shehabgamin commented on code in PR #15168:
URL: https://github.com/apache/datafusion/pull/15168#discussion_r2061232126
##########
datafusion/sqllogictest/src/engines/datafusion_engine/normalize.rs:
##########
@@ -193,7 +192,7 @@ macro_rules! get_row_value {
///
/// Floating numbers are rounded to have a consistent representation with the
Postgres runner.
///
-pub fn cell_to_string(col: &ArrayRef, row: usize) -> Result<String> {
+pub fn cell_to_string(col: &ArrayRef, row: usize, is_spark_path: bool) ->
Result<String> {
Review Comment:
@alamb While digging into your suggestion
(https://github.com/apache/datafusion/pull/15168#discussion_r2004518126), I
realized that we don't need to write an entire engine for Spark. All we care
about is the logic in `cell_to_string`. For now, I haven’t created a
Spark-specific `spark_cell_to_string`, since the issues we originally
encountered with `sqllogictest` were related only to `Float64` precision. We
can always create a Spark-specific`spark_cell_to_string` later if we find that
other changes are needed.
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