apache/iceberg · error · java.lang.UnsupportedOperationException

SparkCachedTableCatalog does not support dropping tables

Error message

SparkCachedTableCatalog does not support dropping tables

What it means

SparkCachedTableCatalog.dropTable() unconditionally throws UnsupportedOperationException. The cached catalog only reads tables into a cache; it has no authority (or mechanism) to delete the underlying table from its owning catalog, so dropping is rejected by design.

Source

Thrown at spark/v3.5/spark/src/main/java/org/apache/iceberg/spark/SparkCachedTableCatalog.java:108

  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

View on GitHub (pinned to 86d9c8fc54)

Solutions

Issue the DROP TABLE against the catalog that owns the table (e.g. the SparkSession catalog the table was cached from).
Use Spark SQL with the fully qualified original identifier (spark_catalog.db.t) rather than the cached namespace.
If programmatic, obtain the org.apache.iceberg.catalog.SupportsDelete catalog and call dropTable there.

Example fix

// before
cachedCatalog.dropTable(Identifier.of(new String[]{"db"}, "t"));

// after
spark.sql("DROP TABLE spark_catalog.db.t"); // resolves to the owning catalog

Defensive patterns

Strategy: validation

Validate before calling

if (catalog instanceof SparkCachedTableCatalog) {
  throw new IllegalArgumentException("dropTable is not supported on SparkCachedTableCatalog; use the owning catalog");
}

Type guard

boolean canDrop = !(catalog instanceof SparkCachedTableCatalog);

Try / catch

try {
  catalog.dropTable(ident);
} catch (UnsupportedOperationException e) {
  // fall back to owning catalog: spark.sql("DROP TABLE spark_catalog.db.t")
}

Prevention

Never build cleanup/retention jobs on top of the cached catalog.
Resolve the owning catalog from the original identifier before destructive operations.
Add unit checks in tooling that DDL targets SparkCatalog/HiveCatalog, never the cached wrapper.

When it happens

Trigger: Calling SparkCachedTableCatalog.dropTable(ident), or executing DROP TABLE in Spark SQL when the identifier resolves to the cached-table catalog.

Common situations: Cleanup scripts that DROP TABLE a list of names without knowing which catalog resolved them; test harnesses assuming any CatalogPlugin supports drop; user runs DROP TABLE after querying via the cached path and expects the drop to hit the source table.

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/782fdeb17861f7dc. Report an issue: GitHub.