[SPARK-32492][SQL][FOLLOWUP][TEST-MAVEN] Fix jenkins maven jobs

### What changes were proposed in this pull request?

The newly added test fails Jenkins maven jobs, see #29303 (comment)

We move the test from `ThriftServerWithSparkContextSuite` to `SparkMetadataOperationSuite`, the former uses an embedded thrift server where the server and the client are in the same JVM process and the latter forks a new process to start the server where the server and client are isolated.
The sbt runner seems to be fine with the test in the `ThriftServerWithSparkContextSuite`, but the maven runner with `scalates`t plugin will face the classloader issue as we will switch classloader to the one in the `sharedState` which is not the one that hive uses to load some classes. This is more like an issue that belongs to the maven runner or the `scalatest`.
So in this PR, we simply move it to bypass the issue.

BTW, we should test against the way of using embedded thrift server to verify whether it is just a maven issue or not, there could be some use cases with this API.

### Why are the changes needed?

Jenkins recovery

### Does this PR introduce _any_ user-facing change?

no

### How was this patch tested?

modified uts

Closes #29347 from yaooqinn/SPARK-32492-F.

Authored-by: Kent Yao <yaooqinn@hotmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>

Author: yaooqinn

sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/SparkMetadataOperationSuite.scala

@@ -19,6 +19,8 @@ package org.apache.spark.sql.hive.thriftserver
 
 import java.sql.{DatabaseMetaData, ResultSet}
 
+import org.apache.spark.sql.types.{ArrayType, BinaryType, BooleanType, DecimalType, DoubleType, FloatType, IntegerType, MapType, NumericType, StringType, StructType, TimestampType}
+
 class SparkMetadataOperationSuite extends HiveThriftJdbcTest {
 
   override def mode: ServerMode.Value = ServerMode.binary
@@ -247,4 +249,88 @@ class SparkMetadataOperationSuite extends HiveThriftJdbcTest {
       checkResult(metaData.getTypeInfo, ThriftserverShimUtils.supportedType().map(_.getName))
     }
   }
+
+  test("check results from get columns operation from thrift server") {
+    val schemaName = "default"
+    val tableName = "spark_get_col_operation"
+    val schema = new StructType()
+      .add("c0", "boolean", nullable = false, "0")
+      .add("c1", "tinyint", nullable = true, "1")
+      .add("c2", "smallint", nullable = false, "2")
+      .add("c3", "int", nullable = true, "3")
+      .add("c4", "long", nullable = false, "4")
+      .add("c5", "float", nullable = true, "5")
+      .add("c6", "double", nullable = false, "6")
+      .add("c7", "decimal(38, 20)", nullable = true, "7")
+      .add("c8", "decimal(10, 2)", nullable = false, "8")
+      .add("c9", "string", nullable = true, "9")
+      .add("c10", "array<long>", nullable = false, "10")
+      .add("c11", "array<string>", nullable = true, "11")
+      .add("c12", "map<smallint, tinyint>", nullable = false, "12")
+      .add("c13", "date", nullable = true, "13")
+      .add("c14", "timestamp", nullable = false, "14")
+      .add("c15", "struct<X: bigint,Y: double>", nullable = true, "15")
+      .add("c16", "binary", nullable = false, "16")
+
+    val ddl =
+      s"""
+         |CREATE TABLE $schemaName.$tableName (
+         |  ${schema.toDDL}
+         |)
+         |using parquet""".stripMargin
+
+    withJdbcStatement(tableName) { statement =>
+      statement.execute(ddl)
+
+      val databaseMetaData = statement.getConnection.getMetaData
+      val rowSet = databaseMetaData.getColumns("", schemaName, tableName, null)
+
+      import java.sql.Types._
+      val expectedJavaTypes = Seq(BOOLEAN, TINYINT, SMALLINT, INTEGER, BIGINT, FLOAT, DOUBLE,
+        DECIMAL, DECIMAL, VARCHAR, ARRAY, ARRAY, JAVA_OBJECT, DATE, TIMESTAMP, STRUCT, BINARY)
+
+      var pos = 0
+
+      while (rowSet.next()) {
+        assert(rowSet.getString("TABLE_CAT") === null)
+        assert(rowSet.getString("TABLE_SCHEM") === schemaName)
+        assert(rowSet.getString("TABLE_NAME") === tableName)
+        assert(rowSet.getString("COLUMN_NAME") === schema(pos).name)
+        assert(rowSet.getInt("DATA_TYPE") === expectedJavaTypes(pos))
+        assert(rowSet.getString("TYPE_NAME") === schema(pos).dataType.sql)
+
+        val colSize = rowSet.getInt("COLUMN_SIZE")
+        schema(pos).dataType match {
+          case StringType | BinaryType | _: ArrayType | _: MapType => assert(colSize === 0)
+          case o => assert(colSize === o.defaultSize)
+        }
+
+        assert(rowSet.getInt("BUFFER_LENGTH") === 0) // not used
+        val decimalDigits = rowSet.getInt("DECIMAL_DIGITS")
+        schema(pos).dataType match {
+          case BooleanType | _: IntegerType => assert(decimalDigits === 0)
+          case d: DecimalType => assert(decimalDigits === d.scale)
+          case FloatType => assert(decimalDigits === 7)
+          case DoubleType => assert(decimalDigits === 15)
+          case TimestampType => assert(decimalDigits === 6)
+          case _ => assert(decimalDigits === 0) // nulls
+        }
+
+        val radix = rowSet.getInt("NUM_PREC_RADIX")
+        schema(pos).dataType match {
+          case _: NumericType => assert(radix === 10)
+          case _ => assert(radix === 0) // nulls
+        }
+
+        assert(rowSet.getInt("NULLABLE") === 1)
+        assert(rowSet.getString("REMARKS") === pos.toString)
+        assert(rowSet.getInt("ORDINAL_POSITION") === pos)
+        assert(rowSet.getString("IS_NULLABLE") === "YES")
+        assert(rowSet.getString("IS_AUTO_INCREMENT") === "NO")
+        pos += 1
+      }
+
+      assert(pos === 17, "all columns should have been verified")
+    }
+  }
 }

sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/ThriftServerWithSparkContextSuite.scala

@@ -19,8 +19,6 @@ package org.apache.spark.sql.hive.thriftserver
 
 import java.sql.SQLException
 
-import scala.collection.JavaConverters._
-
 import org.apache.hive.service.cli.HiveSQLException
 
 import org.apache.spark.sql.hive.HiveUtils
@@ -104,135 +102,6 @@ trait ThriftServerWithSparkContextSuite extends SharedThriftServer {
       }
     }
   }
-
-  test("check results from get columns operation from thrift server") {
-    val schemaName = "default"
-    val tableName = "spark_get_col_operation"
-    val schema = new StructType()
-      .add("c0", "boolean", nullable = false, "0")
-      .add("c1", "tinyint", nullable = true, "1")
-      .add("c2", "smallint", nullable = false, "2")
-      .add("c3", "int", nullable = true, "3")
-      .add("c4", "long", nullable = false, "4")
-      .add("c5", "float", nullable = true, "5")
-      .add("c6", "double", nullable = false, "6")
-      .add("c7", "decimal(38, 20)", nullable = true, "7")
-      .add("c8", "decimal(10, 2)", nullable = false, "8")
-      .add("c9", "string", nullable = true, "9")
-      .add("c10", "array<long>", nullable = false, "10")
-      .add("c11", "array<string>", nullable = true, "11")
-      .add("c12", "map<smallint, tinyint>", nullable = false, "12")
-      .add("c13", "date", nullable = true, "13")
-      .add("c14", "timestamp", nullable = false, "14")
-      .add("c15", "struct<X: bigint,Y: double>", nullable = true, "15")
-      .add("c16", "binary", nullable = false, "16")
-
-    val ddl =
-      s"""
-         |CREATE TABLE $schemaName.$tableName (
-         |  ${schema.toDDL}
-         |)
-         |using parquet""".stripMargin
-
-    withCLIServiceClient { client =>
-      val sessionHandle = client.openSession(user, "")
-      val confOverlay = new java.util.HashMap[java.lang.String, java.lang.String]
-      val opHandle = client.executeStatement(sessionHandle, ddl, confOverlay)
-      var status = client.getOperationStatus(opHandle)
-      while (!status.getState.isTerminal) {
-        Thread.sleep(10)
-        status = client.getOperationStatus(opHandle)
-      }
-      val getCol = client.getColumns(sessionHandle, "", schemaName, tableName, null)
-      val rowSet = client.fetchResults(getCol)
-      val columns = rowSet.toTRowSet.getColumns
-
-      val catalogs = columns.get(0).getStringVal.getValues.asScala
-      assert(catalogs.forall(_.isEmpty), "catalog name mismatches")
-
-      val schemas = columns.get(1).getStringVal.getValues.asScala
-      assert(schemas.forall(_ == schemaName), "schema name mismatches")
-
-      val tableNames = columns.get(2).getStringVal.getValues.asScala
-      assert(tableNames.forall(_ == tableName), "table name mismatches")
-
-      val columnNames = columns.get(3).getStringVal.getValues.asScala
-      columnNames.zipWithIndex.foreach {
-        case (v, i) => assert(v === "c" + i, "column name mismatches")
-      }
-
-      val javaTypes = columns.get(4).getI32Val.getValues
-      import java.sql.Types._
-      assert(javaTypes.get(0).intValue() === BOOLEAN)
-      assert(javaTypes.get(1).intValue() === TINYINT)
-      assert(javaTypes.get(2).intValue() === SMALLINT)
-      assert(javaTypes.get(3).intValue() === INTEGER)
-      assert(javaTypes.get(4).intValue() === BIGINT)
-      assert(javaTypes.get(5).intValue() === FLOAT)
-      assert(javaTypes.get(6).intValue() === DOUBLE)
-      assert(javaTypes.get(7).intValue() === DECIMAL)
-      assert(javaTypes.get(8).intValue() === DECIMAL)
-      assert(javaTypes.get(9).intValue() === VARCHAR)
-      assert(javaTypes.get(10).intValue() === ARRAY)
-      assert(javaTypes.get(11).intValue() === ARRAY)
-      assert(javaTypes.get(12).intValue() === JAVA_OBJECT)
-      assert(javaTypes.get(13).intValue() === DATE)
-      assert(javaTypes.get(14).intValue() === TIMESTAMP)
-      assert(javaTypes.get(15).intValue() === STRUCT)
-      assert(javaTypes.get(16).intValue() === BINARY)
-
-      val typeNames = columns.get(5).getStringVal.getValues.asScala
-      typeNames.zip(schema).foreach { case (tName, f) =>
-        assert(tName === f.dataType.sql)
-      }
-
-      val colSize = columns.get(6).getI32Val.getValues.asScala
-
-      colSize.zip(schema).foreach { case (size, f) =>
-        f.dataType match {
-          case StringType | BinaryType | _: ArrayType | _: MapType => assert(size === 0)
-          case o => assert(size === o.defaultSize)
-        }
-      }
-
-      val decimalDigits = columns.get(8).getI32Val.getValues.asScala
-      decimalDigits.zip(schema).foreach { case (dd, f) =>
-        f.dataType match {
-          case BooleanType | _: IntegerType => assert(dd === 0)
-          case d: DecimalType => assert(dd === d.scale)
-          case FloatType => assert(dd === 7)
-          case DoubleType => assert(dd === 15)
-          case TimestampType => assert(dd === 6)
-          case _ => assert(dd === 0) // nulls
-        }
-      }
-
-      val radixes = columns.get(9).getI32Val.getValues.asScala
-      radixes.zip(schema).foreach { case (radix, f) =>
-        f.dataType match {
-          case _: NumericType => assert(radix === 10)
-          case _ => assert(radix === 0) // nulls
-        }
-      }
-
-      val nullables = columns.get(10).getI32Val.getValues.asScala
-      assert(nullables.forall(_ === 1))
-
-      val comments = columns.get(11).getStringVal.getValues.asScala
-      comments.zip(schema).foreach { case (c, f) => assert(c === f.getComment().get) }
-
-      val positions = columns.get(16).getI32Val.getValues.asScala
-      positions.zipWithIndex.foreach { case (pos, idx) =>
-        assert(pos === idx, "the client columns disorder")
-      }
-
-      val isNullables = columns.get(17).getStringVal.getValues.asScala
-      assert(isNullables.forall(_ === "YES"))
-
-      val autoIncs = columns.get(22).getStringVal.getValues.asScala
-      assert(autoIncs.forall(_ === "NO"))
-    }
-  }
 }