apache/iceberg · error · java.lang.IllegalArgumentException

Invalid iceberg type %s corresponding to Flink logical type

Error message

Invalid iceberg type %s corresponding to Flink logical type %s

What it means

FlinkOrcWriter.primitive() throws IllegalArgumentException 'Invalid iceberg type <type> corresponding to Flink logical type <type>' when an Iceberg primitive type cannot be mapped to an ORC writer for the given Flink logical type — the Iceberg type and Flink type pair is unsupported (mismatch between declared schema and Flink RowType).

Source

Thrown at flink/v2.1/flink/src/main/java/org/apache/iceberg/flink/data/FlinkOrcWriter.java:165

          }
        case TIMESTAMP_NANO:
          Types.TimestampNanoType timestampNanoType = (Types.TimestampNanoType) iPrimitive;
          if (timestampNanoType.shouldAdjustToUTC()) {
            return FlinkOrcWriters.timestampNanoTzs();
          } else {
            return FlinkOrcWriters.timestampNanos();
          }
        case STRING:
          return FlinkOrcWriters.strings();
        case UUID:
        case FIXED:
        case BINARY:
          return GenericOrcWriters.byteArrays();
        case DECIMAL:
          Types.DecimalType decimalType = (Types.DecimalType) iPrimitive;
          return FlinkOrcWriters.decimals(decimalType.precision(), decimalType.scale());
        default:
          throw new IllegalArgumentException(
              String.format(
                  "Invalid iceberg type %s corresponding to Flink logical type %s",
                  iPrimitive, flinkPrimitive));
      }
    }
  }
}

View on GitHub (pinned to 86d9c8fc54)

Solutions

Ensure the Flink RowType is built from the Iceberg schema via FlinkSchemaUtil.convert(schema).
Remove/retype columns producing unsupported pairs (check both types in the message).
Use a different write format (Parquet/Avro) if the mapping exists there.
Upgrade iceberg-flink if a newer version supports the pairing.

Example fix

// before
RowType rowType = customRowType(); // not matching table schema
// after
RowType rowType = FlinkSchemaUtil.convert(table.schema());

Defensive patterns

Strategy: validation

Validate before calling

RowType rowType = FlinkSchemaUtil.convert(table.schema()); // derive Flink type from Iceberg schema, never hand-build

Try / catch

try {
  writer.write(rowData);
} catch (IllegalArgumentException e) {
  if (e.getMessage().contains("Invalid iceberg type")) {
    LOG.error("Flink/Iceberg type pair unsupported: {}", e.getMessage());
  }
  throw e;
}

Prevention

Always derive Flink RowType via FlinkSchemaUtil.convert(schema).
Check the supported Iceberg<->Flink type mapping table before using unusual types.
Test writes on a sample table with the same schema before production.

When it happens

Trigger: Writing ORC files where a column's Iceberg primitive and Flink LogicalType don't form a supported pair (e.g. Iceberg BINARY paired with an unexpected Flink type, or a primitive combination with no branch in the switch).

Common situations: Custom FlinkRowType construction not derived from the Iceberg schema; writer framework upgrades changing type mappings; writing tables whose schema was transformed incorrectly.

Understand the failure class

Background: "is not a compatible type" / "cannot merge" errors: when a value's type doesn't match what the library requires — this error's family across 65 libraries.

Related errors

AI-assisted analysis of apache/iceberg@86d9c8fc54 (2026-09-12). Data as JSON: /api/errors/069f3f96c7c48f64. Report an issue: GitHub.