apache/iceberg · error · UnsupportedOperationException

Unsupported to derive Schema for type: <logicalType>

Error message

Unsupported to derive Schema for type: <logicalType>

What it means

convertToSchema only implements Avro schema derivation for a known set of Flink logical types. RAW (and any unmatched type) has no Avro representation rule, so the converter throws UnsupportedOperationException instead of guessing a schema.

Source

Thrown at flink/v1.20/flink/src/main/java/org/apache/iceberg/flink/formats/avro/typeutils/AvroSchemaConverter.java:593

        Schema record = builder.endRecord();
        return nullable ? nullableSchema(record) : record;
      case MULTISET:
      case MAP:
        Schema map =
            SchemaBuilder.builder()
                .map()
                .values(convertToSchema(extractValueTypeToAvroMap(logicalType), rowName));
        return nullable ? nullableSchema(map) : map;
      case ARRAY:
        ArrayType arrayType = (ArrayType) logicalType;
        Schema array =
            SchemaBuilder.builder()
                .array()
                .items(convertToSchema(arrayType.getElementType(), rowName));
        return nullable ? nullableSchema(array) : array;
      case RAW:
      default:
        throw new UnsupportedOperationException(
            "Unsupported to derive Schema for type: " + logicalType);
    }
  }

  public static LogicalType extractValueTypeToAvroMap(LogicalType type) {
    LogicalType keyType;
    LogicalType valueType;
    if (type instanceof MapType) {
      MapType mapType = (MapType) type;
      keyType = mapType.getKeyType();
      valueType = mapType.getValueType();
    } else {
      MultisetType multisetType = (MultisetType) type;
      keyType = multisetType.getElementType();
      valueType = new IntType();
    }
    if (!keyType.is(LogicalTypeFamily.CHARACTER_STRING)) {
      throw new UnsupportedOperationException(

View on GitHub (pinned to 86d9c8fc54)

Solutions

1. Remove or replace RAW-typed columns before conversion (e.g. deserialize to a supported type with a Map/projection).
2. If the RAW payload is actually a known structure, declare the field with its concrete LogicalType instead of RAW.
3. Check that you are using a Flink/Iceberg version combination where the converter supports your type; upgrade iceberg-flink-runtime if a newer release added support.

Example fix

// before
Schema s = AvroSchemaConverter.convertToSchema(new RawType<>(MyPojo.class));

// after: use a concrete supported type
Schema s = AvroSchemaConverter.convertToSchema(new RowType(...));

// reject unsupported types up-front
Set<LogicalTypeRoot> supported = Set.of(ROW, ARRAY, MAP, MULTISET, CHAR, VARCHAR, BOOLEAN, INTEGER, BIGINT, DECIMAL, FLOAT, DOUBLE, DATE, TIME_WITHOUT_TIME_ZONE, TIMESTAMP_WITHOUT_TIME_ZONE, TIMESTAMP_WITH_LOCAL_TIME_ZONE, BINARY, VARBINARY);
if (!supported.contains(type.getTypeRoot())) {
    throw new IllegalArgumentException("Type not Avro-convertible: " + type.asSummaryString());
}

boolean isAvroConvertible(LogicalType t) {
    return t.getTypeRoot() != LogicalTypeRoot.RAW;
}

try {
    schema = AvroSchemaConverter.convertToSchema(logicalType);
} catch (UnsupportedOperationException e) {
    // fall back to a generic/bytes schema or drop the field
    schema = fallbackSchema(logicalType);
}

When it happens

Trigger: Calling convertToSchema on a LogicalType whose case is RAW or any type not handled by the switch (e.g. a RawType from a custom serializer, or newly added Flink types this converter does not know).

Common situations: DataStreams containing RAW-typed columns (e.g. from DataStream API with custom TypeInformations), or Flink version upgrades introducing new logical types while using an older Iceberg AvroSchemaConverter.

Understand the failure class

Background: UnsupportedOperationException and "is not supported" errors: when a library deliberately refuses a call — this error's family across 30 libraries.

Related errors

• Unsupported type ID:
• Unsupported type: ${primitive}
• Unsupported Avro type '${schema.getType()}'.
• Avro does not support TIME type with precision: <precision>,
• Avro format doesn't support non-string as key type of map. T

AI-assisted analysis of apache/iceberg@86d9c8fc54 (2026-09-12). Data as JSON: /api/errors/f2a196dffb35d542. Report an issue: GitHub.