-
Couldn't load subscription status.
- Fork 246
Closed
Labels
enhancementNew feature or requestNew feature or requestgood first issueGood for newcomersGood for newcomershelp wantedExtra attention is neededExtra attention is needed
Description
What is the problem the feature request solves?
We currently delegate to DataFusion when casting float/double to string and there are some differences in behavior compared to Spark.
- Spark uses
Infinityand-Infinityand DataFusion usesinfand-inf - Spark uses
Efor exponent and DataFusion usese
There can also be differences in formatting but where the values are semantically equivalent. For example, for the input 1.0499721536516571E-4:
Spark produces "1.0499721536516571E-4"
DataFusion produces: "0.00010499721536516571"
We should create a compatibility guide and include this information.
Here are some suggested values to test:
val testData = Seq(Float.NegativeInfinity, Float.PositiveInfinity,
Float.MinPositiveValue, Float.MinValue, Float.MaxValue, Float.NaN, -0.0f, 0.0f)Describe the potential solution
No response
Additional context
No response
Metadata
Metadata
Assignees
Labels
enhancementNew feature or requestNew feature or requestgood first issueGood for newcomersGood for newcomershelp wantedExtra attention is neededExtra attention is needed