I'm having an issue where a very large (30 gig) CSV import aborts at
various points due to small errors in a very tiny number of rows. As
each one is discovered, I can rewrite the import query to deal with
it, but it's a slow process to wait ten hours, get an error, track it
down, start over, wait 11 hours, get an error, etc. The size of the
file makes it difficult to correct it manually, and the export of the
file is done and cannot be easily redone, so the errors in the file
can't be correct by regenerating it from scratch.

Is there any option, flag, or setting which will cause H2 to simply
skip invalid rows, possibly with a log as to which were skipped and
why?

There's other solutions, including ways to clean the data somewhat, or
to split the file, etc, but they're generally inferior to a "skip and
log". We're talking, so far, less than a dozen bad rows out of ~40
million records.

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