itholic opened a new pull request, #43444:
URL: https://github.com/apache/spark/pull/43444
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### What changes were proposed in this pull request?
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This PR proposes to enhanced the `assertDataFrameEqual` function to support
an optional `returnUnequalRows` parameter. This parameter, will return the rows
from both DataFrames that are not equal when set to `True`.
### Why are the changes needed?
This enhancement provides users with an easier debugging experience by
directly pointing out the rows that do not match, eliminating the need for
manual comparison in case of large DataFrames.
### Does this PR introduce _any_ user-facing change?
Yes. An optional parameter `returnUnequalRows` has been introduced in the
`assertDataFrameEqual` function. When set to `True`, it will return unequal
rows for further analysis. For example:
```python
df1 = spark.createDataFrame(
data=[("1", 1000.00), ("2", 3000.00), ("3", 2000.00)], schema=["id",
"amount"])
df2 = spark.createDataFrame(
data=[("1", 1001.00), ("2", 3000.00), ("3", 2003.00)], schema=["id",
"amount"])
try:
assertDataFrameEqual(df1, df2, returnUnequalRows=True)
except PySparkAssertionError as e:
spark.createDataFrame(e.data).show()
```
The above code will produce the following DataFrame:
```
+-----------+-----------+
| _1| _2|
+-----------+-----------+
|{1, 1000.0}|{1, 1001.0}|
|{3, 2000.0}|{3, 2003.0}|
+-----------+-----------+
```
### How was this patch tested?
Added usage example into doctest.
### Was this patch authored or co-authored using generative AI tooling?
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No.
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