apache/seatunnel · error · FileConnectorException

FILE_TYPE_INVALID

FILE_TYPE_INVALID

Error message

This file [%s] is not a parquet file, please check the format of this file

What it means

ParquetReadStrategy.readWithAvro first validates that the file assigned to the split really is a Parquet file (checkFileType inspects the magic header/extension). If not, it refuses to open it with FILE_TYPE_INVALID rather than failing later inside the parquet reader.

Source

Thrown at seatunnel-connectors-v2/connector-file/connector-file-base/src/main/java/org/apache/seatunnel/connectors/seatunnel/file/source/reader/ParquetReadStrategy.java:127

            log.warn(
                    "Failed to read parquet file [{}] with Avro reader due to illegal Avro field"
                            + " name, fallback to native parquet reader",
                    split.getFilePath(),
                    e);
            readWithNativeParquet(split, output);
        }
    }

    private void readWithAvro(FileSourceSplit split, Collector<SeaTunnelRow> output)
            throws IOException, FileConnectorException {
        String tableId = split.getTableId();
        String path = split.getFilePath();
        if (Boolean.FALSE.equals(checkFileType(path))) {
            String errorMsg =
                    String.format(
                            "This file [%s] is not a parquet file, please check the format of this file",
                            path);
            throw new FileConnectorException(FileConnectorErrorCode.FILE_TYPE_INVALID, errorMsg);
        }
        Path filePath = new Path(path);
        Map<String, String> partitionsMap = parsePartitionsByPath(path);
        HadoopInputFile hadoopInputFile =
                hadoopFileSystemProxy.doWithHadoopAuth(
                        (configuration, userGroupInformation) ->
                                HadoopInputFile.fromPath(filePath, configuration));
        int fieldsCount = seaTunnelRowType.getTotalFields();
        GenericData dataModel = new GenericData();
        dataModel.addLogicalTypeConversion(new Conversions.DecimalConversion());
        dataModel.addLogicalTypeConversion(new TimeConversions.DateConversion());
        dataModel.addLogicalTypeConversion(new TimeConversions.LocalTimestampMillisConversion());
        final boolean useSplitRange =
                enableSplitFile && split.getStart() >= 0 && split.getLength() > 0;
        GenericRecord record;
        AvroParquetReader.Builder<GenericData.Record> builder =
                AvroParquetReader.<GenericData.Record>builder(hadoopInputFile)
                        .withDataModel(dataModel);

View on GitHub (pinned to cf67b549a7)

Solutions

Verify the actual format with `file <path>` or by checking the first bytes for the 'PAR1' magic.
Correct the file_format_type in the source config to match the real file format.
Narrow the source path/pattern so only genuine Parquet files are matched.
Re-export/convert the data to real Parquet if the files were mislabeled.

Example fix

// before
FaT = { source = { file = { file_format_type = "parquet", path = "/data/mixed" } } }

// after: match only parquet files
path = "/data/mixed/*.parquet" // and confirm magic bytes are PAR1

Defensive patterns

Strategy: validation

Validate before calling

// Verify parquet magic bytes before configuring/reading the path
byte[] head = new byte[4];
try (InputStream in = Files.newInputStream(Paths.get(path))) {
    if (in.read(head) != 4 || !Arrays.equals(head, "PAR1".getBytes(StandardCharsets.US_ASCII))) {
        throw new IllegalStateException(path + " is not a parquet file");
    }
}

Try / catch

try {
    rows = parquetSource.read();
} catch (FileConnectorException e) {
    if (e.getMessage().contains("is not a parquet file")) {
        // switch file_format_type or fix the path pattern
    } else throw e;
}

Prevention

Check magic bytes ('PAR1') rather than trusting file extensions
Don't mix formats in a single source directory
Use precise path patterns (e.g. *.parquet) in the source config
Validate a sample file after every upstream format/export change

When it happens

Trigger: A source read reaches readWithAvro (via read) for a file whose path fails checkFileType — i.e. the file is not Parquet (wrong magic bytes or extension) while the read strategy selected is the Parquet one.

Common situations: file_format_type configured as parquet but the directory contains ORC/CSV/text files; files with .parquet extension that are actually another format; mixed-format directories read via a wildcard path.

Understand the failure class

Background: "is not a compatible type" / "cannot merge" errors: when a value's type doesn't match what the library requires — this error's family across 65 libraries.

Related errors

AI-assisted analysis of apache/seatunnel@cf67b549a7 (2026-09-10). Data as JSON: /api/errors/54da27b038d2afec. Report an issue: GitHub.