[SPARK-51065][SQL] Disallowing non-nullable schema when Avro encoding is used for TransformWithState #49751
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| "STATE_STORE_SCHEMA_MUST_BE_NULLABLE" : { | ||
| "message" : [ | ||
| "If schema evolution is enabled, all the fields in the schema for column family <columnFamilyName> must be nullable.", | ||
| "Please set the 'spark.sql.streaming.stateStore.encodingFormat' to 'UnsafeRow' or make the schema nullable.", |
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This is stored in the offset log though. So maybe just say that they should make schema nullable ?
anishshri-db
approved these changes
Jan 31, 2025
| schemas.map { case (colFamilyName, schema) => | ||
| // assert that each field is nullable if schema evolution is enabled | ||
| schema.valueSchema.fields.foreach { field => | ||
| if (!field.nullable && ensureNullableFields) { |
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Should we just always enforce this for transformWithState ?
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@ericm-db - can u add the SPARK ticket in the PR title ? |
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@ericm-db - also, is test failure related to the change ? |
ericm-db
changed the title
HyukjinKwon
changed the title
anishshri-db
reviewed
Feb 3, 2025
| schemas.map { case (colFamilyName, schema) => | ||
| // assert that each field is nullable if schema evolution is enabled | ||
| schema.valueSchema.fields.foreach { field => | ||
| if (!field.nullable && shouldCheckNullable && !isInternal(colFamilyName)) { |
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Why do we need to treat internal col families differently ?
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What changes were proposed in this pull request?
Right now, effectively set all fields in a schema to nullable, regardless of what the user specifies. If a field is specified as non-nullable and Avro encoding is used we will throw an error
Why are the changes needed?
In order to keep parity with the user-specified schema with the actual schema that we use.
Does this PR introduce any user-facing change?
This error is thrown if the schema is defined as non-nullable
How was this patch tested?
Unit tests
Was this patch authored or co-authored using generative AI tooling?
No