Amazon Redshift will no longer support the creation of new Python UDFs starting Patch 198. Existing Python UDFs will continue to function until June 30, 2026. For more information, see the [ blog post ](https://amazonaws-china.com/blogs/big-data/amazon-redshift-python-user-defined-functions-will-reach-end-of-support-after-june-30-2026/). 

# System tables for troubleshooting data loads
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The following Amazon Redshift system tables can be helpful in troubleshooting data load issues:
+ Query [STL\$1LOAD\$1ERRORS](r_STL_LOAD_ERRORS.md) to discover the errors that occurred during specific loads.
+ Query [STL\$1FILE\$1SCAN](r_STL_FILE_SCAN.md) to view load times for specific files or to see if a specific file was even read.
+ Query [STL\$1S3CLIENT\$1ERROR](r_STL_S3CLIENT_ERROR.md) to find details for errors encountered while transferring data from Amazon S3.

**To find and diagnose load errors**

1. Create a view or define a query that returns details about load errors. The following example joins the STL\$1LOAD\$1ERRORS table to the STV\$1TBL\$1PERM table to match table IDs with actual table names. 

   ```
   create view loadview as
   (select distinct tbl, trim(name) as table_name, query, starttime,
   trim(filename) as input, line_number, colname, err_code,
   trim(err_reason) as reason
   from stl_load_errors sl, stv_tbl_perm sp
   where sl.tbl = sp.id);
   ```

1. Set the MAXERRORS option in your COPY command to a large enough value to enable COPY to return useful information about your data. If the COPY encounters errors, an error message directs you to consult the STL\$1LOAD\$1ERRORS table for details.

1. Query the LOADVIEW view to see error details. For example: 

   ```
   select * from loadview where table_name='venue';
   ```

   ```
     tbl   | table_name | query |         starttime          
   --------+------------+-------+----------------------------
    100551 | venue      | 20974 | 2013-01-29 19:05:58.365391 
   
   |     input      | line_number | colname | err_code |       reason
   +----------------+-------------+---------+----------+--------------------
   | venue_pipe.txt |           1 |       0 |     1214 | Delimiter not found
   ```

1. Fix the problem in the input file or the load script, based on the information that the view returns. Some typical load errors to watch for include: 
   + Mismatch between data types in table and values in input data fields.
   + Mismatch between number of columns in table and number of fields in input data.
   + Mismatched quotation marks. Amazon Redshift supports both single and double quotation marks; however, these quotation marks must be balanced appropriately.
   + Incorrect format for date/time data in input files.
   + Out-of-range values in input files (for numeric columns).
   + Number of distinct values for a column exceeds the limitation for its compression encoding.