comphead commented on issue #5544: URL: https://github.com/apache/datafusion-comet/issues/5544#issuecomment-5546992022
Another edge case is
```
import org.apache.spark.sql.functions._
Seq(Option(1)).toDF("k").write.mode("overwrite").parquet("/tmp/comet_repro/empty_map")
val df = spark.read.parquet("/tmp/comet_repro/empty_map")
val emptyMapping = typedLit(Map.empty[Int, List[Int]])
println(emptyMapping.expr.dataType) //
MapType(IntegerType,ArrayType(IntegerType,false),true)
val out = df.select(array(emptyMapping($"k")).as("a"))
out.show()
println(new
org.apache.comet.ExtendedExplainInfo().getFallbackReasons(out.queryExecution.executedPlan))
```
I still see a fallback for it
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