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https://issues.apache.org/jira/browse/SPARK-26054?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16686293#comment-16686293
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Marco Gaido commented on SPARK-26054:
-------------------------------------
I cannot reproduce this:
{code}
val df = Seq(AA("0101", "2500.98".toDouble), AA("0102",
"5690.9876".toDouble)).toDF
df.select($"id", $"amount", round($"amount", 2)).show()
{code}
returned
{code}
+----+--------------------+----------------+
| id| amount|round(amount, 2)|
+----+--------------------+----------------+
|0101|2500.980000000000...| 2500.98|
|0102|5690.987600000000...| 5690.99|
+----+--------------------+----------------+
{code}
Moreover in the image you posted the values are pretty weird... I mean also the
double ones are very different from what is represented in the strings...
> Creating a computed column applying the spark sql rounding on a column of
> type decimal affects the orginal column as well.
> --------------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-26054
> URL: https://issues.apache.org/jira/browse/SPARK-26054
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.4.0
> Reporter: Jaya Krishna
> Priority: Minor
> Attachments: sparksql-rounding.png
>
>
> When a computed column that rounds the value is added to a data frame, it is
> affecting the value of the original column as well. The behavior depends on
> the database column type - If it is either float or double, the result is as
> expected - the original column will have its own formatting and the computed
> column will be rounded as per the rounding definition specified for it.
> However if the column type in the database is decimal, then Spark SQL is
> applying the rounding even to the original column. Attached image has the
> spark sql code that shows the issue.
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