RussellSpitzer commented on issue #7657:
URL: https://github.com/apache/iceberg/issues/7657#issuecomment-1554603272

   The `rewrite-datafiles` is almost certainly a red herring. It shouldn't have 
any effect on the table if it failed since it is transactional like all Iceberg 
operations. It may be that this is coincidental or perhaps the system has just 
run out of some resource like disk space.
   
   > Spark will attempt to load and sort the entire table before inserting the 
new batch even though we are partitioning by loaded_at which should never need 
more than one partition.
   
   This is quite confusing to me. An "append" should never require reading 
anything from the target table. The source though will have a shuffle applied 
to it based on the `write.distribution-mode` of the table. We recently did 
change the default to hash which would request that the incoming data be 
shuffled by the partition of the destination table. If you are confident it 
does not need to be shuffled you can always set the mode to `none`.


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