Problem

You are using a Databricks SQL environment where columns defined with the DOUBLE data type lose precision when storing or comparing numeric values that exceed 15 significant digits. As a result, numeric values are silently rounded or truncated, leading to incorrect data storage, inaccurate query results, and unexpected behavior in equality comparisons or joins.

Cause

The DOUBLE data type in Databricks SQL is based on the IEEE 754 double-precision floating-point standard, which uses 64 bits to represent a numeric value. Of these 64 bits, only 53 are used to represent the significant digits, which limits the precision to approximately 15 significant decimal digits based on the numeric value. 

This means that when you store a numeric value with more than 15 digits—especially large integers or high-precision identifiers—the DOUBLE type instead rounds the value to the nearest representable binary approximation.

Solution

Switch the data type from DOUBLE to DECIMAL to allow the table to store and query values with higher precision. 

For example, changing the column to DECIMAL(38,0) allows the table to store and query values with up to 38 digits of precision. This ensures that the complete digits are preserved and displayed accurately.

To change the data type of the column:

1. Connect to your Databricks SQL environment.

2. Locate the affected Delta table and identify the column with the DOUBLE data type.

3. Run the following SQL command to alter the column data type to DECIMAL(p,s) where p and s are the required precision and scale required for the application.

```sql
ALTER TABLE <your-database>.<your-table>
ALTER COLUMN id TYPE DECIMAL(p,s); -- p and s are the required precision and scale for the application
```

4. Verify the change by querying the table and checking the data type of the column.