Improve strict schema string match with smarter matching #621
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linzhou-db
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Jan 7, 2025
| val newSchemaFieldNames = newSchemaFields.keySet | ||
| val currentSchemaFieldNames = currentSchemaFields.keySet | ||
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| // Ensure that all the new schema field names are a subset of current schema field names |
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I feel we could follow this Delta check in general. Right now I see few differences:
- For the Delta check, they ensure current schema fields are a subset new schema fields, but we're doing the opposite.
- They have checks on the nullability too.
I'm not familiar with the rationale behind the check either. Might worth to ask Ryan or Delta folks to make sure the change is safe.
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- Reversed the check
- Nullability is checked within DataType.equalsStructurally
| field.name -> field.dataType | ||
| }).toMap | ||
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| val schemaChangedException = new SparkException( |
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nit: do we want to include the info of culprit field in the error message?
| val newSchemaFieldNames = newSchemaFields.keySet | ||
| val currentSchemaFieldNames = currentSchemaFields.keySet | ||
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| // Ensure that all the new schema field names are a subset of current schema field names |
There was a problem hiding this comment.
I feel we could follow this Delta check in general. Right now I see few differences:
- For the Delta check, they ensure current schema fields are a subset new schema fields, but we're doing the opposite.
- They have checks on the nullability too.
I'm not familiar with the rationale behind the check either. Might worth to ask Ryan or Delta folks to make sure the change is safe.
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This PR improves the strict schema string match with smarter matching i.e. subset matching
Added unit test
Tested against DBR:
