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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 -- This message was sent by Atlassian Jira (v8.3.4#803005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org