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Description

MindsDB provides two ways of using the UPDATE statement:
  1. The regular UPDATE statement updates specific column values in an existing table.
  2. The UPDATE FROM SELECT statement updates data in an existing table from a subselect query. It can be used as an alternative to CREATE TABLE or INSERT INTO to store predictions.

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Syntax

Here is an example of the regular UPDATE statement: 
UPDATE integration_name.table_name
SET column_name = new_value
WHERE column_name = old_value
Please replace the placeholders as follows:
  • integration_name is the name of the connected data source.
  • table_name is the table name within that data source.
  • column_name is the column name within that table.
And here is an example of the UPDATE FROM SELECT statement that updates a table with predictions made within MindsDB: 
UPDATE
    integration_to_be_updated.table_to_be_updated
SET
    column_to_be_updated = prediction_data.predicted_value_column,
FROM 
    (
        SELECT p.predicted_value_column, p.column1, p.column2
        FROM integration_name.table_name as t
        JOIN model_name as p
    ) AS prediction_data
WHERE
    column1 = prediction_data.column1
    AND column2 = prediction_data.column2
Below is an alternative for the UPDATE FROM SELECT statement that updates a table with predictions. This syntax is easier to write. 
UPDATE
    integration_to_be_updated.table_to_be_updated
ON 
    column1, column2
FROM 
    (
        SELECT p.predicted_value_column as column_to_be_updated, p.column1, p.column2
        FROM integration_name.table_name as t
        JOIN model_name as p
    )
The steps followed by the syntax:
  • It executes query from the FROM clause to get the output data. In our example, we query for predictions, but it could be a simple select from another table. Please note that it is aliased as prediction_data.
  • It updates all rows from the table_to_be_updated table (that belongs to the integration_to_be_updated integration) that match the WHERE clause criteria. The rows are updated with values as defined in the SET clause.
It is recommended to use the primary key column(s) in the WHERE clause (here, column1 and column2), as the primary key column(s) uniquely identify each row. Otherwise, the UPDATE statement may lead to unexpected results by altering rows that you didn’t want to affect.