HyukjinKwon commented on a change in pull request #33436:
URL: https://github.com/apache/spark/pull/33436#discussion_r673652611
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File path: docs/sql-migration-guide.md
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@@ -22,6 +22,10 @@ license: |
* Table of contents
{:toc}
+## Upgrading from Spark SQL 3.2 to 3.3
+
+ - Non-nullable schema was not supported properly in previous Spark version
so the output schema of `DataFrameReader.json(jsonDataset: Dataset[String])`
and `DataFrameReader.csv(csvDataset: Dataset[String])` became nullable which
also matches with `DataFrameReader.json(path: String)` and
`DataFrameReader.csv(path: String)`.
Review comment:
Hm, it gives you a wrong result only when the data contains `null` or
the field is missing for non-nullable types. If the data doesn't contain `null`
or all fields are present, it works all good.
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