[SPARK-48241][SQL][3.5] CSV parsing failure with char/varchar type columns

### What changes were proposed in this pull request?
CSV table containing char and varchar columns will result in the following error when selecting from the CSV table:
```
spark-sql (default)> show create table test_csv;
CREATE TABLE default.test_csv (
  id INT,
  name CHAR(10))
USING csv
```
```
java.lang.IllegalArgumentException: requirement failed: requiredSchema (struct<id:int,name:string>) should be the subset of dataSchema (struct<id:int,name:string>).
    at scala.Predef$.require(Predef.scala:281)
    at org.apache.spark.sql.catalyst.csv.UnivocityParser.<init>(UnivocityParser.scala:56)
    at org.apache.spark.sql.execution.datasources.csv.CSVFileFormat.$anonfun$buildReader$2(CSVFileFormat.scala:127)
    at org.apache.spark.sql.execution.datasources.FileFormat$$anon$1.apply(FileFormat.scala:155)
    at org.apache.spark.sql.execution.datasources.FileFormat$$anon$1.apply(FileFormat.scala:140)
    at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.org$apache$spark$sql$execution$datasources$FileScanRDD$$anon$$readCurrentFile(FileScanRDD.scala:231)
    at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:293)
    at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:125)
```

### Why are the changes needed?
For char and varchar types, Spark will convert them to `StringType` in `CharVarcharUtils.replaceCharVarcharWithStringInSchema` and record `__CHAR_VARCHAR_TYPE_STRING` in the metadata.

The reason for the above error is that the `StringType` columns in the `dataSchema` and `requiredSchema` of `UnivocityParser` are not consistent. The `StringType` in the `dataSchema` has metadata, while the metadata in the `requiredSchema` is empty. We need to retain the metadata when resolving schema.

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

### How was this patch tested?
Add a new test case in `CSVSuite`.

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

Closes #46565 from liujiayi771/branch-3.5-SPARK-48241.

Authored-by: joey.ljy <[email protected]>
Signed-off-by: Wenchen Fan <[email protected]>

Author: liujiayi771

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/LogicalPlan.scala

@@ -116,7 +116,9 @@ abstract class LogicalPlan
   def resolve(schema: StructType, resolver: Resolver): Seq[Attribute] = {
     schema.map { field =>
       resolve(field.name :: Nil, resolver).map {
-        case a: AttributeReference => a
+        case a: AttributeReference =>
+          // Keep the metadata in given schema.
+          a.withMetadata(field.metadata)
         case _ => throw QueryExecutionErrors.resolveCannotHandleNestedSchema(this)
       }.getOrElse {
         throw QueryCompilationErrors.cannotResolveAttributeError(

sql/core/src/test/resources/test-data/char.csv

@@ -0,0 +1,4 @@
+color,name
+pink,Bob
+blue,Mike
+grey,Tom

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

@@ -80,6 +80,7 @@ abstract class CSVSuite
   private val valueMalformedFile = "test-data/value-malformed.csv"
   private val badAfterGoodFile = "test-data/bad_after_good.csv"
   private val malformedRowFile = "test-data/malformedRow.csv"
+  private val charFile = "test-data/char.csv"
 
   /** Verifies data and schema. */
   private def verifyCars(
@@ -3226,6 +3227,29 @@ abstract class CSVSuite
       }
     }
   }
+
+  test("SPARK-48241: CSV parsing failure with char/varchar type columns") {
+    withTable("charVarcharTable") {
+      spark.sql(
+        s"""
+           |CREATE TABLE charVarcharTable(
+           |  color char(4),
+           |  name varchar(10))
+           |USING csv
+           |OPTIONS (
+           |  header "true",
+           |  path "${testFile(charFile)}"
+           |)
+       """.stripMargin)
+      val expected = Seq(
+        Row("pink", "Bob"),
+        Row("blue", "Mike"),
+        Row("grey", "Tom"))
+      checkAnswer(
+        sql("SELECT * FROM charVarcharTable"),
+        expected)
+    }
+  }
 }
 
 class CSVv1Suite extends CSVSuite {