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Hi, I have a Delta table where column mapping is enabled (minReaderVersion=2, minWriterVersion=5).
There is a reading application that does not understand that feature / protocol yet, so I thought that I could simply downgrade the Delta table to a lower protocol by rewriting the entire table (accepting that RENAME/DROP COLUMN will not work anymore):
Hi, I have a Delta table where column mapping is enabled (
minReaderVersion=2
,minWriterVersion=5
).There is a reading application that does not understand that feature / protocol yet, so I thought that I could simply downgrade the Delta table to a lower protocol by rewriting the entire table (accepting that
RENAME/DROP COLUMN
will not work anymore):However, the resulting table still has
minReaderVersion=2
,minWriterVersion=5
.Inconsistently, when using a different (new) name in
saveAsTable()
the new table will haveminReaderVersion=1
,minWriterVersion=2
.Is this plausible or a bug?
Is there a way to explicitly set the protocol / table properties as part of the
df.write
operation?I am using Spark 3.3 + Delta 2.2.0.
full code to reproduce
result
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