apache/flink · error · UnsupportedOperationException

Unsupported type

Error message

Unsupported type: {}

What it means

UnsupportedOperationException from the default branch of createVectorFromConstant in ParquetSplitReaderUtil. This utility materializes an in-memory constant column vector for a logical type (used to fill missing/all-null columns); the exhaustive switch covers primitives, timestamps, dates, etc., and any unhandled LogicalTypeRoot falls through to this throw.

Solutions

1. Ensure every projected column exists in the Parquet files so no constant/missing-column vector is needed for nested types
2. Cast or flatten the nested/exotic column out of the projection
3. Upgrade Flink - coverage of constant vectors for nested types has expanded over versions; check the changelog for your type

static boolean supportsConstantVector(LogicalTypeRoot root) {
    return root == LogicalTypeRoot.CHAR || root == LogicalTypeRoot.VARCHAR
            || root == LogicalTypeRoot.BOOLEAN || root == LogicalTypeRoot.TINYINT
            || root == LogicalTypeRoot.SMALLINT || root == LogicalTypeRoot.INTEGER
            || root == LogicalTypeRoot.BIGINT || root == LogicalTypeRoot.FLOAT
            || root == LogicalTypeRoot.DOUBLE || root == LogicalTypeRoot.DECIMAL
            || root == LogicalTypeRoot.DATE || root == LogicalTypeRoot.TIME_WITHOUT_TIME_ZONE
            || root == LogicalTypeRoot.TIMESTAMP_WITHOUT_TIME_ZONE
            || root == LogicalTypeRoot.TIMESTAMP_WITH_LOCAL_TIME_ZONE;
}

catch (UnsupportedOperationException e) { if (e.getMessage().startsWith("Unsupported type:")) { /* drop nested/exotic column from projection */ } else throw e; }

When it happens

Trigger: createVectorFromConstant(batchSize, type, value) invoked with a logical type outside the handled set - typically structured types (ARRAY/MAP/ROW/MULTISET) or exotic roots (STRUCTURED_TYPE, SYMBOL, DISTINCT_TYPE, UNRESOLVED) when a constant vector must be built for them.

Common situations: Reading tables where a nested (array/map/row) column is missing from a file and must be filled with nulls; table schemas containing rarely used SQL types not covered by the vectorized Parquet path in that Flink version.

Related errors

• is not supported now.
• A stream against this file was already created.
• Can not find column io for parquet reader.
• Corrupted Parquet schema
• could not decode the dictionary for

AI-assisted analysis of apache/flink@2f3c205e92 (2026-08-14). Data as JSON: /api/errors/1fc48834cec0ddd6. Report an issue: GitHub.

Appendix: source

Thrown at flink-formats/flink-parquet/src/main/java/org/apache/flink/formats/parquet/vector/ParquetSplitReaderUtil.java:284

                    dv.fill(((Number) value).doubleValue());
                }
                return dv;
            case DATE:
                if (value instanceof LocalDate) {
                    value = Date.valueOf((LocalDate) value);
                }
                return createVectorFromConstant(
                        new IntType(), value == null ? null : toInternal((Date) value), batchSize);
            case TIMESTAMP_WITHOUT_TIME_ZONE:
                HeapTimestampVector tv = new HeapTimestampVector(batchSize);
                if (value == null) {
                    tv.fillWithNulls();
                } else {
                    tv.fill(TimestampData.fromLocalDateTime((LocalDateTime) value));
                }
                return tv;
            default:
                throw new UnsupportedOperationException("Unsupported type: " + type);
        }
    }

    private static List<ColumnDescriptor> getAllColumnDescriptorByType(
            int depth, Type type, List<ColumnDescriptor> columns) throws ParquetRuntimeException {
        List<ColumnDescriptor> res = new ArrayList<>();
        for (ColumnDescriptor descriptor : columns) {
            if (depth >= descriptor.getPath().length) {
                throw new InvalidSchemaException("Corrupted Parquet schema");
            }
            if (type.getName().equals(descriptor.getPath()[depth])) {
                res.add(descriptor);
            }
        }

        // If doesn't find the type descriptor in corresponding depth, throw exception
        if (res.isEmpty()) {
            throw new InvalidSchemaException(

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