MaxGekk commented on code in PR #35519:
URL: https://github.com/apache/spark/pull/35519#discussion_r1420919590
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docs/sql-migration-guide.md:
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@@ -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`.
Review Comment:
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
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