apache/iceberg · error · java.lang.UnsupportedOperationException

Unsupported type - map

Error message

Unsupported type - map

What it means

IcebergArrowColumnVector throws UnsupportedOperationException from getMap because Iceberg's Spark vectorized Arrow read path does not support reading map columns; map data must go through the non-vectorized row reader.

Source

Thrown at spark/v4.2/spark/src/main/java/org/apache/iceberg/spark/data/vectorized/IcebergArrowColumnVector.java:128

    return accessor.getFloat(rowId);
  }

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

  @Override
  public ColumnarArray getArray(int rowId) {
    if (isNullAt(rowId)) {
      return null;
    }
    return accessor.getArray(rowId);
  }

  @Override
  public ColumnarMap getMap(int rowId) {
    throw new UnsupportedOperationException("Unsupported type - map");
  }

  @Override
  public Decimal getDecimal(int rowId, int precision, int scale) {
    if (isNullAt(rowId)) {
      return null;
    }
    return accessor.getDecimal(rowId, precision, scale);
  }

  @Override
  public UTF8String getUTF8String(int rowId) {
    if (isNullAt(rowId)) {
      return null;
    }
    return accessor.getUTF8String(rowId);
  }

View on GitHub (pinned to 86d9c8fc54)

Solutions

1. Disable vectorized reads: set read.vectorization.enabled=false (table property) so map columns use the row-based reader.
2. Reproject the query to avoid selecting map columns directly (e.g. explode or extract keys/values via functions that route through supported readers).
3. Upgrade to an Iceberg release that adds map support to the vectorized reader for your Spark version.
4. Check whether an Iceberg/Spark runtime mismatch is accidentally enabling the Arrow path for map types.

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

try { vector.getMap(rowId); } catch (UnsupportedOperationException e) {
  // switch reader to the row-based (non-vectorized) path
}

When it happens

Trigger: A query selects a map-typed column while vectorized reads are enabled, and Spark's vectorized reader calls getMap(rowId) on the resulting IcebergArrowColumnVector.

Common situations: Reading Iceberg tables containing map columns with spark.read.format('iceberg') and vectorization on; scanning nested maps inside structs via the vectorized path; older Iceberg runtimes that lack vectorized map support.

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 - map
• Unsupported type - map
• Unsupported type - byte
• Unsupported type - byte
• Unsupported type - short

AI-assisted analysis of apache/iceberg@86d9c8fc54 (2026-09-12). Data as JSON: /api/errors/dbc9ec4438718f33. Report an issue: GitHub.