HyukjinKwon commented on a change in pull request #25214: [SPARK-28461][SQL]
Pad Decimal numbers with trailing zeros to the scale of the column
URL: https://github.com/apache/spark/pull/25214#discussion_r316951489
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File path: docs/sql-migration-guide-upgrade.md
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@@ -159,6 +159,32 @@ license: |
- Since Spark 3.0, Dataset query fails if it contains ambiguous column
reference that is caused by self join. A typical example: `val df1 = ...; val
df2 = df1.filter(...);`, then `df1.join(df2, df1("a") > df2("a"))` returns an
empty result which is quite confusing. This is because Spark cannot resolve
Dataset column references that point to tables being self joined, and
`df1("a")` is exactly the same as `df2("a")` in Spark. To restore the behavior
before Spark 3.0, you can set `spark.sql.analyzer.failAmbiguousSelfJoin` to
`false`.
+ - Since Spark 3.0, we pad decimal numbers with trailing zeros to the scale
of the column for Hive result, for example:
Review comment:
To me, it looks not clear what Hive result is.
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