[SPARK-46862][SQL][FOLLOWUP] Fix column pruning without schema enforc…

…ing in V1 CSV datasource

### What changes were proposed in this pull request?
In the PR, I propose to invoke `CSVOptons.isColumnPruningEnabled` introduced by #44872 while matching of CSV header to a schema in the V1 CSV datasource.

### Why are the changes needed?
To fix the failure when column pruning happens and a schema is not enforced:
```scala
scala> spark.read.
     | option("multiLine", true).
     | option("header", true).
     | option("escape", "\"").
     | option("enforceSchema", false).
     | csv("/Users/maximgekk/tmp/es-939111-data.csv").
     | count()
24/01/27 12:43:14 ERROR Executor: Exception in task 0.0 in stage 3.0 (TID 3)
java.lang.IllegalArgumentException: Number of column in CSV header is not equal to number of fields in the schema:
 Header length: 4, schema size: 0
CSV file: file:///Users/maximgekk/tmp/es-939111-data.csv
```

### Does this PR introduce _any_ user-facing change?
No.

### How was this patch tested?
By running the affected test suites:
```
$ build/sbt "test:testOnly *CSVv1Suite"
$ build/sbt "test:testOnly *CSVv2Suite"
$ build/sbt "test:testOnly *CSVLegacyTimeParserSuite"
$ build/sbt "testOnly *.CsvFunctionsSuite"
```

### Was this patch authored or co-authored using generative AI tooling?
No.

Closes #44910 from MaxGekk/check-header-column-pruning.

Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Max Gekk <max.gekk@gmail.com>
(cherry picked from commit bc51c9f)
Signed-off-by: Max Gekk <max.gekk@gmail.com>

sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVFileFormat.scala

@@ -100,12 +100,12 @@ class CSVFileFormat extends TextBasedFileFormat with DataSourceRegister {
       hadoopConf: Configuration): (PartitionedFile) => Iterator[InternalRow] = {
     val broadcastedHadoopConf =
       sparkSession.sparkContext.broadcast(new SerializableConfiguration(hadoopConf))
-    val columnPruning = sparkSession.sessionState.conf.csvColumnPruning
     val parsedOptions = new CSVOptions(
       options,
-      columnPruning,
+      sparkSession.sessionState.conf.csvColumnPruning,
       sparkSession.sessionState.conf.sessionLocalTimeZone,
       sparkSession.sessionState.conf.columnNameOfCorruptRecord)
+    val isColumnPruningEnabled = parsedOptions.isColumnPruningEnabled
 
     // Check a field requirement for corrupt records here to throw an exception in a driver side
     ExprUtils.verifyColumnNameOfCorruptRecord(dataSchema, parsedOptions.columnNameOfCorruptRecord)
@@ -125,7 +125,7 @@ class CSVFileFormat extends TextBasedFileFormat with DataSourceRegister {
         actualRequiredSchema,
         parsedOptions,
         actualFilters)
-      val schema = if (columnPruning) actualRequiredSchema else actualDataSchema
+      val schema = if (isColumnPruningEnabled) actualRequiredSchema else actualDataSchema
       val isStartOfFile = file.start == 0
       val headerChecker = new CSVHeaderChecker(
         schema, parsedOptions, source = s"CSV file: ${file.urlEncodedPath}", isStartOfFile)

sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/csv/CSVSuite.scala

@@ -3215,12 +3215,15 @@ abstract class CSVSuite
 
     withTempPath { path =>
       Files.write(path.toPath, data.getBytes(StandardCharsets.UTF_8))
-      val df = spark.read
-        .option("multiline", "true")
-        .option("header", "true")
-        .option("escape", "\"")
-        .csv(path.getCanonicalPath)
-      assert(df.count() === 5)
+      Seq(true, false).foreach { enforceSchema =>
+        val df = spark.read
+          .option("multiLine", true)
+          .option("header", true)
+          .option("escape", "\"")
+          .option("enforceSchema", enforceSchema)
+          .csv(path.getCanonicalPath)
+        assert(df.count() === 5)
+      }
     }
   }
 }