[SPARK-32025][SQL] Csv schema inference problems with different types in the same column

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala

@@ -82,7 +82,8 @@ class CSVInferSchema(val options: CSVOptions) extends Serializable {
   def inferRowType(rowSoFar: Array[DataType], next: Array[String]): Array[DataType] = {
     var i = 0
     while (i < math.min(rowSoFar.length, next.length)) {  // May have columns on right missing.
-      rowSoFar(i) = inferField(rowSoFar(i), next(i))
+      val typeElemInfer = inferField(rowSoFar(i), next(i))
+      rowSoFar(i) = compatibleType(rowSoFar(i), typeElemInfer).getOrElse(StringType)
       i+=1
     }
     rowSoFar

sql/core/src/test/resources/test-data/mixed-types1.csv

@@ -0,0 +1,4 @@
+col_mixed_types
+2012
+1997
+True

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

@@ -67,6 +67,7 @@ abstract class CSVSuite extends QueryTest with SharedSparkSession with TestCsvDa
   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 mixedTypes = "test-data/mixed-types1.csv"
 
   /** Verifies data and schema. */
   private def verifyCars(
@@ -2341,6 +2342,17 @@ abstract class CSVSuite extends QueryTest with SharedSparkSession with TestCsvDa
       checkAnswer(csv, Row(null))
     }
   }
+
+  test("Test mixed types") {
+    val data = spark
+      .read
+      .format("csv")
+      .option("header", "true")
+      .option("inferSchema", "true")
+      .load(testFile(mixedTypes))
+
+    assert(data.schema.fields.last == StructField("col_mixed_types", StringType, true))
+  }
 }
 
 class CSVv1Suite extends CSVSuite {