harshmotw-db opened a new pull request, #50741:
URL: https://github.com/apache/spark/pull/50741
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### What changes were proposed in this pull request?
Prior to this PR, in a very specific codepath in the non-SQL expression
`MapObjects`, an iterator is returned by df.collect() when codegen is disabled.
This can lead to non-deterministic behavior when codegen is disabled. For
example the following code could return incorrect results:
```
spark.conf.set("spark.sql.codegen.factoryMode", "NO_CODEGEN")
import org.apache.spark.sql.Row
case class Posting(transfer_type: String)
val df3 = spark.range(0, 8, 1, 1).selectExpr("""
case when id = 0 then array(named_struct('a', '1'), named_struct('a', '3'))
when id = 1 then null
when id = 2 then null
when id = 3 then null
when id = 4 then null
when id = 5 then null
when id = 6 then array(named_struct('a', '5'), named_struct('a', '7'))
else array(named_struct('a', '9'), named_struct('a', '11'))
end result
""")
val res6 = df3.select("result").map(row =>
if (row.get(0) != null) row.get(0).asInstanceOf[Seq[Row]].map(v =>
Posting(v.get(0).asInstanceOf[String]))
else null
).collect()
```
### Why are the changes needed?
The previous code that returned an iterator could give incorrect results
when a DataFrame represents scala case classes. This PR fixes it.
### Does this PR introduce _any_ user-facing change?
Users could see more deterministic behavior when forcing Interpreted mode
and using scala objects in DataFrames.
### How was this patch tested?
Existing tests
### Was this patch authored or co-authored using generative AI tooling?
No
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