[SPARK-53802][SDP] Support string values for user-specified schema in SDP tables #52517
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| assert(graph.tables.size == 1) | ||
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| val table = graph.table(graphIdentifier("table_with_string_schema")) | ||
| assert(table.specifiedSchema.isDefined) |
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nit: shall we simply compare table.specifiedSchema with an expected schema (for example, StructType.fromDDL(id LONG, name STRING))
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Oo yeah was not aware of that
| optional spark.connect.DataType schema = 7; | ||
| oneof schema { | ||
| spark.connect.DataType schema_data_type = 7; | ||
| string schema_string = 10; |
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since Spark 4.1 is not offically released. I wonder if we can change the sequence numbers here.
gengliangwang
approved these changes
Oct 7, 2025
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Thanks, merging to master |
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What changes were proposed in this pull request?
When defining a streaming table or materialized view, enable passing a string to its schema, in addition to a StructType. This mimics the flexibility of the
DataFrameReaderschema arg.E.g.
Why are the changes needed?
For flexibility and consistency with similar args.
Does this PR introduce any user-facing change?
Makes changes to unreleased protos.
How was this patch tested?
Was this patch authored or co-authored using generative AI tooling?