Spark: Validate table columns don't conflict with metadata columns #3456
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aokolnychyi
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Nov 3, 2021
| return result; | ||
| } | ||
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| public static void validateMetadataColumnReferences(Schema tableSchema, Schema readSchema) { |
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I initially did this for Spark only. It may make sense to move it to DataTableScan in core.
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Looks good to me. I think this is going to be rare enough that we won't need another solution. |
rdblue
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Nov 3, 2021
kbendick
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Nov 3, 2021
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Left a comment but this looks good to me. Thanks @aokolnychyi!
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| table.updateSchema() | ||
| .addColumn(MetadataColumns.SPEC_ID.name(), Types.IntegerType.get()) | ||
| .addColumn(MetadataColumns.FILE_PATH.name(), Types.StringType.get()) | ||
| .commit(); |
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Eventually, would it make sense to fail here, in the updateSchema pathway?
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Maybe. I would like to avoid not allowing these names, but you're right that it would catch the problem earlier.
rdblue
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Nov 5, 2021
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This PR is a follow-up to #3373 and throws an exception when table columns conflict with metadata columns during reads.