What causes SnowparkSQLException?

An unsupported operation was chained on a Snowpark DataFrame (e.g. a Python UDF registered with an incompatible return type). A column reference in the DataFrame plan points to a column that does not exist in the underlying table. The Snowpark session expired mid-operation and the generated SQL could not be submitted. A join between two DataFrames produced ambiguous column names that Snowflake's SQL engine could not resolve. A Python UDF raised an exception and the error was surfaced as SnowparkSQLException

How do I fix SnowparkSQLException?

Inspect the inner SQL error code in the exception message — it follows the format XXNNN and maps to a specific Snowflake SQL error.. Enable Snowpark query history: session.sql_simplifier_enabled = True and check QUERY_HISTORY for the generated SQL.. Verify column names by calling df.schema before executing an action.. Re-create the Snowpark session if it has been idle beyond the Snowflake network_policy timeout.. For UDF errors, test the Python function independently with sample inputs before registering it as a UDF.

High severityexecution

Power BI Refresh Error:
SnowparkSQLException

What does this error mean?

A Snowpark DataFrame action (collect, show, save, or a SQL-generating transformation) raised a SnowparkSQLException, indicating the generated SQL was rejected by Snowflake. The error wraps the underlying Snowflake SQL error code and message.

Common causes

1An unsupported operation was chained on a Snowpark DataFrame (e.g. a Python UDF registered with an incompatible return type)
2A column reference in the DataFrame plan points to a column that does not exist in the underlying table
3The Snowpark session expired mid-operation and the generated SQL could not be submitted
4A join between two DataFrames produced ambiguous column names that Snowflake's SQL engine could not resolve
5A Python UDF raised an exception and the error was surfaced as SnowparkSQLException

How to fix it

1Inspect the inner SQL error code in the exception message — it follows the format XXNNN and maps to a specific Snowflake SQL error.
2Enable Snowpark query history: session.sql_simplifier_enabled = True and check QUERY_HISTORY for the generated SQL.
3Verify column names by calling df.schema before executing an action.
4Re-create the Snowpark session if it has been idle beyond the Snowflake network_policy timeout.
5For UDF errors, test the Python function independently with sample inputs before registering it as a UDF.

Frequently asked questions

How do I get the underlying Snowflake SQL error from SnowparkSQLException?

Access exception.error_code for the numeric Snowflake error code and exception.message for the full error string. The error code maps directly to the Snowflake SQL error reference.

Does Snowpark automatically retry failed operations?

No. Snowpark does not retry SQL operations automatically. Implement retry logic in your Python code, checking exception.error_code to distinguish transient errors (e.g. 000630 timeout) from permanent errors.