apache/iceberg · error · UnsupportedOperationException

Cannot drop partition field in non-Iceberg table: $table

Error message

Cannot drop partition field in non-Iceberg table: $table

What it means

This UnsupportedOperationException is thrown by Spark's DROP PARTITION FIELD execution when the target table is not an Iceberg table. Partition field (partition spec evolution) changes are Iceberg-only; the non-Iceberg table case falls through to the default match and throws.

Source

Thrown at spark/v4.2/spark-extensions/src/main/scala/org/apache/spark/sql/execution/datasources/v2/DropPartitionFieldExec.scala:58

        val schema = iceberg.table.schema
        transform match {
          case IdentityTransform(FieldReference(parts))
              if parts.size == 1 && schema.findField(parts.head) == null =>
            // the name is not present in the Iceberg schema, so it must be a partition field name, not a column name
            iceberg.table
              .updateSpec()
              .removeField(parts.head)
              .commit()

          case _ =>
            iceberg.table
              .updateSpec()
              .removeField(Spark3Util.toIcebergTerm(transform))
              .commit()
        }

      case table =>
        throw new UnsupportedOperationException(
          s"Cannot drop partition field in non-Iceberg table: $table")
    }

    Nil
  }

  override def simpleString(maxFields: Int): String = {
    s"DropPartitionField ${catalog.name}.${ident.quoted} ${transform.describe}"
  }
}

View on GitHub (pinned to 86d9c8fc54)

Solutions

1. Confirm the table is an Iceberg table
2. Qualify the table name with the Iceberg catalog in the DDL
3. Check spark.sql.catalog.<name> points to org.apache.iceberg.spark.SparkCatalog
4. Rewrite the statement to the native provider's partitioning API if the table is not Iceberg

Example fix

// before
ALTER TABLE other_table DROP PARTITION FIELD years(ts);
// after
ALTER TABLE iceberg_catalog.db.other_table DROP PARTITION FIELD years(ts);

val icebergTable = Spark3Util.loadIcebergTable(spark, fullTableName)
require(icebergTable != null, s"$fullTableName is not an Iceberg table")

def isIcebergTable(spark: SparkSession, name: String): Boolean =
  scala.util.Try(Spark3Util.loadIcebergTable(spark, name)).map(_ != null).getOrElse(false)

When it happens

Trigger: Running 'ALTER TABLE ... DROP PARTITION FIELD <transform>' where the table resolves to a non-Iceberg Spark table.

Common situations: Migrating DDL scripts written for Iceberg to tables in other formats; missing or wrong catalog qualification; catalog plugin misconfiguration.

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

• v4 manifests are not bound to a single partition spec
• Renaming a view is not supported by catalog: ${catalogName}
• Cannot convert predicate to SQL: <pred>
• Cannot convert term to SQL: <term>
• Cannot retrieve UUID for table <table.name()>

AI-assisted analysis of apache/iceberg@86d9c8fc54 (2026-09-12). Data as JSON: /api/errors/392453ec071d188d. Report an issue: GitHub.