Amazon Redshift will no longer support the use of Python UDFs after June 30, 2026.
We will start enforcing it in phases. For more information on the details of Python end of life
and migration options, see the
blog post
Optimizing storage for narrow tables
If you have a table with very few columns but a very large number of rows, the three hidden metadata identity columns (INSERT_XID, DELETE_XID, ROW_ID) will consume a disproportionate amount of the disk space for the table.
In order to optimize compression of the hidden columns, load the table in a single COPY transaction where possible. If you load the table with multiple separate COPY commands, the INSERT_XID column will not compress well. You must perform a vacuum operation if you use multiple COPY commands, but it will not improve compression of INSERT_XID.