apache/iceberg · error · IllegalArgumentException

Invalid iceberg type %s corresponding to ORC type %s

Error message

Invalid iceberg type %s corresponding to ORC type %s

What it means

FlinkOrcReader's visitor throws IllegalArgumentException('Invalid iceberg type %s corresponding to ORC type %s') when an Iceberg primitive cannot be matched to the corresponding ORC primitive during value reader construction — the Iceberg type and the ORC column type are incompatible or the Iceberg type is unmapped.

Source

Thrown at flink/v2.2/flink/src/main/java/org/apache/iceberg/flink/data/FlinkOrcReader.java:132

          }
        case TIMESTAMP_NANO:
          Types.TimestampNanoType timestampNanoType = (Types.TimestampNanoType) iPrimitive;
          if (timestampNanoType.shouldAdjustToUTC()) {
            return FlinkOrcReaders.timestampTzs();
          } else {
            return FlinkOrcReaders.timestamps();
          }
        case STRING:
          return FlinkOrcReaders.strings();
        case UUID:
        case FIXED:
        case BINARY:
          return OrcValueReaders.bytes();
        case DECIMAL:
          Types.DecimalType decimalType = (Types.DecimalType) iPrimitive;
          return FlinkOrcReaders.decimals(decimalType.precision(), decimalType.scale());
        default:
          throw new IllegalArgumentException(
              String.format(
                  "Invalid iceberg type %s corresponding to ORC type %s", iPrimitive, primitive));
      }
    }
  }
}

View on GitHub (pinned to 86d9c8fc54)

Solutions

Align the Iceberg schema with the actual ORC file types, or rewrite the ORC files with matching types.
Use schema projection/naming consistent with the file's written schema (check table metadata snapshots).
Verify the file was written by Iceberg ORC writer; if not, import with correct type mapping.

Example fix

// before
Schema s = new Schema(required(1, "f", Types.StringType.get())); // ORC column is double
// after
Schema s = new Schema(required(1, "f", Types.DoubleType.get())); // matches ORC type

Defensive patterns

Strategy: validation

Validate before calling

// check Iceberg type matches ORC physical type before reading
if (icebergType.typeId() != expectedIdFor(orcType)) {
  throw new IllegalStateException("Iceberg/ORC type mismatch on column " + field);
}

Type guard

boolean matchesOrc(Type.PrimitiveType p, OrcProto.Type orc) { return ORC_KIND_BY_ICEBERG.get(p.typeId()) == orc.getKind(); }

Try / catch

try { reader.read(...); } catch (IllegalArgumentException e) { /* realign schema or rewrite files */ }

Prevention

Import external ORC files with an explicit matching schema
Verify file types with ORC metadata tools before reads
Avoid schema overwrites that diverge from physical ORC types

When it happens

Trigger: Reading ORC files where the Iceberg schema's primitive for a column doesn't correspond to the ORC field type (e.g. Iceberg LongType against an ORC double, or an unmapped Iceberg primitive hitting default).

Common situations: ORC files written outside Iceberg with mismatched types; schema evolution mismatched the file's physical types; corrupt/mismatched ORC metadata.

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

AI-assisted analysis of apache/iceberg@86d9c8fc54 (2026-09-12). Data as JSON: /api/errors/55f2b9793dc531d0. Report an issue: GitHub.