL:
Then we create aGINindex to speed up the search:
Now we are ready to perform a fast full text search:
When using a separate column to store thetsvectorrepresentation, it is necessary to create a trigger to keep thetsvectorcolumn current anytimetitleorbodychanges.Section 12.4.3explains how to do that.
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 ondefault_text_search_config. Another advantage is that searches will be faster, since it will not be necessary to redo theto_tsvectorcalls to verify index matches. (This is more important when using a GiST index than a GIN index; seeSection 12.9.) The expression-index approach is simpler to set up, however, and it requires less disk space since thetsvectorrepresentation is not stored explicitly.