HyukjinKwon commented on a change in pull request #21586:
URL: https://github.com/apache/spark/pull/21586#discussion_r806382550
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File path: docs/sql-migration-guide-upgrade.md
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@@ -138,6 +138,8 @@ 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.
Review comment:
Yeah we should
##########
File path: docs/sql-migration-guide-upgrade.md
##########
@@ -138,6 +138,8 @@ 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.
Review comment:
are you interested in creating a PR (with a new JIRA) to fix the doc?
2.4 is EOL but I think it's good to fix the docs anyway.
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