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https://issues.apache.org/jira/browse/SPARK-35342?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xinrong Meng updated SPARK-35342:
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Description:
In PySpark, {{DoubleType}} and {{FloatType}} could have NaN, whereas
{{DecimalType}} not.
Now, {{DecimalType,}} {{DoubleType,}} and {{FloatType}} data share the
{{FractionalOps}} class.
We would like to introduce the {{DecimalOps}} for NaN check.
> Introduce DecimalOps
> --------------------
>
> Key: SPARK-35342
> URL: https://issues.apache.org/jira/browse/SPARK-35342
> Project: Spark
> Issue Type: Sub-task
> Components: PySpark
> Affects Versions: 3.2.0
> Reporter: Xinrong Meng
> Priority: Major
>
> In PySpark, {{DoubleType}} and {{FloatType}} could have NaN, whereas
> {{DecimalType}} not.
> Now, {{DecimalType,}} {{DoubleType,}} and {{FloatType}} data share the
> {{FractionalOps}} class.
> We would like to introduce the {{DecimalOps}} for NaN check.
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