Understanding the Snowflake SQL Compilation Error: Object ‘SNOWPARK_TEMP_STAGE_FLGVIWVUC’ Already Exists

When working with Snowflake and writing data to temporary tables, users often encounter a frustrating error message that can be difficult to resolve. In this article, we will delve into the specifics of the “SQL compilation error: Object ‘SNOWPARK_TEMP_STAGE FLGVIWVUC’ already exists” issue in Snowflake and provide a solution using try-except blocks and Snowflake-specific features.

Background on Snowflake Temporary Tables

Temporary tables in Snowflake are stored in memory and do not persist across sessions or instance restarts. They are used to optimize query performance by allowing for the temporary storage of data that can be used in subsequent queries without having to load it into a regular table.

Temporary tables have three types:

• SNOWPARK_TEMP_FILE_FORMAT_XXXX: Represents file formats used when writing data to disk.
• SNOWPARK_TEMP_STAGE_XXXX: Represents stages used for storing and retrieving data from disk.
• SNOWPARK Temp Storage: Represents the storage of data on disk.

The Error

The “SQL compilation error: Object ‘SNOWPARK_TEMP_STAGE FLGVIWVUC’ already exists” error occurs when trying to create a new temporary stage with an existing name. This can happen if another session or process has created the stage and not dropped it, or if Snowflake is experiencing issues that cause stages to be duplicated.

Possible Causes

There are several reasons why this error may occur:

• Concurrent Session Creation: When multiple sessions try to create temporary tables with the same name simultaneously, they may overwrite each other’s creations.
• Snowflake Instance Issues: Downtime or maintenance on a Snowflake instance can cause issues with stage creation and deletion.
• Code Errors: Incorrect code that fails to handle errors properly can lead to duplicated stages.

Solution: Using Try-Except Blocks

To resolve the “SQL compilation error: Object ‘SNOWPARK_TEMP_STAGE FLGVIWVUC’ already exists” issue, we need to use try-except blocks to catch and handle any exceptions thrown by Snowflake when trying to create a new temporary stage. We will also drop any existing stages with the same name using DROP STAGE IF EXISTS statements.

Modified Code

The following code snippet demonstrates how to modify your Snowflake writing code to include try-except blocks for handling duplicate stage errors:

# Import necessary modules and initialize the Snowflake session
import re
from snowflake.snowpark.context import get_active_session

session = get_active_session()

def try_to_write_pd_to_table(my_session, my_df, my_tablename, my_db, my_sch):
    # Try to create the temporary stage
    try:
        my_session.write_pandas(my_df, my_tablename, database=f"{my_db}", schema="{my_sch}", auto_create_table=True, overwrite=True)
    except Exception as e1:
        # Check for duplicate file format errors
        tmp_file_format = re.findall('SNOWPARK_TEMP_FILE_FORMAT_[A-Z]{10}', str(e1))
        if len(tmp_file_format) > 0:
            my_session.sql(f'DROP FILE FORMAT IF EXISTS {my_db}.{my_sch}.{tmp_file_format[0]};').collect()
        
        # Check for duplicate stage errors
        tmp_stage = re.findall('SNOWPARK_TEMP_STAGE_[A-Z]{10}', str(e1))
        if len(tmp_stage) > 0:
            my_session.sql(f'DROP STAGE IF EXISTS {my_db}.{my_sch}.{tmp_stage[0]};').collect()
        
        # Try again to create the temporary stage
        try:
            my_session.write_pandas(my_df, my_tablename, database=f"{my_db}", schema="{my_sch}", auto_create_table=True, overwrite=True)
        except Exception as e2:
            # Repeat the process for duplicate file format errors
            tmp_file_format = re.findall('SNOWPARK_TEMP_FILE_FORMAT_[A-Z]{10}', str(e2))
            if len(tmp_file_format) > 0:
                my_session.sql(f'DROP FILE FORMAT IF EXISTS {my_db}.{my_sch}.{tmp_file_format[0]};').collect()
            
            # Repeat the process for duplicate stage errors
            tmp_stage = re.findall('SNOWPARK_TEMP_STAGE_[A-Z]{10}', str(e2))
            if len(tmp_stage) > 0:
                my_session.sql(f'DROP STAGE IF EXISTS {my_db}.{my_sch}.{tmp_stage[0]};').collect()
            
            # Repeat the process again to finally create the temporary stage
            try:
                my_session.write_pandas(my_df, my_tablename, database=f"{my_db}", schema="{my_sch}", auto_create_table=True, overwrite=True)
            except Exception as e3:
                # Handle any remaining errors
                print(f"Error occurred: {e3}")

try_to_write_pd_to_table(session, df_final, "TEMPTABLE", 'LLM_DATABASE', 'ML_SCHEMA');

Additional Best Practices

In addition to using try-except blocks for handling duplicate stage errors, consider the following best practices when working with Snowflake temporary tables:

• Use meaningful table names: Choose names that are descriptive and clear to avoid confusion.
• Handle errors properly: Catch any exceptions thrown by Snowflake and handle them accordingly to prevent data loss or corruption.
• Optimize query performance: Use Snowflake’s built-in optimization features, such as CTEs (Common Table Expressions) and window functions, to improve query performance.

By following these best practices and using try-except blocks for handling duplicate stage errors, you can minimize the risk of encountering the “SQL compilation error: Object ‘SNOWPARK_TEMP_STAGE FLGVIWVUC’ already exists” issue in Snowflake.

Last modified on 2024-11-08