Datasette facets can be used to add a faceted browse interface to any database table. With facets, tables are displayed along with a summary showing the most common values in specified columns. These values can be selected to further filter the table.
To turn on faceting for specific columns on a Datasette table view, add one or more ``_facet=COLUMN`` parameters to the URL. For example, if you want to turn on facets for the ``city_id`` and ``state`` columns, construct a URL that looks like this::
This works for both the HTML interface and the ``.json`` view. When enabled, facets will cause a ``facet_results`` block to be added to the JSON output, looking something like this::
If Datasette detects that a column is a foreign key, the ``"label"`` property will be automatically derived from the detected label column on the referenced table.
The default number of facet results returned is 30, controlled by the :ref:`setting_default_facet_size` setting. You can increase this on an individual page by adding ``?_facet_size=100`` to the query string, up to a maximum of :ref:`setting_max_returned_rows` (which defaults to 1000).
That last point is particularly important: Datasette runs a query for every column that is displayed on a page, which could get expensive - so to avoid slow load times it sets a time limit of just 50ms for each of those queries. This means suggested facets are unlikely to appear for tables with millions of records in them.
The performance of facets can be greatly improved by adding indexes on the columns you wish to facet by. Adding indexes can be performed using the ``sqlite3`` command-line utility. Here's how to add an index on the ``state`` column in a table called ``Food_Trucks``::
$ sqlite3 mydatabase.db
SQLite version 3.19.3 2017-06-27 16:48:08
Enter ".help" for usage hints.
sqlite> CREATE INDEX Food_Trucks_state ON Food_Trucks("state");
If your SQLite installation provides the ``json1`` extension (you can check using :ref:`JsonDataView_versions`) Datasette will automatically detect columns that contain JSON arrays of values and offer a faceting interface against those columns.
This is useful for modelling things like tags without needing to break them out into a new table.
If Datasette finds any columns that contain dates in the first 100 values, it will offer a faceting interface against the dates of those values. This works especially well against timestamp values such as ``2019-03-01 12:44:00``.