apache/beam · error · IllegalArgumentException

Unsupported type

Error message

Unsupported type ${fieldType}

What it means

The default branch of the TypeName switch in AvroUtils.genericFromBeamField: the Beam field's TypeName is one the Beam-to-Avro converter does not handle. Only BYTE/INT16/INT32/INT64/FLOAT/DOUBLE/BOOLEAN/STRING/DECIMAL/DATETIME/BYTES/LOGICAL_TYPE/ARRAY/ITERABLE/MAP/ROW are supported; any other Beam type reaching this converter triggers the error.

Solutions

1. Upgrade the Beam SDK so the avro extension supports the TypeName
2. Convert the unsupported field to a supported representation (e.g. STRING) before writing to Avro
3. Regenerate the Avro schema from the Beam schema via AvroUtils.toAvroSchema and confirm all field types map cleanly
4. If the type is truly unsupported, file/report upstream and restructure the schema to avoid it

Example fix

// before
row = row.withValue("payload", someUnsupportedObject);
// after
row = row.withValue("payload", someUnsupportedObject.toString()); // STRING is supported

java.util.Set<String> SUPPORTED = java.util.Set.of("BYTE","INT16","INT32","INT64","FLOAT","DOUBLE","BOOLEAN","STRING","DECIMAL","DATETIME","BYTES","LOGICAL_TYPE","ARRAY","ITERABLE","MAP","ROW");
for (Schema.Field f : beamSchema.getFields()) {
  if (!SUPPORTED.contains(f.getType().getTypeName().name()))
    throw new IllegalStateException("Unsupported Beam type for Avro: " + f.getType().getTypeName());
}

try {
  GenericRecord record = AvroUtils.toGenericRecord(row, avroSchema);
} catch (IllegalArgumentException e) {
  if (e.getMessage() != null && e.getMessage().startsWith("Unsupported type")) {
    throw new IllegalStateException("Beam schema contains a type not convertible to Avro", e);
  } else { throw e; }
}

When it happens

Trigger: Calling toGenericRecord / toAvroType with a Beam schema containing an unsupported TypeName (e.g. some specialized or newly added Beam types not yet mapped in this Avro extension).

Common situations: Using a Beam type added in a recent SDK release with an older avro extension on the classpath; exotic schema fields produced programmatically; type drift between the Beam schema used to build Rows and the converter's supported set.

Understand the failure class

Background: Type mismatch errors: IllegalArgumentException, TypeError and type guards across 150 open-source libraries — this error's family across 150 libraries.

Related errors

• Can't represent as
• FieldType and AVRO schema don't have matching nullability
• Incorrectly sized byte array.
• Converting BigQuery type '' to '' is not supported
• Unexpected Avro field schema type

AI-assisted analysis of apache/beam@12126d8942 (2026-09-13). Data as JSON: /api/errors/74bd86ad1b4396b2. Report an issue: GitHub.

Appendix: source

Thrown at sdks/java/extensions/avro/src/main/java/org/apache/beam/sdk/extensions/avro/schemas/utils/AvroUtils.java:1436

      case MAP:
        Map<Object, @Nullable Object> map = Maps.newHashMap();
        Map<Object, Object> valueMap = (Map<Object, Object>) value;
        for (Map.Entry entry : valueMap.entrySet()) {
          Utf8 key = new Utf8((String) checkNotNull(entry.getKey()));
          map.put(
              key,
              genericFromBeamField(
                  checkNotNull(fieldType.getMapValueType()),
                  typeWithNullability.type.getValueType(),
                  entry.getValue()));
        }
        return map;

      case ROW:
        return toGenericRecord((Row) value, typeWithNullability.type);

      default:
        throw new IllegalArgumentException("Unsupported type " + fieldType);
    }
  }

  private static Object convertLogicalType(
      @PolyNull Object value,
      @Nonnull org.apache.avro.Schema avroSchema,
      @Nonnull FieldType fieldType,
      @Nonnull GenericData genericData) {
    TypeWithNullability type = new TypeWithNullability(avroSchema);

    // TODO: Remove this workaround once Avro is upgraded to 1.12+ where timestamp-nanos
    if (TIMESTAMP_NANOS_LOGICAL_TYPE.equals(type.type.getProp("logicalType"))) {
      if (type.type.getType() == org.apache.avro.Schema.Type.LONG) {
        Long nanos = (Long) value;
        // Check if Beam expects Timestamp logical type
        if (fieldType.getTypeName() == TypeName.LOGICAL_TYPE
            && org.apache.beam.sdk.schemas.logicaltypes.Timestamp.IDENTIFIER.equals(
                fieldType.getLogicalType().getIdentifier())) {

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