cloud-fan commented on a change in pull request #31769:
URL: https://github.com/apache/spark/pull/31769#discussion_r589949658
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File path: docs/sql-migration-guide.md
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@@ -66,6 +66,8 @@ license: |
- In Spark 3.2, the output schema of `SHOW TBLPROPERTIES` becomes `key:
string, value: string` whether you specify the table property key or not. In
Spark 3.1 and earlier, the output schema of `SHOW TBLPROPERTIES` is `value:
string` when you specify the table property key. To restore the old schema with
the builtin catalog, you can set `spark.sql.legacy.keepCommandOutputSchema` to
`true`.
- In Spark 3.2, we support typed literals in the partition spec of INSERT
and ADD/DROP/RENAME PARTITION. For example, `ADD PARTITION(dt =
date'2020-01-01')` adds a partition with date value `2020-01-01`. In Spark 3.1
and earlier, the partition value will be parsed as string value `date
'2020-01-01'`, which is an illegal date value, and we add a partition with null
value at the end.
+
+ - In Spark 3.2, `DataFrameNaFunctions.replace()` no longer uses exact string
match for the input column names. Input column name having a dot in the name
(not nested) needs to be escaped with backtick \`. Now, it throws
`AnalysisException` if the column is not found in the data frame schema. It
also throws `IllegalArgumentException` if the input column name is a nested
column. In Spark 3.1 and earlier, it used to ignore invalid input column name
and nested column name.
Review comment:
looks good, maybe also explain a little bit why we need to make this
change:
```
... no longer uses exact string match for the input column names, to match
the
SQL syntax and support qualified column names. ...
```
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