prestodb/presto · error · ParquetDecodingException

Unsupported Parquet encoding:

Error message

Unsupported Parquet encoding: 

What it means

getParquetTypeUtils.getParquetEncoding maps Parquet's Encoding enum to the library's ParquetEncoding, and the default branch throws a ParquetDecodingException for any encoding it does not recognize. This means the file was written with an encoding this Presto-parquet build cannot decode — typically a newer encoding added after this code was compiled. The failure is unavoidable at read time without upgrading or rewriting the data.

Source

Thrown at presto-parquet/src/main/java/com/facebook/presto/parquet/ParquetTypeUtils.java:176

        switch (encoding) {
            case PLAIN:
                return ParquetEncoding.PLAIN;
            case RLE:
                return ParquetEncoding.RLE;
            case BIT_PACKED:
                return ParquetEncoding.BIT_PACKED;
            case PLAIN_DICTIONARY:
                return ParquetEncoding.PLAIN_DICTIONARY;
            case DELTA_BINARY_PACKED:
                return ParquetEncoding.DELTA_BINARY_PACKED;
            case DELTA_LENGTH_BYTE_ARRAY:
                return ParquetEncoding.DELTA_LENGTH_BYTE_ARRAY;
            case DELTA_BYTE_ARRAY:
                return ParquetEncoding.DELTA_BYTE_ARRAY;
            case RLE_DICTIONARY:
                return ParquetEncoding.RLE_DICTIONARY;
            default:
                throw new ParquetDecodingException("Unsupported Parquet encoding: " + encoding);
        }
    }

    public static org.apache.parquet.schema.Type getParquetTypeByName(String columnName, GroupType messageType)
    {
        if (messageType.containsField(columnName)) {
            return messageType.getType(columnName);
        }
        // parquet is case-sensitive, but hive is not. all hive columns get converted to lowercase
        // check for direct match above but if no match found, try case-insensitive match
        for (org.apache.parquet.schema.Type type : messageType.getFields()) {
            if (type.getName().equalsIgnoreCase(columnName)) {
                return type;
            }
        }

        return null;
    }

View on GitHub (pinned to 55bb57d202)

Solutions

1. Identify the offending encoding from the exception text and upgrade the Presto build / bundled parquet-mr library to a version that supports it.
2. Rewrite the Parquet file with an explicitly compatible encoding (e.g. SNAPPY-compressed PLAIN_DICTIONARY or RLE_DICTIONARY).
3. If you control the writer, disable the new encoding (e.g. set writer version/encoding options to a compatible set).
4. Check the column that failed; sometimes only one column type (e.g. FLOAT/DOUBLE with BYTE_STREAM_SPLIT) needs to be excluded or converted.

Example fix

// before: reading BYTE_STREAM_SPLIT file with old writer
spark.write().parquet("out");
// after: force compatible encodings on write
spark.conf.set("spark.sql.parquet.writer.version", "v1"); // PLAIN_DICTIONARY/RLE
spark.write().parquet("out");

// preflight: inspect encodings present in the file footer
for (ColumnChunkMetaData cc : footer.getBlocks().stream().flatMap(b -> b.getColumns().stream()).collect(toList())) {
    if (!SUPPORTED_ENCODINGS.contains(cc.getEncoding())) {
        throw new IllegalStateException("Unsupported encoding " + cc.getEncoding() + " in column " + cc.getPath());
    }
}

try {
    parquetRecordReader.nextRecord();
} catch (ParquetDecodingException e) {
    if (e.getMessage().startsWith("Unsupported Parquet encoding")) {
        // route file to a rewrite job with compatible encodings
    } else { throw e; }
}

When it happens

Trigger: Reading a Parquet column chunk whose page header declares an encoding enum value not handled by the switch (anything outside PLAIN, PLAIN_DICTIONARY, RLE, BIT_PACKED, DELTA_BINARY_PACKED, DELTA_LENGTH_BYTE_ARRAY, DELTA_BYTE_ARRAY, RLE_DICTIONARY).

Common situations: Files written by newer Parquet/Spark versions using encodings unknown to an old bundled parquet-mr; BYTE_STREAM_SPLIT encoded data; future/experimental encodings from other engines (e.g. newer writer defaults).

Related errors

• Failed to decode.
• We didn't read correct number of definitionLevels
• Still remaining to be read in current batch.
• Corrupted Parquet file: extra %d values to be consumed when
• Still remaining to be read in current batch.

AI-assisted analysis of prestodb/presto@55bb57d202 (2026-09-04). Data as JSON: /api/errors/ca0bc3e04dcf5c35. Report an issue: GitHub.