apache/iceberg · error · UnsupportedOperationException

Unsupported to derive Schema for type:

Error message

Unsupported to derive Schema for type: 

What it means

Thrown when converting a Flink TIMESTAMP_WITH_LOCAL_TIME_ZONE logical type to an Avro schema while legacyTimestampMapping=true. Legacy mapping has no Avro logical type for zoned timestamps, so this case is explicitly rejected with UnsupportedOperationException. Using the non-legacy mapping (timestampMillis/timestampMicros) resolves it.

Source

Thrown at flink/v2.3/flink/src/main/java/org/apache/iceberg/flink/formats/avro/typeutils/AvroSchemaConverter.java:511

          }
        } else {
          if (precision <= 3) {
            avroLogicalType = LogicalTypes.localTimestampMillis();
          } else if (precision <= 6) {
            avroLogicalType = LogicalTypes.localTimestampMicros();
          } else {
            throw new IllegalArgumentException(
                "Avro does not support LOCAL TIMESTAMP type "
                    + "with precision: "
                    + precision
                    + ", it only supports precision less than 6.");
          }
        }
        Schema timestamp = avroLogicalType.addToSchema(SchemaBuilder.builder().longType());
        return nullable ? nullableSchema(timestamp) : timestamp;
      case TIMESTAMP_WITH_LOCAL_TIME_ZONE:
        if (legacyTimestampMapping) {
          throw new UnsupportedOperationException(
              "Unsupported to derive Schema for type: " + logicalType);
        } else {
          final LocalZonedTimestampType localZonedTimestampType =
              (LocalZonedTimestampType) logicalType;
          precision = localZonedTimestampType.getPrecision();
          if (precision <= 3) {
            avroLogicalType = LogicalTypes.timestampMillis();
          } else if (precision <= 6) {
            avroLogicalType = LogicalTypes.timestampMicros();
          } else {
            throw new IllegalArgumentException(
                "Avro does not support TIMESTAMP type "
                    + "with precision: "
                    + precision
                    + ", it only supports precision less than 6.");
          }
          timestamp = avroLogicalType.addToSchema(SchemaBuilder.builder().longType());
          return nullable ? nullableSchema(timestamp) : timestamp;

View on GitHub (pinned to 86d9c8fc54)

Solutions

1. Set legacyTimestampMapping=false when calling convertToSchema.
2. Remove the legacy timestamp mapping option from the connector/format config.
3. If legacy mode cannot be disabled, cast the column to TIMESTAMP (without time zone).
4. Upgrade Flink/Iceberg if legacy mapping is forced by an old version's defaults.

Example fix

// before
AvroSchemaConverter.convertToSchema(localZonedTimestampType, true); // throws
// after
AvroSchemaConverter.convertToSchema(localZonedTimestampType, false); // timestampMillis/Micros

if (logicalType instanceof LocalZonedTimestampType && legacyTimestampMapping) { /* disable legacy mapping or cast to TIMESTAMP without time zone */ }

When it happens

Trigger: Calling AvroSchemaConverter.convertToSchema(LogicalType, boolean) with a LocalZonedTimestampType while legacyTimestampMapping is true.

Common situations: Tables containing TIMESTAMPTZ / TIMESTAMP WITH LOCAL TIME ZONE columns written to Avro with legacy mapping enabled from an older Flink/Iceberg configuration.

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: ${type}
• Unsupported type: ${type}
• Unsupported to derive Schema for type: ${logicalType}
• Unsupported type: " + type
• Unsupported type: " + type

AI-assisted analysis of apache/iceberg@86d9c8fc54 (2026-09-12). Data as JSON: /api/errors/0c7c1d1595a47839. Report an issue: GitHub.