public static SparkRDDAggregator buildAggregator()

in spark-load/spark-load-dpp/src/main/java/org/apache/doris/load/loadv2/dpp/SparkRDDAggregator.java [61:153]
93 lines of code
53 McCabe index (conditional complexity)

    public static SparkRDDAggregator buildAggregator(EtlJobConfig.EtlColumn column) throws SparkDppException {
        String aggType = StringUtils.lowerCase(column.aggregationType);
        String columnType = StringUtils.lowerCase(column.columnType);
        switch (aggType) {
            case "bitmap_union":
                return new BitmapUnionAggregator();
            case "hll_union":
                return new HllUnionAggregator();
            case "max":
                switch (columnType) {
                    case "tinyint":
                    case "smallint":
                    case "int":
                    case "bigint":
                    case "float":
                    case "double":
                    case "decimalv2":
                    case "decimal32":
                    case "decimal64":
                    case "decimal128":
                    case "date":
                    case "datetime":
                    case "datev2":
                    case "datetimev2":
                        return new NumberMaxAggregator();
                    case "char":
                    case "varchar":
                        return new StringMaxAggregator();
                    case "largeint":
                        return new LargeIntMaxAggregator();
                    default:
                        throw new SparkDppException(
                                String.format("unsupported max aggregator for column type:%s", columnType));
                }
            case "min":
                switch (columnType) {
                    case "tinyint":
                    case "smallint":
                    case "int":
                    case "bigint":
                    case "float":
                    case "double":
                    case "decimalv2":
                    case "decimal32":
                    case "decimal64":
                    case "decimal128":
                    case "date":
                    case "datetime":
                    case "datev2":
                    case "datetimev2":
                        return new NumberMinAggregator();
                    case "char":
                    case "varchar":
                        return new StringMinAggregator();
                    case "largeint":
                        return new LargeIntMinAggregator();
                    default:
                        throw new SparkDppException(
                                String.format("unsupported min aggregator for column type:%s", columnType));
                }
            case "sum":
                switch (columnType) {
                    case "tinyint":
                        return new ByteSumAggregator();
                    case "smallint":
                        return new ShortSumAggregator();
                    case "int":
                        return new IntSumAggregator();
                    case "bigint":
                        return new LongSumAggregator();
                    case "float":
                        return new FloatSumAggregator();
                    case "double":
                        return new DoubleSumAggregator();
                    case "largeint":
                        return new LargeIntSumAggregator();
                    case "decimalv2":
                    case "decimal32":
                    case "decimal64":
                    case "decimal128":
                        return new BigDecimalSumAggregator();
                    default:
                        throw new SparkDppException(
                                String.format("unsupported sum aggregator for column type:%s", columnType));
                }
            case "replace_if_not_null":
                return new ReplaceIfNotNullAggregator();
            case "replace":
                return new ReplaceAggregator();
            default:
                throw new SparkDppException(String.format("unsupported aggregate type %s", aggType));
        }
    }