Implement Spark-compatible CAST from float/double to integer types

[andygrove]

What is the problem the feature request solves?

We currently delegate to DataFusion when casting from floating point to integer types and there are some differences in behavior compared to Spark.

Here is an example test from CometCastSuite:

  test("cast float to int") {
    castTest(generateFloats, DataTypes.IntegerType)
  }

  private def generateFloats(): DataFrame = {
    val r = new Random(0)
    val values = Range(0, dataSize).map(_ => r.nextFloat()) ++ Seq(Float.MaxValue, Float.MinPositiveValue,
      Float.MinValue, Float.NaN, Float.PositiveInfinity, Float.NegativeInfinity, 0.0f, -0.0f)
    values.toDF("a")
  }

Here are differences between Spark and Comet output:

== Results ==
!== Spark Answer - 1008 ==     == Comet Answer - 1008 ==
 struct<a:float,converted:int>   struct<a:float,converted:int>
![-3.4028235E38,-2147483648]     [-3.4028235E38,null]
![-Infinity,-2147483648]         [-Infinity,null]

Describe the potential solution

No response

Additional context

No response

[rohitrastogi]

Can I give this one a try?