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Posted to issues@spark.apache.org by "Thomas Graves (Jira)" <ji...@apache.org> on 2020/08/17 20:05:00 UTC
[jira] [Updated] (SPARK-32640) Spark 3.1 log(NaN) returns null
instead of NaN
[ https://issues.apache.org/jira/browse/SPARK-32640?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Thomas Graves updated SPARK-32640:
----------------------------------
Description:
I was testing Spark 3.1.0 and I noticed that if you take the log(NaN) it now returns a null whereas in Spark 3.0 it returned a NaN. I'm not an expert in this but I thought NaN was correct.
Spark 3.1.0 Example:
>>> df.selectExpr(["value", "log1p(value)"]).show()
+--------------+-----------------+
| value| LOG1P(value)|
+--------------+-----------------+
|-3.4028235E38| null|
|3.4028235E38|88.72283906194683|
| 0.0| 0.0|
| -0.0| -0.0|
| 1.0|0.6931471805599453|
| -1.0| null|
| NaN| null|
+--------------+-----------------+
Spark 3.0.0 example:
+-------------+------------------+
| value| LOG1P(value)|
+-------------+------------------+
|-3.4028235E38| null|
| 3.4028235E38| 88.72283906194683|
| 0.0| 0.0|
| -0.0| -0.0|
| 1.0|0.6931471805599453|
| -1.0| null|
| NaN| NaN|
+-------------+------------------+
Note it also does the same for log1p, log2, log10
was:
I was testing Spark 3.1.0 and I noticed that if you take the log(NaN) it now returns a null whereas in Spark 3.0 it returned a NaN. I'm not an expert in this but I thought NaN was correct.
Spark 3.1.0 Example:
>>> df.selectExpr(["value", "log1p(value)"]).show()
+-------------+------------------+
| value| LOG1P(value)|
+-------------+------------------+
|-3.4028235E38| null|
| 3.4028235E38| 88.72283906194683|
| 0.0| 0.0|
| -0.0| -0.0|
| 1.0|0.6931471805599453|
| -1.0| null|
| NaN| null|
+-------------+------------------+
Spark 3.0.0 example:
+-------------+-----------------+
| value| LOG(E(), value)|
+-------------+-----------------+
|-3.4028235E38| null|
| 3.4028235E38|88.72283906194683|
| 0.0| null|
| -0.0| null|
| 1.0| 0.0|
| -1.0| null|
| NaN| NaN|
+-------------+-----------------+
Note it also does the same for log1p, log2, log10
> Spark 3.1 log(NaN) returns null instead of NaN
> ----------------------------------------------
>
> Key: SPARK-32640
> URL: https://issues.apache.org/jira/browse/SPARK-32640
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.1.0
> Reporter: Thomas Graves
> Priority: Major
>
> I was testing Spark 3.1.0 and I noticed that if you take the log(NaN) it now returns a null whereas in Spark 3.0 it returned a NaN. I'm not an expert in this but I thought NaN was correct.
> Spark 3.1.0 Example:
> >>> df.selectExpr(["value", "log1p(value)"]).show()
> +--------------+-----------------+
> | value| LOG1P(value)|
> +--------------+-----------------+
> |-3.4028235E38| null|
> |3.4028235E38|88.72283906194683|
> | 0.0| 0.0|
> | -0.0| -0.0|
> | 1.0|0.6931471805599453|
> | -1.0| null|
> | NaN| null|
> +--------------+-----------------+
>
> Spark 3.0.0 example:
>
> +-------------+------------------+
> | value| LOG1P(value)|
> +-------------+------------------+
> |-3.4028235E38| null|
> | 3.4028235E38| 88.72283906194683|
> | 0.0| 0.0|
> | -0.0| -0.0|
> | 1.0|0.6931471805599453|
> | -1.0| null|
> | NaN| NaN|
> +-------------+------------------+
>
> Note it also does the same for log1p, log2, log10
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