apache/iceberg · error · UnsupportedOperationException

does not support dropping tables

Error message

${CLASS_NAME} does not support dropping tables

What it means

SparkRewriteTableCatalog is a build-and-commit catalog used only for staged rewrite procedures (e.g. REWRITE DATA FILES). It intentionally implements table mutation methods as unsupported: dropping a table through it would bypass the rewrite protocol, so any dropTable call throws UnsupportedOperationException with the catalog class name.

Solutions

  1. Use SparkCatalog (org.apache.iceberg.spark.SparkCatalog) or SparkSessionCatalog as the catalog implementation for DDL operations
  2. Register the rewrite catalog only for procedure-style rewrite usage, not as the session default catalog
  3. Catch UnsupportedOperationException and route DDL to the real Hive/REST/Hadoop catalog

Example fix

// before
spark.sql.catalog.ice = org.apache.iceberg.spark.SparkRewriteTableCatalog
// after
spark.sql.catalog.ice = org.apache.iceberg.spark.SparkCatalog
Defensive patterns

Strategy: try-catch

Validate before calling

// verify the catalog supports mutation before DDL
if (catalog instanceof SparkRewriteTableCatalog) {
  throw new IllegalStateException("Route DDL to a full catalog, not the rewrite catalog");
}

Type guard

boolean supportsDdl(CatalogPlugin c) {
  return c instanceof SparkCatalog || c instanceof SparkSessionCatalog;
}

Try / catch

try {
  catalog.dropTable(ident);
} catch (UnsupportedOperationException e) {
  // fall back to the production catalog
  prodCatalog.dropTable(ident);
}

Prevention

When it happens

Trigger: Calling dropTable(ident) on a catalog registered as org.apache.iceberg.spark.SparkRewriteTableCatalog, e.g. running DROP TABLE against a Spark session whose session/catalog config points at the rewrite catalog, or invoking SparkCatalog/Spark3Util paths that delegate mutation to it.

Common situations: Misconfigured spark.sql.catalog.<name>.implementation pointing at SparkRewriteTableCatalog instead of SparkCatalog; SQL scripts that assume all Iceberg catalogs support DDL; automated table lifecycle jobs hitting the wrong catalog.

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

AI-assisted analysis of apache/iceberg@86d9c8fc54 (2026-09-12). Data as JSON: /api/errors/ebfe1a6e40d3d976. Report an issue: GitHub.

Appendix: source

Thrown at spark/v4.2/spark/src/main/java/org/apache/iceberg/spark/SparkRewriteTableCatalog.java:90

  public void invalidateTable(Identifier ident) {
    throw new UnsupportedOperationException(CLASS_NAME + " does not support table invalidation");
  }

  @Override
  public SparkTable createTable(
      Identifier ident, StructType schema, Transform[] partitions, Map<String, String> properties)
      throws TableAlreadyExistsException {
    throw new UnsupportedOperationException(CLASS_NAME + " does not support creating tables");
  }

  @Override
  public SparkTable alterTable(Identifier ident, TableChange... changes) {
    throw new UnsupportedOperationException(CLASS_NAME + " does not support altering tables");
  }

  @Override
  public boolean dropTable(Identifier ident) {
    throw new UnsupportedOperationException(CLASS_NAME + " does not support dropping tables");
  }

  @Override
  public boolean purgeTable(Identifier ident) throws UnsupportedOperationException {
    throw new UnsupportedOperationException(CLASS_NAME + " does not support purging tables");
  }

  @Override
  public void renameTable(Identifier oldIdent, Identifier newIdent) {
    throw new UnsupportedOperationException(CLASS_NAME + " does not support renaming tables");
  }

  @Override
  public void initialize(String catalogName, CaseInsensitiveStringMap options) {
    this.name = catalogName;
  }

  @Override

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