zhengruifeng opened a new pull request, #43683:
URL: https://github.com/apache/spark/pull/43683
### What changes were proposed in this pull request?
Fix column resolution in DataFrame.drop
### Why are the changes needed?
```
from pyspark.sql.functions import col
# create first dataframe
left_df = spark.createDataFrame([(1, 'a'), (2, 'b'), (3, 'c')], ['join_key',
'value1'])
# create second dataframe
right_df = spark.createDataFrame([(1, 'aa'), (2, 'bb'), (4, 'dd')],
['join_key', 'value2'])
joined_df = left_df.join(right_df, on=left_df['join_key'] ==
right_df['join_key'], how='left')
display(joined_df)
cleaned_df = joined_df.drop(left_df['join_key'])
display(cleaned_df) # error here
JVM stacktrace:
org.apache.spark.sql.AnalysisException: [AMBIGUOUS_REFERENCE] Reference
`join_key` is ambiguous, could be: [`join_key`, `join_key`]. SQLSTATE: 42704
at
org.apache.spark.sql.errors.QueryCompilationErrors$.ambiguousReferenceError(QueryCompilationErrors.scala:1957)
at
org.apache.spark.sql.catalyst.expressions.package$AttributeSeq.resolve(package.scala:377)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolve(LogicalPlan.scala:156)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveQuoted(LogicalPlan.scala:167)
at org.apache.spark.sql.Dataset.$anonfun$drop$4(Dataset.scala:3071)
```
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
ci
### Was this patch authored or co-authored using generative AI tooling?
no
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