The SELECT
statement fetches predictions from the model table. The data is returned on the fly and the result set is not persisted.
But there are ways to save predictions data! You can save your predictions as a view using the CREATE VIEW
statement. Please note that a view is a saved query and does not store data like a table. Another way is to create a table using the CREATE TABLE
statement or insert your predictions into an existing table using the INSERT INTO
statement.
Here is the syntax for making batch predictions by joining one or more data source tables with one or more model tables:
Where:
integration_name.table_name1
, integration_name.table_name2
.mindsdb.model_name1
, mindsdb.model_name2
.Note that you can provide input to the models from the data tables and also in the WHERE
clause.
Follow this doc page to learn more about AI Tables.
Let’s make bulk predictions to predict the rental_price
value using the home_rentals_model
model joined with the data source table.
On execution, we get:
Follow this doc page to see examples of joining multiple data table with multiple models.
The SELECT
statement fetches predictions from the model table. The data is returned on the fly and the result set is not persisted.
But there are ways to save predictions data! You can save your predictions as a view using the CREATE VIEW
statement. Please note that a view is a saved query and does not store data like a table. Another way is to create a table using the CREATE TABLE
statement or insert your predictions into an existing table using the INSERT INTO
statement.
Here is the syntax for making batch predictions by joining one or more data source tables with one or more model tables:
Where:
integration_name.table_name1
, integration_name.table_name2
.mindsdb.model_name1
, mindsdb.model_name2
.Note that you can provide input to the models from the data tables and also in the WHERE
clause.
Follow this doc page to learn more about AI Tables.
Let’s make bulk predictions to predict the rental_price
value using the home_rentals_model
model joined with the data source table.
On execution, we get:
Follow this doc page to see examples of joining multiple data table with multiple models.