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I've noticed that when running under spark issing is not skipped.
It is propagated to the deserialiser/serializer which, in case of an int value explodes with:
TypeError(int() argument must be a string, a bytes-like object or a real number, not '_Missing')
Alos all the missing string fields are serialized as '<marshmallow.missing>'.
The text was updated successfully, but these errors were encountered:
albertocalderari
changed the title
Ehn deserializing/Serializing in a spark job _Missing fileds throw TypeErrrors
When deserializing/serializing in a spark job _Missing fileds throw TypeErrrors
Apr 12, 2022
I've noticed that when running under spark issing is not skipped.
It is propagated to the deserialiser/serializer which, in case of an int value explodes with:
TypeError(int() argument must be a string, a bytes-like object or a real number, not '_Missing')
Alos all the missing string fields are serialized as '<marshmallow.missing>'.
This oddly doesn't happen in a unit test, only when I execute within spark.
The exception gets thrown here: https://github.com/marshmallow-code/marshmallow/blob/dev/src/marshmallow/schema.py#L520
See below my pip freeze:
I'm running under Python 3.10.2.
The text was updated successfully, but these errors were encountered: