apache/beam · error · UnsupportedOperationException

Error while converting FieldSchema to HCatFieldSchema

Error message

Error while converting FieldSchema to HCatFieldSchema

What it means

SchemaUtils.toBeamField converts a Hive/HCard FieldSchema into a Beam Schema.Field. HCatSchemaUtils.getHCatFieldSchema failed with a checked HCatException, so the library wraps it as an UnsupportedOperationException. This means the incoming field definition from the Metastore could not be interpreted as an HCatFieldSchema.

Solutions

  1. Inspect the offending column's type string in the Hive Metastore (DESCRIBE table) and normalize it to a standard Hive type
  2. Upgrade/align hive-hcatalog and parquet-hadoop dependency versions with the Metastore version
  3. Pre-validate the table schema with HCatSchemaUtils.getHCatFieldSchema in a try/catch before running the Beam pipeline
  4. If the column is unusable, project around it or copy the table with only supported types

Example fix

// before
Schema schema = SchemaUtils.beamSchemaFromTableSchema(hcatSchema);
// after
for (HCatFieldSchema f : hcatSchema.getFields()) {
  try { HCatSchemaUtils.getHCatFieldSchema(f); }
  catch (HCatException e) { throw new IllegalArgumentException("Bad column: " + f.getName(), e); }
}
Schema schema = SchemaUtils.beamSchemaFromTableSchema(hcatSchema);
Defensive patterns

Strategy: validation

Validate before calling

try { HCatSchemaUtils.getHCatFieldSchema(field); } catch (HCatException e) { throw new IllegalArgumentException("Unsupported field " + field.getName(), e); }

Type guard

null

Try / catch

try { Schema s = SchemaUtils.beamSchema(hcatSchema); } catch (UnsupportedOperationException e) { throw new PipelineSchemaException("HCatalog schema invalid: " + e.getMessage(), e); }

Prevention

When it happens

Trigger: Calling HCatalogIO.read() whose table schema contains a FieldSchema that HCatSchemaUtils rejects (malformed type string, unsupported type descriptor, corrupted Metastore metadata).

Common situations: Tables created with non-standard or legacy Hive type strings; Metastore schema drift after a Hive version upgrade; partition-key schemas that differ from the storage schema.

Understand the failure class

Background: Schema validation failed / invalid input schema: payload rejected because its shape doesn't match the expected schema — this error's family across 28 libraries.

Related errors


AI-assisted analysis of apache/beam@12126d8942 (2026-09-13). Data as JSON: /api/errors/61c302fa3e26a836. Report an issue: GitHub.

Appendix: source

Thrown at sdks/java/io/hcatalog/src/main/java/org/apache/beam/sdk/io/hcatalog/SchemaUtils.java:68

          .put(HCatFieldSchema.Type.VARCHAR, FieldType.STRING)
          .put(HCatFieldSchema.Type.BINARY, FieldType.BYTES)
          .put(HCatFieldSchema.Type.DATE, FieldType.DATETIME)
          .put(HCatFieldSchema.Type.TIMESTAMP, FieldType.DATETIME)
          .build();

  static Schema toBeamSchema(List<FieldSchema> fields) {
    return fields.stream().map(SchemaUtils::toBeamField).collect(toSchema());
  }

  private static Schema.Field toBeamField(FieldSchema field) {
    String name = field.getName();
    HCatFieldSchema hCatFieldSchema;

    try {
      hCatFieldSchema = HCatSchemaUtils.getHCatFieldSchema(field);
    } catch (HCatException e) {
      // Converting checked Exception to unchecked Exception.
      throw new UnsupportedOperationException(
          "Error while converting FieldSchema to HCatFieldSchema", e);
    }

    switch (hCatFieldSchema.getCategory()) {
      case PRIMITIVE:
        {
          if (!HCAT_TO_BEAM_TYPES_MAP.containsKey(hCatFieldSchema.getType())) {
            throw new UnsupportedOperationException(
                "The Primitive HCat type '"
                    + field.getType()
                    + "' of field '"
                    + name
                    + "' cannot be converted to Beam FieldType");
          }

          FieldType fieldType = HCAT_TO_BEAM_TYPES_MAP.get(hCatFieldSchema.getType());
          return Schema.Field.of(name, fieldType).withNullable(true);
        }

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