phakawatfong opened a new pull request, #50205:
URL: https://github.com/apache/spark/pull/50205
when I parse ignoreColumnType=True when call the function, it cast all
values to be 'str' which causing the comparison between val1 and val2 to be
failed.
for example
val1 = 1505.76189560
val2= 1505.761896
assertDataFrameEqual(source_df, databricks_df, ignoreColumnType=True,)
I will convert the original data into string with this clause first
```
if ignoreColumnType:
actual = cast_columns_to_string(actual)
expected = cast_columns_to_string(expected)
.
.
compare_vals(val1, val2)
```
it will become string comparison instead of compare by using the tolerance
equation
'1505.76189560' != '1505.761896'
Hence assertError, even if the atol and rtol already assigned
### What changes were proposed in this pull request?
add more elif case to convert str to float and parse into tolerant
calculations
### Why are the changes needed?
I think it might not be the only way to fix it, but just to be your ideas
Thank you !
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Test on my local data source, comparing 2 dataframes
by patch the code into my local env.
### Was this patch authored or co-authored using generative AI tooling?
No
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