MaxGekk commented on code in PR #44872:
URL: https://github.com/apache/spark/pull/44872#discussion_r1467408202
##########
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/csv/CSVPartitionReaderFactory.scala:
##########
@@ -58,7 +58,7 @@ case class CSVPartitionReaderFactory(
actualReadDataSchema,
options,
filters)
- val schema = if (options.columnPruning) actualReadDataSchema else
actualDataSchema
+ val schema = if (options.isColumnPruningEnabled) actualReadDataSchema else
actualDataSchema
Review Comment:
The `schema` is used only in `CSVHeaderChecker` which is supposed to check
column names in CSV and provided schema fields. It shouldn't depend on the
column pruning feature at all, from my point of view.
```scala
private def checkHeaderColumnNames(columnNames: Array[String]): Unit = {
...
if (headerLen == schemaSize) {
...
} else {
errorMessage = Some(
s"""|Number of column in CSV header is not equal to number of
fields in the schema:
| Header length: $headerLen, schema size: $schemaSize
|$source""".stripMargin)
}
```
`schemaSize` must be **full data schema** of CSV filed, but not the required
schema.
Let me re-think it, and avoid the dependency from the column pruning in
`CSVHeaderChecker`.
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