[SPARK-53802][SDP] Support string values for user-specified schema in SDP tables #52517
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sryza
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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
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Oct 7, 2025
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Thanks, merging to master |
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…th `4.1.0-preview3` RC1 ### What changes were proposed in this pull request? This PR aims to update Spark Connect-generated Swift source code with Apache Spark `4.1.0-preview3` RC1. ### Why are the changes needed? There are many changes between Apache Spark 4.1.0-preview2 and preview3. - apache/spark#52685 - apache/spark#52613 - apache/spark#52553 - apache/spark#52532 - apache/spark#52517 - apache/spark#52514 - apache/spark#52487 - apache/spark#52328 - apache/spark#52200 - apache/spark#52154 - apache/spark#51344 To use the latest bug fixes and new messages to develop for new features of `4.1.0-preview3`. ``` $ git clone -b v4.1.0-preview3 https://github.com/apache/spark.git $ cd spark/sql/connect/common/src/main/protobuf/ $ protoc --swift_out=. spark/connect/*.proto $ protoc --grpc-swift_out=. spark/connect/*.proto // Remove empty GRPC files $ cd spark/connect $ grep 'This file contained no services' * | awk -F: '{print $1}' | xargs rm ``` ### Does this PR introduce _any_ user-facing change? Pass the CIs. ### How was this patch tested? Pass the CIs. I manually tested with `Apache Spark 4.1.0-preview3` (with the two SDP ignored tests). ``` $ swift test --no-parallel ... ✔ Test run with 203 tests in 21 suites passed after 19.088 seconds. ``` ``` ### Was this patch authored or co-authored using generative AI tooling? No. Closes #252 from dongjoon-hyun/SPARK-54043. Authored-by: Dongjoon Hyun <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]>
huangxiaopingRD
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Nov 25, 2025
… SDP tables ### 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 `DataFrameReader` schema arg](https://spark.apache.org/docs/latest/api/python/reference/pyspark.ss/api/pyspark.sql.streaming.DataStreamReader.schema.html#pyspark.sql.streaming.DataStreamReader.schema). E.g. ```python from pyspark.sql.functions import lit dp.materialized_view(schema="id LONG, name STRING") def table_with_string_schema(): return spark.range(5).withColumn("name", lit("test")) ``` ### 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? Closes apache#52517 from sryza/dataset-schema-string. Authored-by: Sandy Ryza <[email protected]> Signed-off-by: Gengliang Wang <[email protected]>
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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?