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[SPARK-38211][SQL][DOCS] Add SQL migration guide on restoring loose upcast from string to other types #35519

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[SPARK-38211][SQL][DOCS] Add SQL migration guide on restoring loose upcast from string to other types #35519

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2 changes: 1 addition & 1 deletion docs/sql-migration-guide.md
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Expand Up @@ -420,7 +420,7 @@ license: |
need to specify a value with units like "30s" now, to avoid being interpreted as milliseconds; otherwise,
the extremely short interval that results will likely cause applications to fail.

- When turning a Dataset to another Dataset, Spark will up cast the fields in the original Dataset to the type of corresponding fields in the target DataSet. In version 2.4 and earlier, this up cast is not very strict, e.g. `Seq("str").toDS.as[Int]` fails, but `Seq("str").toDS.as[Boolean]` works and throw NPE during execution. In Spark 3.0, the up cast is stricter and turning String into something else is not allowed, i.e. `Seq("str").toDS.as[Boolean]` will fail during analysis.
- When turning a Dataset to another Dataset, Spark will up cast the fields in the original Dataset to the type of corresponding fields in the target DataSet. In version 2.4 and earlier, this up cast is not very strict, e.g. `Seq("str").toDS.as[Int]` fails, but `Seq("str").toDS.as[Boolean]` works and throw NPE during execution. In Spark 3.0, the up cast is stricter and turning String into something else is not allowed, i.e. `Seq("str").toDS.as[Boolean]` will fail during analysis. To restore the behavior before 2.4.1, set `spark.sql.legacy.looseUpcast` to `true`.
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@MaxGekk MaxGekk Dec 8, 2023

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You modified the item for migration to 2.4.1. Does the 2.4.1 have the config spark.sql.legacy.looseUpcast. Seems not, see https://github.com/apache/spark/blob/v2.4.1-rc9/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala


## Upgrading from Spark SQL 2.3 to 2.4

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