RussellSpitzer commented on issue #2040:
URL: https://github.com/apache/iceberg/issues/2040#issuecomment-1414466758
Both Spark and Iceberg have their own checks to determine whether an input
schema is valid for writing to a given table. The Spark checks are first and
require that all of the columns present in the output table are also present in
the Dataframe writing to that table. To fix this a flag is allowed to be set
which will disable the Spark Checks for compatible schema and instead it will
only use the Iceberg check. This is accomplished by setting
write.spark.accept-any-schema in the table properties.
```
public static final String SPARK_WRITE_ACCEPT_ANY_SCHEMA =
"write.spark.accept-any-schema";
```
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