@Test
  public void testAddColumnToIcebergTable() throws IOException {
    // Create an Iceberg table with the columns customer_id, first_name and last_name with some initial data.
    Table icebergTable = testTables.createTable(shell, "customers", HiveIcebergStorageHandlerTestUtils.CUSTOMER_SCHEMA,
        fileFormat, HiveIcebergStorageHandlerTestUtils.CUSTOMER_RECORDS);

    // Add a new column (age long) to the Iceberg table.
    icebergTable.updateSchema().addColumn("age", Types.LongType.get()).commit();
    if (testTableType != TestTables.TestTableType.HIVE_CATALOG) {
      // We need to update columns for non-Hive catalogs
      shell.executeStatement("ALTER TABLE customers UPDATE COLUMNS");
    }

    Schema customerSchemaWithAge = new Schema(optional(1, "customer_id", Types.LongType.get()),
        optional(2, "first_name", Types.StringType.get(), "This is first name"),
        optional(3, "last_name", Types.StringType.get(), "This is last name"),
        optional(4, "age", Types.LongType.get()));

    // Also add a new entry to the table where the age column is set.
    icebergTable = testTables.loadTable(TableIdentifier.of("default", "customers"));
    List<Record> newCustomerWithAge = TestHelper.RecordsBuilder.newInstance(customerSchemaWithAge)
        .add(3L, "James", "Red", 34L).add(4L, "Lily", "Blue", null).build();
    testTables.appendIcebergTable(shell.getHiveConf(), icebergTable, fileFormat, null, newCustomerWithAge);

    // Do a 'select *' from Hive and check if the age column appears in the result.
    // It should be null for the old data and should be filled for the data added after the column addition.
    TestHelper.RecordsBuilder customersWithAgeBuilder = TestHelper.RecordsBuilder.newInstance(customerSchemaWithAge)
        .add(0L, "Alice", "Brown", null).add(1L, "Bob", "Green", null).add(2L, "Trudy", "Pink", null)
        .add(3L, "James", "Red", 34L).add(4L, "Lily", "Blue", null);
    List<Record> customersWithAge = customersWithAgeBuilder.build();

    List<Object[]> rows = shell.executeStatement("SELECT * FROM default.customers");
    HiveIcebergTestUtils.validateData(customersWithAge, HiveIcebergTestUtils.valueForRow(customerSchemaWithAge, rows),
        0);

    // Do a 'select customer_id, age' from Hive to check if the new column can be queried from Hive.
    // The customer_id is needed because of the result sorting.
    Schema customerSchemaWithAgeOnly =
        new Schema(optional(1, "customer_id", Types.LongType.get()), optional(4, "age", Types.LongType.get()));
    TestHelper.RecordsBuilder customerWithAgeOnlyBuilder = TestHelper.RecordsBuilder
        .newInstance(customerSchemaWithAgeOnly).add(0L, null).add(1L, null).add(2L, null).add(3L, 34L).add(4L, null);
    List<Record> customersWithAgeOnly = customerWithAgeOnlyBuilder.build();

    rows = shell.executeStatement("SELECT customer_id, age FROM default.customers");
    HiveIcebergTestUtils.validateData(customersWithAgeOnly,
        HiveIcebergTestUtils.valueForRow(customerSchemaWithAgeOnly, rows), 0);

    // Insert some data with age column from Hive. Insert an entry with null age and an entry with filled age.
    shell.executeStatement(
        "INSERT INTO default.customers values (5L, 'Lily', 'Magenta', NULL), (6L, 'Roni', 'Purple', 23L)");

    customersWithAgeBuilder.add(5L, "Lily", "Magenta", null).add(6L, "Roni", "Purple", 23L);
    customersWithAge = customersWithAgeBuilder.build();
    rows = shell.executeStatement("SELECT * FROM default.customers");
    HiveIcebergTestUtils.validateData(customersWithAge, HiveIcebergTestUtils.valueForRow(customerSchemaWithAge, rows),
        0);

    customerWithAgeOnlyBuilder.add(5L, null).add(6L, 23L);
    customersWithAgeOnly = customerWithAgeOnlyBuilder.build();
    rows = shell.executeStatement("SELECT customer_id, age FROM default.customers");
    HiveIcebergTestUtils.validateData(customersWithAgeOnly,
        HiveIcebergTestUtils.valueForRow(customerSchemaWithAgeOnly, rows), 0);
  }
Tests that schema changes of Iceberg backed Hive tables are correctly reflected in subsequent select statements.
Verification is done from both ends:
 - when ALTER TABLE statements were initiated from Hive
 - when schema changes were originally done on the Iceberg table
iceberg/iceberg-handler/src/test/java/org/apache/iceberg/mr/hive/TestHiveIcebergSchemaEvolution.java