}
			} else {
				results[col] = result
			}
		} else {
			results[column] = result
		}
	}

	// select columns
	for _, column := range stmt.Selects {
		processColumn(column, true)
	}

	// omit columns
	for _, column := range stmt.Omits {
		processColumn(column, false)
	}

	if stmt.Schema != nil {
		for _, field := range stmt.Schema.FieldsByName {

			if stmt.Schema != nil && len(values.Columns) >= 1 {
				selectColumns, restricted := stmt.SelectAndOmitColumns(true, true)

				columns := make([]string, 0, len(values.Columns)-1)
				for _, column := range values.Columns {
					if field := stmt.Schema.LookUpField(column.Name); field != nil {
						if v, ok := selectColumns[field.DBName]; (ok && v) || (!ok && !restricted) {

					}

					if len(selectExpr.Exprs) == 0 {
						selectExpr.Exprs = []clause.Expression{clause.Expr{SQL: "*", Vars: []interface{}{}}}
					}

					partitionBy := clause.CommaExpression{}
					for _, column := range refColumns {
						partitionBy.Exprs = append(partitionBy.Exprs, clause.Expr{SQL: "?", Vars: []interface{}{clause.Column{Name: column.Name}}})
					}

	} else if len(langs) != 1 {
		t.Errorf("should only find only 1 languages, but got %+v", langs)
	}

	lang3 := Language{Code: "upsert", Name: "Upsert"}
	if err := DB.Clauses(clause.OnConflict{
		Columns:   []clause.Column{{Name: "code"}},
		DoUpdates: clause.Assignments(map[string]interface{}{"name": "upsert-new"}),
	}).Create(&lang3).Error; err != nil {
		t.Fatalf("failed to upsert, got %v", err)
	}

 * Null row keys, columns keys, and values are not supported.
 *
 * <p>Lookups by row key are often faster than lookups by column key, because the data is stored in
 * a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still runs
 * quickly, since the row key is provided. However, {@code column(columnKey).size()} takes longer,
 * since an iteration across all row keys occurs.
 *

 *
 * <p>The allowed row and column keys must be supplied when the table is created. The table always
 * contains a mapping for every row key / column pair. The value corresponding to a given row and
 * column is null unless another value is provided.
 *
 * <p>The table's size is constant: the product of the number of supplied row keys and the number of

			} else if eq, ok := expr.(clause.Eq); ok {
				switch column := eq.Column.(type) {
				case string:
					assigns[column] = eq.Value
				case clause.Column:
					assigns[column.Name] = eq.Value
				}
			}
		}

		return tx.Model(dest).Updates(assigns)
	}

	return tx
}

- Parquet API supports columnar compression for  using GZIP, Snappy, LZ4. Whole object compression is not supported for Parquet objects.
- Server-side encryption - The Select API supports querying objects that are protected with server-side encryption.

					t.Fatalf("column age comment should be correct, name: %v, column: %#v", columnType.Name(),
						columnType)
				}
			case "code":
				if v, ok := columnType.Unique(); !ok || !v {
					t.Fatalf("column code unique should be correct, name: %v, column: %#v", columnType.Name(),
						columnType)
				}
				if v, ok := columnType.DefaultValue(); !ok || v != "hello" {

// UnmarshalYAML - BatchJobNotification extends unmarshal to extract line, column information
func (b *BatchJobNotification) UnmarshalYAML(val *yaml.Node) error {
	type notification BatchJobNotification
	var tmp notification
	err := val.Decode(&tmp)
	if err != nil {
		return err
	}

	*b = BatchJobNotification(tmp)
	b.line, b.col = val.Line, val.Column
	return nil
}