apache/iceberg · error · java.lang.UnsupportedOperationException

Unsupported type - byte

Error message

Unsupported type - byte

What it means

IcebergArrowColumnVector delegates column access to an Arrow accessor for the vectorized Parquet reader. Iceberg's Spark vectorized read path never maps any physical/logical Iceberg type to an Arrow byte column, so getByte is intentionally unsupported and always throws UnsupportedOperationException.

Source

Thrown at spark/v4.2/spark/src/main/java/org/apache/iceberg/spark/data/vectorized/IcebergArrowColumnVector.java:90

  @Override
  public int numNulls() {
    return nullabilityHolder.numNulls();
  }

  @Override
  public boolean isNullAt(int rowId) {
    return nullabilityHolder.isNullAt(rowId) == 1;
  }

  @Override
  public boolean getBoolean(int rowId) {
    return accessor.getBoolean(rowId);
  }

  @Override
  public byte getByte(int rowId) {
    throw new UnsupportedOperationException("Unsupported type - byte");
  }

  @Override
  public short getShort(int rowId) {
    throw new UnsupportedOperationException("Unsupported type - short");
  }

  @Override
  public int getInt(int rowId) {
    return accessor.getInt(rowId);
  }

  @Override
  public long getLong(int rowId) {
    return accessor.getLong(rowId);
  }

  @Override

View on GitHub (pinned to 86d9c8fc54)

Solutions

1. Disable vectorized reads for tables with byte-typed columns: set read.vectorization.enabled=false on the table or session.
2. Check that the Iceberg runtime version matches your Spark version (spark.sql.extensions and iceberg-spark-runtime artifact); mismatched runtimes are a common cause.
3. Cast the tinyint column to integer in the query as a workaround so it uses getInt.
4. Upgrade Iceberg to a version adding byte support to IcebergArrowColumnVector, or implement getByte via an appropriate Arrow accessor.

if (schema.fields().stream().anyMatch(f -> f.dataType() == ByteType)) {
  spark.conf.set("read.vectorization.enabled", "false");
}

try { vector.getByte(rowId); } catch (UnsupportedOperationException e) {
  byte v = (byte) vector.getInt(rowId); // fallback via int accessor
}

When it happens

Trigger: Spark's VectorizedColumnReader or generated code invokes getByte(rowId) on an IcebergArrowColumnVector — e.g. reading a column whose Spark type is ByteType that got planned through the Arrow-based vectorized reader.

Common situations: Queries selecting tinyint columns where vectorization settings force the Arrow path; using an Iceberg/Spark version combination where byte-typed columns aren't covered by vectorized reads; schema mapping experiments that route byte data through Arrow readers.

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 - byte
• Unsupported type - short
• Unsupported type - short
• Cannot read unsupported column types:
• Unsupported type: boolean

AI-assisted analysis of apache/iceberg@86d9c8fc54 (2026-09-12). Data as JSON: /api/errors/79a127f965dd1215. Report an issue: GitHub.