Directly use the built-in SQL function 'sqrt' in your queries without defining a UDF, as it is the most performant option.

Define a temporary SQL UDF using 'CREATE TEMPORARY FUNCTION sqrt AS 'your.package.SqrtUDF' USING JAR 'path/to/your/jarfile.jar'; and then use it in your queries.

Use a Python UDF (pandas_udf) for calculating the square root, as it offers better performance for numerical computations in Spark SQL.

Precompute the square root values and store them in a new column in your DataFrame to avoid runtime calculations.

Both B and C are correct approaches depending on the specific requirements and constraints of your project.